The multinational enterprise as a source of international knowledge flows:Direct evidence from Italy

This paper examines the determinants of technology transfer between parent firms and their international affiliates, and of knowledge spillovers from those affiliates to host-country firms. Using a unique data set of foreign multinational enterprise (MNE) affiliates based in Italy, we find that affiliate investment in R&D and investment in capital-embodied technology plays a significant role in determining the nature of intra-firm technology flows. However, the basis for any spillovers arising from MNE affiliates does not originate from codified knowledge associated with R&D, but rather from the productivity of the affiliate.

Stochastically driven instability in rotating shear flows

Origin of hydrodynamic turbulence in rotating shear flows is investigated. The particular emphasis is on flows whose angular velocities decrease but specific angular momenta increase with increasing radial coordinate. Such flows are Rayleigh stable, but must be turbulent in order to explain observed data. Such a mismatch between the linear theory and observations/experiments is more severe when any hydromagnetic/magnetohydrodynamic instability and the corresponding turbulence therein is ruled out. The present work explores the effect of stochastic noise on such hydrodynamic flows. We focus on a small section of such a flow which is essentially a plane shear flow supplemented by the Coriolis effect. This also mimics a small section of an astrophysical accretion disk. It is found that such stochastically driven flows exhibit large temporal and spatial correlations of perturbation velocities, and hence large energy dissipations, that presumably generate instability. A range of angular velocity profiles (for the steady flow), starting with the constant angular momentum to that of the constant circular velocity are explored. It is shown that the growth and roughness exponents calculated from the contour (envelope) of the perturbed flows are all identical, revealing a unique universality class for the stochastically forced hydrodynamics of rotating shear flows. This work, to the best of our knowledge, is the first attempt to understand origin of instability and turbulence in the three-dimensional Rayleigh stable rotating shear flows by introducing additive stochastic noise to the underlying linearized governing equations. This has important implications in resolving the turbulence problem in astrophysical hydrodynamic flows such as accretion disks.

Magnetohydrodynamic stability of stochastically driven accretion flows

We investigate the evolution of magnetohydrodynamic (or hydromagnetic as coined by Chandrasekhar) perturbations in the presence of stochastic noise in rotating shear flows. The particular emphasis is the flows whose angular velocity decreases but specific angular momentum increases with increasing radial coordinate. Such flows, however, are Rayleigh stable but must be turbulent in order to explain astrophysical observed data and, hence, reveal a mismatch between the linear theory and observations and experiments. The mismatch seems to have been resolved, at least in certain regimes, in the presence of a weak magnetic field, revealing magnetorotational instability. The present work explores the effects of stochastic noise on such magnetohydrodynamic flows, in order to resolve the above mismatch generically for the hot flows. We essentially concentrate on a small section of such a flow which is nothing but a plane shear flow supplemented by the Coriolis effect, mimicking a small section of an astrophysical accretion disk around a compact object. It is found that such stochastically driven flows exhibit large temporal and spatial autocorrelations and cross-correlations of perturbation and, hence, large energy dissipations of perturbation, which generate instability. Interestingly, autocorrelations and cross-correlations appear independent of background angular velocity profiles, which are Rayleigh stable, indicating their universality. This work initiates our attempt to understand the evolution of three-dimensional hydromagnetic perturbations in rotating shear flows in the presence of stochastic noise. © 2013 American Physical Society.

Reconstruction of a stationary flow from boundary data using iterative methods

In this paper, three iterative procedures (Landweber-Fridman, conjugate gradient and minimal error methods) for obtaining a stable solution to the Cauchy problem in slow viscous flows are presented and compared. A section is devoted to the numerical investigations of these algorithms. There, we use the boundary element method together with efficient stopping criteria for ceasing the iteration process in order to obtain stable solutions.

Scaling and Multiscaling Exponents in Networks and Flows

The main focus of this paper is on mathematical theory and methods which have a direct bearing on problems involving multiscale phenomena. Modern technology is refining measurement and data collection to spatio-temporal scales on which observed geophysical phenomena are displayed as intrinsically highly variable and intermittant heirarchical structures,e.g. rainfall, turbulence, etc. The heirarchical structure is reflected in the occurence of a natural separation of scales which collectively manifest at some basic unit scale. Thus proper data analysis and inference require a mathematical framework which couples the variability over multiple decades of scale in which basic theoretical benchmarks can be identified and calculated. This continues the main theme of the research in this area of applied probability over the past twenty years.

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of the input space and the sample size n are usually the main ingredients in the characterization of data bigness. The specific statistical machine learning technique used to handle a particular big data set will depend on which category it falls in within the bigness taxonomy. Large p small n data sets for instance require a different set of tools from the large n small p variety. Among other tools, we discuss Preprocessing, Standardization, Imputation, Projection, Regularization, Penalization, Compression, Reduction, Selection, Kernelization, Hybridization, Parallelization, Aggregation, Randomization, Replication, Sequentialization. Indeed, it is important to emphasize right away that the so-called no free lunch theorem applies here, in the sense that there is no universally superior method that outperforms all other methods on all categories of bigness. It is also important to stress the fact that simplicity in the sense of Ockham’s razor non-plurality principle of parsimony tends to reign supreme when it comes to massive data. We conclude with a comparison of the predictive performance of some of the most commonly used methods on a few data sets.

