Compactness in quasi-Banach function spaces and applications to compact embeddings of Besov-type spaces

There are two main aims of the paper. The first one is to extend the criterion for the precompactness of sets in Banach function spaces to the setting of quasi-Banach function spaces. The second one is to extend the criterion for the precompactness of sets in the Lebesgue spaces $L_p(\Rn)$, $1 \leq p < \infty$, to the so-called power quasi-Banach function spaces. These criteria are applied to establish compact embeddings of abstract Besov spaces into quasi-Banach function spaces. The results are illustrated on embeddings of Besov spaces $B^s_{p,q}(\Rn)$, $0

Statistical modeling of protein lysate array data

The protein lysate array is an emerging technology for quantifying the protein concentration ratios in multiple biological samples. It is gaining popularity, and has the potential to answer questions about post-translational modifications and protein pathway relationships. Statistical inference for a parametric quantification procedure has been inadequately addressed in the literature, mainly due to two challenges: the increasing dimension of the parameter space and the need to account for dependence in the data. Each chapter of this thesis addresses one of these issues. In Chapter 1, an introduction to the protein lysate array quantification is presented, followed by the motivations and goals for this thesis work. In Chapter 2, we develop a multi-step procedure for the Sigmoidal models, ensuring consistent estimation of the concentration level with full asymptotic efficiency. The results obtained in this chapter justify inferential procedures based on large-sample approximations. Simulation studies and real data analysis are used to illustrate the performance of the proposed method in finite-samples. The multi-step procedure is simpler in both theory and computation than the single-step least squares method that has been used in current practice. In Chapter 3, we introduce a new model to account for the dependence structure of the errors by a nonlinear mixed effects model. We consider a method to approximate the maximum likelihood estimator of all the parameters. Using the simulation studies on various error structures, we show that for data with non-i.i.d. errors the proposed method leads to more accurate estimates and better confidence intervals than the existing single-step least squares method.

An algorithm for the inclusion of RC compact models of packages into board level thermal simulation tools

International audience

A parallel numerical solver using hierarchically tiled arrays

Solving linear systems is an important problem for scientific computing. Exploiting parallelism is essential for solving complex systems, and this traditionally involves writing parallel algorithms on top of a library such as MPI. The SPIKE family of algorithms is one well-known example of a parallel solver for linear systems. The Hierarchically Tiled Array data type extends traditional data-parallel array operations with explicit tiling and allows programmers to directly manipulate tiles. The tiles of the HTA data type map naturally to the block nature of many numeric computations, including the SPIKE family of algorithms. The higher level of abstraction of the HTA enables the same program to be portable across different platforms. Current implementations target both shared-memory and distributed-memory models. In this thesis we present a proof-of-concept for portable linear solvers. We implement two algorithms from the SPIKE family using the HTA library. We show that our implementations of SPIKE exploit the abstractions provided by the HTA to produce a compact, clean code that can run on both shared-memory and distributed-memory models without modification. We discuss how we map the algorithms to HTA programs as well as examine their performance. We compare the performance of our HTA codes to comparable codes written in MPI as well as current state-of-the-art linear algebra routines.

Spatial and temporal measurements using polyoxometalate, enzymatic and biofilm layers on a CMOS 0.35 μm 64 X 64-pixel I.S.F.E.T. array sensor

This thesis presents the achievements and scientific work conducted using a previously designed and fabricated 64 x 64-pixel ion camera with the use of a 0.35 μm CMOS technology. We used an array of Ion Sensitive Field Effect Transistors (ISFETs) to monitor and measure chemical and biochemical reactions in real time. The area of our observation was a 4.2 x 4.3 mm silicon chip while the actual ISFET array covered an area of 715.8 x 715.8 μm consisting of 4096 ISFET pixels in total with a 1 μm separation space among them. The ion sensitive layer, the locus where all reactions took place was a silicon nitride layer, the final top layer of the austriamicrosystems 0.35 μm CMOS technology used. Our final measurements presented an average sensitivity of 30 mV/pH. With the addition of extra layers we were able to monitor a 65 mV voltage difference during our experiments with glucose and hexokinase, whereas a difference of 85 mV was detected for a similar glucose reaction mentioned in literature, and a 55 mV voltage difference while performing photosynthesis experiments with a biofilm made from cyanobacteria, whereas a voltage difference of 33.7 mV was detected as presented in literature for a similar cyanobacterial species using voltamemtric methods for detection. To monitor our experiments PXIe-6358 measurement cards were used and measurements were controlled by LabVIEW software. The chip was packaged and encapsulated using a PGA-100 chip carrier and a two-component commercial epoxy. Printed circuit board (PCB) has also been previously designed to provide interface between the chip and the measurement cards.

