Healthcare Network Modeling and Analysis

Part 20: Health and Care Networks

Radio Frequency Superconducting Quantum Interference Device Meta-atoms and Metamaterials: Experiment, Theory, and Analysis

Metamamterials are 1D, 2D or 3D arrays of articial atoms. The articial atoms, called "meta-atoms", can be any component with tailorable electromagnetic properties, such as resonators, LC circuits, nano particles, and so on. By designing the properties of individual meta-atoms and the interaction created by putting them in a lattice, one can create a metamaterial with intriguing properties not found in nature. My Ph. D. work examines the meta-atoms based on radio frequency superconducting quantum interference devices (rf-SQUIDs); their tunability with dc magnetic field, rf magnetic field, and temperature are studied. The rf-SQUIDs are superconducting split ring resonators in which the usual capacitance is supplemented with a Josephson junction, which introduces strong nonlinearity in the rf properties. At relatively low rf magnetic field, a magnetic field tunability of the resonant frequency of up to 80 THz/Gauss by dc magnetic field is observed, and a total frequency tunability of 100% is achieved. The macroscopic quantum superconducting metamaterial also shows manipulative self-induced broadband transparency due to a qualitatively novel nonlinear mechanism that is different from conventional electromagnetically induced transparency (EIT) or its classical analogs. A near complete disappearance of resonant absorption under a range of applied rf flux is observed experimentally and explained theoretically. The transparency comes from the intrinsic bi-stability and can be tuned on/ off easily by altering rf and dc magnetic fields, temperature and history. Hysteretic in situ 100% tunability of transparency paves the way for auto-cloaking metamaterials, intensity dependent filters, and fast-tunable power limiters. An rf-SQUID metamaterial is shown to have qualitatively the same behavior as a single rf-SQUID with regards to dc flux, rf flux and temperature tuning. The two-tone response of self-resonant rf-SQUID meta-atoms and metamaterials is then studied here via intermodulation (IM) measurement over a broad range of tone frequencies and tone powers. A sharp onset followed by a surprising strongly suppressed IM region near the resonance is observed. This behavior can be understood employing methods in nonlinear dynamics; the sharp onset, and the gap of IM, are due to sudden state jumps during a beat of the two-tone sum input signal. The theory predicts that the IM can be manipulated with tone power, center frequency, frequency difference between the two tones, and temperature. This quantitative understanding potentially allows for the design of rf-SQUID metamaterials with either very low or very high IM response.

Microwave-assisted solvent extraction and analysis of shikimic acid from plant tissues.

A better method for determination of shikimate in plant tissues is needed to monitor exposure of plants to the herbicide glyphosate [N-(phosphonomethyl)glycine] and to screen the plant kingdom for high levels of this valuable phytochemical precursor to the pharmaceutical oseltamivir. A simple, rapid, and efficient method using microwave-assisted extraction (MWAE) with water as the extraction solvent was developed for the determination of shikimic acid in plant tissues. High performance liquid chromatography was used for the separation of shikimic acid, and chromatographic data were acquired using photodiode array detection. This MWAE technique was successful in recovering shikimic acid from a series of fortified plant tissues at more than 90% efficiency with an interference-free chromatogram. This allowed the use of lower amounts of reagents and organic solvents, reducing the use of toxic and/or hazardous chemicals, as compared to currently used methodologies. The method was used to determine the level of endogenous shikimic acid in several species of Brachiaria and sugarcane (Saccharum officinarum) and on B. decumbens and soybean (Glycine max) after treatment with glyphosate. The method was sensitive, rapid and reliable in all cases.

Modeling and analysis of thermoelectric energy conversion efficiency in nanostructures.

116 p.

Identification and analysis of novel virulence-defective Rhodococcus fascians mutants

Rhodococcus fascians é uma actinomiceta fitopatogénica que induz uma doença, conhecida como irritação frondosa, caracterizada pela indução de múltiplos rebentos, numa vasta gama de plantas herbáceas dicotiledóneas. O principal factor de patogenicidade da bactéria é a produção de uma mistura de 6 citoquininas codificadas pelos genes do operão fas que está localizado num plasmídeo linear associado à virulência, pFiD188. Este trabalho teve como objectivo a análise de dois novos loci deste plasmídeo associados à virulência: GT1 que codifica uma glicosiltransferase e os genes mtr1 e mtr2, grandemente homólogos, que codificam metiltransferases dependentes de SAM. Trabalhos prévios com 21D5, mutante na glicosiltransferase, mostraram que possui uma morfologia de colónia modificada e forma agregados em culturas líquidas. Neste trabalho demonstrou-se que essas características não afectam o crescimento em meio de cultura rico, mas levam à incapacidade de proliferação em condições de privação de nutrientes, tendo um impacto forte na competência epifítica. Este impacto foi demostrado pela atenuação severa da virulência em 21D5, que foi acompanhada de uma expressão alterada dos genes fas e att, essenciais para a virulência, e consequente redução da capacidade de invasão dos tecidos da planta e de produção dos factores de virulência. Demonstrou-se também que a expressão de GT1 é induzida por compostos que são acumulados em plantas nas fases iniciais da infecção, colocando a função de GT1 no começo da interacção. Tal como R. fascians, Streptomyces turgidiscabies possui um operão fas e dois genes mtr associados. R. fascians mutantes nestes genes mtr’s perderam a capacidade de provocar sintomas, mas produziram 2MeS-citoquininas, implicando que outras citoquininas metiladas são cruciais para a indução da doença. De modo a identificar os produtos de reacção das MTRs procedeu-se à análise do perfil de citoquininas de R. fascians em condições que induzem a expressão dos genes do operão fas e de S. turgidiscabies alimentados com SAM e adenina marcadas com 14C em TLC. No entanto, não foi possível a identificação de compostos dependentes de fas ou mtr nos sobrenadantes. Pela determinação do perfil de expressão dos genes mtr in vitro e in planta tornou-se claro que a regulação destes genes é muito complexa, sendo a sua expressão limitada a células de R. fascians que colonizam o hospedeiro. Para possibilitar a identificação dos produtos de recção de MTR, desenvolveu-se um protocolo que permite a expressão in planta em condições in vitro, o que permitirá a repetição dos ensaios de marcação com 14C.