Host and network optimizations for performance enhancement and energy efficiency in data center networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

Seismic scattering and absorption mapping of debris flows, feeding paths, and tectonic units at Mount St. Helens volcano

Acknowledgments We thank Edoardo Del Pezzo, Ludovic Margerin, Haruo Sato, Mare Yamamoto, Tatsuhiko Saito, Malcolm Hole, and Seth Moran for the valuable suggestions regarding the methodology and interpretation. Greg Waite provided the P wave velocity model of MSH. An important revision of the methods was done after two blind reviews performed before submission. The suggestions of two anonymous reviewers greatly enhanced our ability of imaging structures, interpreting our results, and testing their reliability. The facilities of the IRIS Data Management System, and specifically the IRIS Data Management Center, were used for access to waveform and metadata required in this study, and provided by the Cascades Volcano Observatory – USGS. Interaction with geologists and geographers part of the Landscape Dynamics Theme of the Scottish Alliance for Geoscience, Environment and Society (SAGES) has been important for the interpretation of the results.

Field data, numerical simulations and probability analyses to assess lava flow hazards at Mount Etna

Improving lava flow hazard assessment is one of the most important and challenging fields of volcanology, and has an immediate and practical impact on society. Here, we present a methodology for the quantitative assessment of lava flow hazards based on a combination of field data, numerical simulations and probability analyses. With the extensive data available on historic eruptions of Mt. Etna, going back over 2000 years, it has been possible to construct two hazard maps, one for flank and the other for summit eruptions, allowing a quantitative analysis of the most likely future courses of lava flows. The effective use of hazard maps of Etna may help in minimizing the damage from volcanic eruptions through correct land use in densely urbanized area with a population of almost one million people. Although this study was conducted on Mt. Etna, the approach used is designed to be applicable to other volcanic areas.

(Table 1) Sample locations and clay mineral data of sediment surface samples from the Barents Sea region

A new surface sediment sample set gained in the western Barents Sea by the MAREANO program has been analysed for basic clay mineral assemblages. Distribution maps including additional samples from earlier German research cruises to and off Svalbard are compiled. Some trends in the clay mineral assemblages are related to the sub-Barents Sea geology because the Quaternary sediment cover is rather thin. Additionally, land masses like Svalbard and northern Scandinavia dominate the clay mineral signal with their erosional products. Dense bottom water, very often of brine origin, that flows within deep troughs, such as the Storfjorden or Bear Island Trough, transport the clay mineral signal from their origin to the Norwegian-Greenland Sea.

A Game of Horns: Transnational Flows of Rhino Horn

A multi-sectorial regime of protection including international treaties, conservation and security measures, demand reduction campaigns and quasi-military interventions has been established to protect rhinos. Despite these efforts, the poaching of rhinos and trafficking of rhino horn continue unabated. This dissertation asks why the illegal market in rhinoceros horn is so resilient in spite of the myriad measures employed to disrupt it. A theoretical approach grounded in the sociology of markets is applied to explain the structure and functioning of the illegal market. The project follows flows of rhino horn from the source in southern Africa to illegal markets in Southeast Asia. The multi-sited ethnography included participant observations, interviews and focus groups with 416 informants during fourteen months of fieldwork. The sample comprised of, amongst others, convicted and active rhino poachers, smugglers and kingpins, private rhino breeders and hunting outfitters, African and Asian law enforcement officials, as well as affected local communities and Asian consumers. Court files, CITES trade data, archival materials, newspaper reports and social media posts were also analysed to supplement findings and to verify and triangulate data from interviews, focus groups and observations. Central to the analysis is the concept of “contested illegality”, a legitimization mechanism employed by market participants along the different segments of the horn supply chain. These actors' implicit or explicit contestation of the state-sponsored label of illegality serves as a legitimising and enabling mechanism, facilitating participation in gray or illegal markets for rhino horn. The research identified fluid interfaces between legal, illegal and gray markets, with recurring actors who have access to transnational trade structures, and who also possess market and product knowledge, as well as information about the regulatory regime and its loopholes. It is against the background of colonial, apartheid and neoliberal exploitation and marginalization of local communities that a second argument is introduced: the path dependency of conservation paradigms. Underpinning rhino conservation and regulation are archaic and elitist conservation regimes that discount the potential for harmonious relationships between local communities and wildlife. The increasing militarization of anti-poaching measures and green land grabs are exacerbating the rhino problem by alienating communities further from conservation areas and wild animals. The third argument looks at how actors deal with coordination problems in transnational illegal markets. Resolving the coordination problems of cooperation, value and competition are considered essential to the operation of formal markets. It is argued that the problem of security provides an additional and crucial obstacle to actors transacting in markets. The systematic analysis of flows between the researched sites of production, distribution and consumption of rhino horn shows that the social embeddedness of actors facilitates the flourishing of illegal markets in ways that escape an effective enforcement of CITES regulations.