Using a voxel-based krogh cylinder array to simulate microvascular contrast enhancement

The goal of this study is to better simulate microscopic and voxel-based dynamic contrast enhancement in magnetic resonance imaging. Specifically, errors imposed by the traditional two-compartment model are reduced by introducing a novel Krogh cylinder network. The two-compartment model was developed for macroscopic pharmacokinetic analysis of dynamic contrast enhancement and generalizing it to voxel dimensions, due to the significant decrease in scale, imposes physiologically unrealistic assumptions. In the project, a system of microscopic exchange between plasma and extravascular-extracellular space is built while numerically simulating the local contrast agent flow between and inside image elements. To do this, tissue parameter maps were created, contrast agent was introduced to the tissue via a flow lattice, and various data sets were simulated. The effects of sources, tissue heterogeneity, and the contribution of individual tissue parameters to an image are modeled. Further, the study attempts to demonstrate the effects of a priori flow maps on image contrast, indicating that flow data is as important as permeability data when analyzing tumor contrast enhancement. In addition, the simulations indicate that it may be possible to obtain tumor-type diagnostic information by acquiring both flow and permeability data.

A distributed, compact routing protocol for the Internet

The Internet has grown in size at rapid rates since BGP records began, and continues to do so. This has raised concerns about the scalability of the current BGP routing system, as the routing state at each router in a shortest-path routing protocol will grow at a supra-linearly rate as the network grows. The concerns are that the memory capacity of routers will not be able to keep up with demands, and that the growth of the Internet will become ever more cramped as more and more of the world seeks the benefits of being connected. Compact routing schemes, where the routing state grows only sub-linearly relative to the growth of the network, could solve this problem and ensure that router memory would not be a bottleneck to Internet growth. These schemes trade away shortest-path routing for scalable memory state, by allowing some paths to have a certain amount of bounded “stretch”. The most promising such scheme is Cowen Routing, which can provide scalable, compact routing state for Internet routing, while still providing shortest-path routing to nearly all other nodes, with only slightly stretched paths to a very small subset of the network. Currently, there is no fully distributed form of Cowen Routing that would be practical for the Internet. This dissertation describes a fully distributed and compact protocol for Cowen routing, using the k-core graph decomposition. Previous compact routing work showed the k-core graph decomposition is useful for Cowen Routing on the Internet, but no distributed form existed. This dissertation gives a distributed k-core algorithm optimised to be efficient on dynamic graphs, along with with proofs of its correctness. The performance and efficiency of this distributed k-core algorithm is evaluated on large, Internet AS graphs, with excellent results. This dissertation then goes on to describe a fully distributed and compact Cowen Routing protocol. This protocol being comprised of a landmark selection process for Cowen Routing using the k-core algorithm, with mechanisms to ensure compact state at all times, including at bootstrap; a local cluster routing process, with mechanisms for policy application and control of cluster sizes, ensuring again that state can remain compact at all times; and a landmark routing process is described with a prioritisation mechanism for announcements that ensures compact state at all times.

Ocean bottom pressure records from the Cascadia array and short surface gravity waves

The ocean bottom pressure records from eight stations of the Cascadia array are used to investigate the properties of short surface gravity waves with frequencies ranging from 0.2 to 5 Hz. It is found that the pressure spectrum at all sites is a well-defined function of the wind speed U10 and frequency f, with only a minor shift of a few dB from one site to another that can be attributed to variations in bottom properties. This observation can be combined with the theoretical prediction that the ocean bottom pressure spectrum is proportional to the surface gravity wave spectrum E(f) squared, times the overlap integral I(f) which is given by the directional wave spectrum at each frequency. This combination, using E(f) estimated from modeled spectra or parametric spectra, yields an overlap integral I(f) that is a function of the local wave age inline image. This function is maximum for f∕fPM = 8 and decreases by 10 dB for f∕fPM = 2 and f∕fPM = 30. This shape of I(f) can be interpreted as a maximum width of the directional wave spectrum at f∕fPM = 8, possibly equivalent to an isotropic directional spectrum, and a narrower directional distribution toward both the dominant low frequencies and the higher capillary-gravity wave frequencies.

