Sparse covariance estimation in heterogeneous samples

Standard Gaussian graphical models (GGMs) implicitly assume that the conditional independence among variables is common to all observations in the sample. However, in practice, observations are usually collected form heterogeneous populations where such assumption is not satisfied, leading in turn to nonlinear relationships among variables. To tackle these problems we explore mixtures of GGMs; in particular, we consider both infinite mixture models of GGMs and infinite hidden Markov models with GGM emission distributions. Such models allow us to divide a heterogeneous population into homogenous groups, with each cluster having its own conditional independence structure. The main advantage of considering infinite mixtures is that they allow us easily to estimate the number of number of subpopulations in the sample. As an illustration, we study the trends in exchange rate fluctuations in the pre-Euro era. This example demonstrates that the models are very flexible while providing extremely interesting interesting insights into real-life applications

Reduced Switching Connectivity for Large Scale Antenna Selection

In this paper, we explore reduced-connectivity radio frequency (RF) switching networks for reducing the analog hardware complexity and switching power losses in antenna selection (AS) systems. In particular, we analyze different hardware architectures for implementing the RF switching matrices required in AS designs with a reduced number of RF chains. We explicitly show that fully-flexible switching matrices, which facilitate the selection of any possible subset of antennas and attain the maximum theoretical sum rates of AS, present numerous drawbacks such as the introduction of significant insertion losses, particularly pronounced in massive multiple-input multiple-output (MIMO) systems. Since these disadvantages make fully-flexible switching suboptimal in the energy efficiency sense, we further consider partially-connected switching networks as an alternative switching architecture with reduced hardware complexity, which we characterize in this work. In this context, we also analyze the impact of reduced switching connectivity on the analog hardware and digital signal processing of AS schemes that rely on channel power information. Overall, the analytical and simulation results shown in this paper demonstrate that partially-connected switching maximizes the energy efficiency of massive MIMO systems for a reduced number of RF chains, while fully-flexible switching offers sub-optimal energy efficiency benefits due to its significant switching power losses.Comment: 14 pages, 11 figure

Adjustment of model parameters to estimate distribution transformers remaining lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.Fil: Jimenez, Victor Adrian. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Will, Adrian L. E.. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Gotay Sardiñas, Jorge. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Rodriguez, Sebastian Alberto. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentin

Hybrid Analog-Digital Precoding Revisited under Realistic RF Modeling

In this paper we revisit hybrid analog-digital precoding systems with emphasis on their modelling and radio-frequency (RF) losses, to realistically evaluate their benefits in 5G system implementations. For this, we decompose the analog beamforming networks (ABFN) as a bank of commonly used RF components and formulate realistic model constraints based on their S-parameters. Specifically, we concentrate on fully-connected ABFN (FC-ABFN) and Butler networks for implementing the discrete Fourier transform (DFT) in the RF domain. The results presented in this paper reveal that the performance and energy efficiency of hybrid precoding systems are severely affected, once practical factors are considered in the overall design. In this context, we also show that Butler RF networks are capable of providing better performances than FC-ABFN for systems with a large number of RF chains.Comment: 12 pages, 5 figure

Digital-Analog Quantum Simulations with Superconducting Circuits

Quantum simulations consist in the intentional reproduction of physical or unphysical models into another more controllable quantum system. Beyond establishing communication vessels between unconnected fields, they promise to solve complex problems which may be considered as intractable for classical computers. From a historic perspective, two independent approaches have been pursued, namely, digital and analog quantum simulations. The former usually provide universality and flexibility, while the latter allows for better scalability. Here, we review recent literature merging both paradigms in the context of superconducting circuits, yielding: digital-analog quantum simulations. In this manner, we aim at getting the best of both approaches in the most advanced quantum platform involving superconducting qubits and microwave transmission lines. The discussed merge of quantum simulation concepts, digital and analog, may open the possibility in the near future for outperforming classical computers in relevant problems, enabling the reach of a quantum advantage.Comment: Review article, 26 pages, 4 figure

Native American Young Adults in their Transition to College, and Persistence Through the First Year

This dissertation study focused on a mixed-methods exploration of Native American students’ perceptions of risks and protective factors as they transitioned to college at a predominately White institution (PWI), and navigated through their first year. Due to low numbers of Native Americans at PWIs, individuals have described feeling invisible, which negatively impacts their ethnic identity development, sense of belonging, wellbeing, and retention in college. Factors involving respect, positive relationships, cultural affirmation, and resiliency are associated with success and retention for Native American students. A mixed-methods model, guided by grounded theory and principles of social justice advocacy provided a reflection on Native American first time freshmen’s perceived concerns related to transition as well as their coping efforts. Selection criteria included: (a) 18 years or older, (b) primary identification as Native American, and (c) enrollment in first semester of college. Eight interviews were conducted during Fall 2012 (September – October). Additional interviews were conducted during Fall 2013 (September - October) for a total of 10 original interviews and 2 follow-up interviews. Quantitative measures included the Experiences in Close Relationships Scale, the Native American Acculturation Scale, and the Bicultural Self-Efficacy Scale. Results suggested that all participants experienced anxiety during the first month and a half of their first year. No significant relationships between transition anxiety and measures of attachment, acculturation, or bicultural self-efficacy were found. Participants initially utilized established relationships with family and close others, primarily off-campus, to cope with concerns related to transition. As they became more familiar with campus culture through positive interactions with faculty, staff, teaching assistants, resident advisors, and classmates, participants described becoming less anxious. The reduction in anxiety occurred within their first month and a half on campus. Participants began to seek out academic and student services resources, and to form new connections with classmates, and other peers on campus. These early positive interactions lead to a sense of belonging. Through reflection on these early experiences, participants became more self-sufficient, and resilient. They identified new coping strategies for future concerns. This process also increased interest in further exploring Native American culture for some participants