Detached eddy simulation of unsteady turbulent flows in the draft tube of a bulb turbine

Les aspirateurs de turbines hydrauliques jouent un rôle crucial dans l’extraction de l’énergie disponible. Dans ce projet, les écoulements dans l’aspirateur d’une turbine de basse chute ont été simulés à l’aide de différents modèles de turbulence dont le modèle DDES, un hybride LES/RANS, qui permet de résoudre une partie du spectre turbulent. Déterminer des conditions aux limites pour ce modèle à l’entrée de l’aspirateur est un défi. Des profils d’entrée 1D axisymétriques et 2D instationnaires tenant compte des sillages et vortex induits par les aubes de la roue ont notamment été testés. Une fluctuation artificielle a également été imposée, afin d’imiter la turbulence qui existe juste après la roue. Les simulations ont été effectuées pour deux configurations d’aspirateur du projet BulbT. Pour la deuxième, plusieurs comparaisons avec des données expérimentales ont été faites pour deux conditions d’opération, à charge partielle et dans la zone de baisse rapide du rendement après le point de meilleur rendement. Cela a permis d’évaluer l’efficacité et les lacunes de la modélisation turbulente et des conditions limites à travers leurs effets sur les quantités globales et locales. Les résultats ont montrés que les structures tourbillonnaires et sillages sortant de la roue sont adéquatement résolus par les simulations DDES de l’aspirateur, en appliquant les profils instationnaires bidimensionnels et un schéma de faible dissipation pour le terme convectif. En outre, les effets de la turbulence artificielle à l’entrée de l’aspirateur ont été explorés à l’aide de l’estimation de l’intermittence du décollement, de corrélations en deux points, du spectre d’énergie et du concept de structures cohérentes lagrangiennes. Ces analyses ont montré que les détails de la dynamique de l’écoulement et de la séparation sont modifiés, ainsi que les patrons des lignes de transport à divers endroits de l’aspirateur. Cependant, les quantités globales comme le coefficient de récupération de l’aspirateur ne sont pas influencées par ces spécificités locales.

Computational modelling of non-equilibrium condensing steam flows in low-pressure steam turbines

The steam turbines play a significant role in global power generation. Especially, research on low pressure (LP) steam turbine stages is of special importance for steam turbine man- ufactures, vendors, power plant owners and the scientific community due to their lower efficiency than the high pressure steam turbine stages. Because of condensation, the last stages of LP turbine experience irreversible thermodynamic losses, aerodynamic losses and erosion in turbine blades. Additionally, an LP steam turbine requires maintenance due to moisture generation, and therefore, it is also affecting on the turbine reliability. Therefore, the design of energy efficient LP steam turbines requires a comprehensive analysis of condensation phenomena and corresponding losses occurring in the steam tur- bine either by experiments or with numerical simulations. The aim of the present work is to apply computational fluid dynamics (CFD) to enhance the existing knowledge and understanding of condensing steam flows and loss mechanisms that occur due to the irre- versible heat and mass transfer during the condensation process in an LP steam turbine. Throughout this work, two commercial CFD codes were used to model non-equilibrium condensing steam flows. The Eulerian-Eulerian approach was utilised in which the mix- ture of vapour and liquid phases was solved by Reynolds-averaged Navier-Stokes equa- tions. The nucleation process was modelled with the classical nucleation theory, and two different droplet growth models were used to predict the droplet growth rate. The flow turbulence was solved by employing the standard k-ε and the shear stress transport k-ω turbulence models. Further, both models were modified and implemented in the CFD codes. The thermodynamic properties of vapour and liquid phases were evaluated with real gas models. In this thesis, various topics, namely the influence of real gas properties, turbulence mod- elling, unsteadiness and the blade trailing edge shape on wet-steam flows, are studied with different convergent-divergent nozzles, turbine stator cascade and 3D turbine stator-rotor stage. The simulated results of this study were evaluated and discussed together with the available experimental data in the literature. The grid independence study revealed that an adequate grid size is required to capture correct trends of condensation phenomena in LP turbine flows. The study shows that accurate real gas properties are important for the precise modelling of non-equilibrium condensing steam flows. The turbulence modelling revealed that the flow expansion and subsequently the rate of formation of liquid droplet nuclei and its growth process were affected by the turbulence modelling. The losses were rather sensitive to turbulence modelling as well. Based on the presented results, it could be observed that the correct computational prediction of wet-steam flows in the LP turbine requires the turbulence to be modelled accurately. The trailing edge shape of the LP turbine blades influenced the liquid droplet formulation, distribution and sizes, and loss generation. The study shows that the semicircular trailing edge shape predicted the smallest droplet sizes. The square trailing edge shape estimated greater losses. The analysis of steady and unsteady calculations of wet-steam flow exhibited that in unsteady simulations, the interaction of wakes in the rotor blade row affected the flow field. The flow unsteadiness influenced the nucleation and droplet growth processes due to the fluctuation in the Wilson point.