The scientific rationale, design and implementation plan for a Biogeochemical-Argo float array

Biogeochemical-Argo is the extension of the Argo array of profiling floats to include floats that are equipped with biogeochemical sensors for pH, oxygen, nitrate, chlorophyll, suspended particles, and downwelling irradiance. Argo is a highly regarded, international program that measures the changing ocean temperature (heat content) and salinity with profiling floats distributed throughout the ocean. Newly developed sensors now allow profiling floats to also observe biogeochemical properties with sufficient accuracy for climate studies. This extension of Argo will enable an observing system that can determine the seasonal to decadal-scale variability in biological productivity, the supply of essential plant nutrients from deep-waters to the sunlit surface layer, ocean acidification, hypoxia, and ocean uptake of CO2. Biogeochemical-Argo will drive a transformative shift in our ability to observe and predict the effects of climate change on ocean metabolism, carbon uptake, and living marine resource management. Presently, vast areas of the open ocean are sampled only once per decade or less, with sampling occurring mainly in summer. Our ability to detect changes in biogeochemical processes that may occur due to the warming and acidification driven by increasing atmospheric CO2, as well as by natural climate variability, is greatly hindered by this undersampling. In close synergy with satellite systems (which are effective at detecting global patterns for a few biogeochemical parameters, but only very close to the sea surface and in the absence of clouds), a global array of biogeochemical sensors would revolutionize our understanding of ocean carbon uptake, productivity, and deoxygenation. The array would reveal the biological, chemical, and physical events that control these processes. Such a system would enable a new generation of global ocean prediction systems in support of carbon cycling, acidification, hypoxia and harmful algal blooms studies, as well as the management of living marine resources. In order to prepare for a global Biogeochemical-Argo array, several prototype profiling float arrays have been developed at the regional scale by various countries and are now operating. Examples include regional arrays in the Southern Ocean (SOCCOM ), the North Atlantic Sub-polar Gyre (remOcean ), the Mediterranean Sea (NAOS ), the Kuroshio region of the North Pacific (INBOX ), and the Indian Ocean (IOBioArgo ). For example, the SOCCOM program is deploying 200 profiling floats with biogeochemical sensors throughout the Southern Ocean, including areas covered seasonally with ice. The resulting data, which are publically available in real time, are being linked with computer models to better understand the role of the Southern Ocean in influencing CO2 uptake, biological productivity, and nutrient supply to distant regions of the world ocean. The success of these regional projects has motivated a planning meeting to discuss the requirements for and applications of a global-scale Biogeochemical-Argo program. The meeting was held 11-13 January 2016 in Villefranche-sur-Mer, France with attendees from eight nations now deploying Argo floats with biogeochemical sensors present to discuss this topic. In preparation, computer simulations and a variety of analyses were conducted to assess the resources required for the transition to a global-scale array. Based on these analyses and simulations, it was concluded that an array of about 1000 biogeochemical profiling floats would provide the needed resolution to greatly improve our understanding of biogeochemical processes and to enable significant improvement in ecosystem models. With an endurance of four years for a Biogeochemical-Argo float, this system would require the procurement and deployment of 250 new floats per year to maintain a 1000 float array. The lifetime cost for a Biogeochemical-Argo float, including capital expense, calibration, data management, and data transmission, is about $100,000. A global Biogeochemical-Argo system would thus cost about $25,000,000 annually. In the present Argo paradigm, the US provides half of the profiling floats in the array, while the EU, Austral/Asia, and Canada share most the remaining half. If this approach is adopted, the US cost for the Biogeochemical-Argo system would be ~$12,500,000 annually and ~$6,250,000 each for the EU, and Austral/Asia and Canada. This includes no direct costs for ship time and presumes that float deployments can be carried out from future research cruises of opportunity, including, for example, the international GO-SHIP program (http://www.go-ship.org). The full-scale implementation of a global Biogeochemical-Argo system with 1000 floats is feasible within a decade. The successful, ongoing pilot projects have provided the foundation and start for such a system.