Multimodal Imaging of Anisotropic Hierarchical Materials

The thesis is focused on studying the nanostructure of natural and synthetic hierarchical materials with biological applications, using X-ray scattering imaging and birefringence microscopy. The term "hierarchical materials" is used for structures composed of sub-units organised in different length scales that create the building blocks for the next level. Hierarchical materials are commonly found in nature, with diverse structures and functionalities. In the first part of this thesis, the nanostructure of mineralised tissue, such as tusk and bone, was the focus. Scanning SAXS, SAXS tensor tomography and birefringence microscopy were used to study the helicoidal structure of narwhal tusk. A high degree of anisotropy was found, in which the dentine and cementum have a very highly organised nanostructure with a preferential orientation along the tusk. However, those two main components differ in the deviations from that primary orientation, which revealed a complex helical pattern that could be the source of its anisotropic mechanical properties. A layered structure was also observed using X-ray fluorescence spectroscopy, indicating tusk growth layers that reflect the animal history. Those methods were also applied to study the anisotropic nanostructure of regenerated bone in biodegradable scaffolds and titanium implants in vivo, successfully demonstrating that the scaffold or implant architecture influence the new bone formation. Scaffolds with aligned fibres led to well-structured bone and a faster regeneration process, while scaffolds with randomly oriented fibres only created a callus around the damaged area with poor growth of new tissue.In the second part of this thesis, the anisotropy of self-assembled lyotropic liquid crystals for 3D printing of bone-mimetic composites was studied. This work aimed to understand the fundamental processes and mechanisms that induce the alignment of the self-assembled crystalline units to create composites with more anisotropic mechanical properties. In that study, an in situ characterisation of the nanostructure during flow in the 3D printer was done using scanning SAXS and birefringence microscopy to correlate the manufacturing process with the observed structural alignment of the material. The results demonstrated the role of the shear stress in such liquid crystals, highlighting the effect it has on the anisotropy and morphological transitions in the self-assembled structures. The importance of time and environmental conditions during 3D printing is also shown, which may affect the final structure and orientation

Study of the flow-induced structure and anisotropy in lyotropic liquid crystals for hierarchical composites

Controlling the micro and nanostructure of materials is highly beneficial in order to tailor\ua0their physical properties. Extrusion-based 3D printing is a promising tool to produce\ua0hierarchical structures with controlled architecture. Combining additive manufacturing and\ua0self-assembled materials, complex structures with high anisotropy can be created. Lyotropic\ua0liquid crystals offer a wide variety of structures and compositions, in which hexagonal andlamellar phases are very interesting options. Far from the idealistic concepts of 3D printing\ua0and extrusion, the variability of the different systems, physical properties of the inks and\ua0environmental conditions play a fundamental role in the appearance of imperfections,\ua0undesired nanostructures and the limitation in the maximum effective alignment achieved.\ua0To understand the mechanisms that induce alignment in liquid crystalline phases and produce\ua0secondary effects and imperfections, a combination of different methods was utilized. Using\ua0small-angle X-ray scattering as the main characterization tool, the nanostructure of the liquid crystals as well as the anisotropy was measured. The use of imaging techniques adds an extra\ua0dimension which brings a broader view of the self-assembled structure. Microfluidic channels\ua0were used to study the mechanisms of alignment in the confined space offered by the nozzle\ua0walls and the high pressures applied in the printing process. The confined flow in the printing\ua0nozzle has different properties and constraints compared to the open flow that the extruded\ua0filament encounters in the printing platform, which was studied by in-situ 3D printing in the\ua0X-ray beam. By complementary rheological characterization, a more detailed analysis\ua0understanding of the flow behaviour was achieved and birefringence microscopy opened up\ua0the possibilities of a time-resolved study of the anisotropy in the filament. The results demonstrated the role of the shear stress in liquid crystals in confined flow,\ua0highlighting both the effect it has on the anisotropy as well as on morphological transitions\ua0in the self-assembled structures. The performed experiments also reflect on the possible\ua0causes of misalignment such as stress release and try to find the optimal parameters in the\ua0nozzle design which lead to the best alignment in terms of homogeneity in the strand and\ua0maximizing the orientation. Finally, the results also show the importance of time and\ua0environmental conditions during 3D printing, which may affect the final structure and\ua0orientation prior the fixation of the nanostructure