A Thermal Management Solution for Compact Power Converters

Regulated Transformer Rectifier Units contain several power electronic boards to facilitate AC to DC power conversion. As these units become smaller, the number of devices on each board increases while their distance from each other decreases, making active cooling essential to maintaining reliable operation. Although it is widely accepted that liquid is a far superior heat transfer medium to air, the latter is still capable of yielding low device operating temperatures with proper heat sink and airflow design. The purpose of this study is to describe the models and methods used to design and build the thermal management system for one of the power electronic boards in a compact, high power regulated transformer rectifier unit. Maximum device temperature, available pressure drop and manufacturability were assessed when selecting the final design for testing. Once constructed, the thermal management system’s performance was experimentally verified at three different power levels.

Aluminum nanoholes for optical biosensing

Sub-wavelength diameter holes in thin metal layers can exhibit remarkable optical features that make them highly suitable for (bio)sensing applications. Either as efficient light scattering centers for surface plasmon excitation or metal-clad optical waveguides, they are able to form strongly localized optical fields that can effectively interact with biomolecules and/or nanoparticles on the nanoscale. As the metal of choice, aluminum exhibits good optical and electrical properties, is easy to manufacture and process and, unlike gold and silver, its low cost makes it very promising for commercial applications. However, aluminum has been scarcely used for biosensing purposes due to corrosion and pitting issues. In this short review, we show our recent achievements on aluminum nanohole platforms for (bio)sensing. These include a method to circumvent aluminum degradation—which has been successfully applied to the demonstration of aluminum nanohole array (NHA) immunosensors based on both, glass and polycarbonate compact discs supports—the use of aluminum nanoholes operating as optical waveguides for synthesizing submicron-sized molecularly imprinted polymers by local photopolymerization, and a technique for fabricating transferable aluminum NHAs onto flexible pressure-sensitive adhesive tapes, which could facilitate the development of a wearable technology based on aluminum NHAs.

Compact discs as versatile cost-effective substrates for releasable nanopatterned aluminium films

We demonstrate that standard polycarbonate compact disk surfaces can provide unique adhesion to Al films that is both strong enough to permit Al film nanopatterning and weak enough to allow easy nanopatterned Al film detachment using Scotch tape. Transferred Al nanohole arrays on Scotch tape exhibit excellent optical and plasmonic performance.

Design of Nanophotonic Antireflection Coatings for III-V Thin-Film Photovoltaics

Thin-film photovoltaics have provided a critical design avenue to help decrease the overall cost of solar power. However, a major drawback of thin-film solar cell technology is decreased optical absorption, making compact, high-quality antireflection coatings of critical importance to ensure that all available light enters the cell. In this thesis, we describe high efficiency thin-film InP and GaAs solar cells that utilize a periodic array of nanocylinders as antireflection coatings. We use coupled optical and electrical simulations to find that these nanophotonic structures reduce the solar-weighted average reflectivity of InP and GaAs solar cells to around 1.3 %, outperforming the best double-layer antireflection coatings. The coupling between Mie scattering resonances and thin-film interference effects accurately describes the optical enhancement provided by the nanocylinders. The spectrally resolved reflectivity and J-V characteristics of the devices under AM1.5G solar illumination are determined via the coupled optical and electrical simulations, resulting in predicted power conversion efficiencies > 23 %. We conclude that the nanostructured coatings reduce reflection without negatively affecting the electronic properties of the InP and GaAs solar cells by separating the nanostructured optical components from the active layer of the device.

Optimization of Energy Distribution in Solar Panel Array Configurations by Graph Theory and Minkowski’s Paths

Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know the performance of each of the PV modules that integrate the PV field in real time. In this respect, a PLC communications based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Malaga. With this device you can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface. Since these fluctuations in electricity production from a single panel affect the overall sum of all panels that conform a string, it is necessary to isolate the problem and modify the routes of energy through alternative paths in case of PV panels array configuration.