User interaction monitoring and analysis framework

An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.

Microwave-assisted solvent extraction and analysis of shikimic acid from plant tissues.

2008

Design, development, and analysis of hybrid metal-composite tube for industrial application

In the aerospace, automotive, printing, and sports industries, the development of hybrid Carbon Fiber Reinforced Polymer (CFRP)-metal components is becoming increasingly important. The coupling of metal with CFRP in axial symmetric components results in reduced production costs and increased mechanical properties such as bending, torsional stiffness, mass reduction, damping, and critical speed compared to the single material-built ones. In this thesis, thanks to a novel methodology involving a rubbery/viscoelastic interface layer, several hybrid aluminum-CFRP prototype tubes were produced. Besides, an innovative system for the cure of the CFRP part has been studied, analyzed, tested, and developed in the company that financed these research activities (Reglass SRL, Minerbio BO, Italy). The residual thermal stresses and strains have been investigated with numerical models based on the Finite Element Method (FEM) and compared with experimental tests. Thanks to numerical models, it was also possible to reduce residual thermal stresses by optimizing the lamination sequence of CFRP and determining the influence of the system parameters. A novel software and methodology for evaluating mechanical and damping properties of specimens and tubes made in CFRP were also developed. Moreover, to increase the component's damping properties, rubber nanofibers have been produced and interposed throughout the lamination of specimens. The promising results indicated that the nanofibrous mat could improve the material damping factor over 77% and be adopted in CFRP components with a negligible increment of weight or losing mechanical properties.

Synthesis of Na-PSS geopolymers and analysis of the H2O/Na2O molar ratio influence over their mechanical properties

Geopolymers are solid aluminosilicate material made by mixing an activating solution and a solid precursor. This work studied the mechanisms of synthesis of metakaolin-based geopolymers and the influence of water content, described by the molar ratio H2O/Na2O, on the final product. The samples were tested using a Uniaxial Compressive Test (UCT) to define their compressive resistance. Two geopolymers series were synthetized and let them rest for 7- days and 28-days, each of them composed by six different sets. 7-day rest series showed that water addition had no relevant effect over its resistance while the 28-day rest series almost doubled the compressive resistance, although those with the highest H2O/Na2O molar ratio showed instead a drastic reduction. Two other series were synthesized by adding silt aggregate, a waste material obtained in the production of aggregate for concrete, corresponding to 10wt% and 20wt%of the metakaolin used. After 28 days of aging, these samples were tested via UCT to measure the variation of the compressive resistance after the silt addition. The aggregate has disruptive effects over the compressive resistance, but the 20wt% samples achieved a higher compressive resistance. Samples with highest and lowest compressive resistance have been chosen to carry out an XRD analysis. In all the samples it has been recognized the presence of Anatase (TiO2), a titanium oxide found in the metakaolin and Thermonatrite, a hydrated sodium carbonate [Na2CO3 • (H2O)]. Scanning Electron Microscopy was carried out on the samples with the highest compressive resistance and showed that the samples with lower water content developed a homogeneous geopolymeric texture, while those with higher water content showed instead a spongy-like texture and a higher air or pore solution bubbles presence. Silt/geopolymer composites showed a fracture system developing across the interstitial transition zone between the geopolymer matrix and the aggregate particle.

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

Development and Demonstration of a Freezing Drizzle Algorithm for Roadway Environmental Sensing Systems, Final Report, October 2012

The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Structural analysis of combinatorial optimization problem characteristics and their resolution using hybrid approaches

Many combinatorial problems coming from the real world may not have a clear and well defined structure, typically being dirtied by side constraints, or being composed of two or more sub-problems, usually not disjoint. Such problems are not suitable to be solved with pure approaches based on a single programming paradigm, because a paradigm that can effectively face a problem characteristic may behave inefficiently when facing other characteristics. In these cases, modelling the problem using different programming techniques, trying to ”take the best” from each technique, can produce solvers that largely dominate pure approaches. We demonstrate the effectiveness of hybridization and we discuss about different hybridization techniques by analyzing two classes of problems with particular structures, exploiting Constraint Programming and Integer Linear Programming solving tools and Algorithm Portfolios and Logic Based Benders Decomposition as integration and hybridization frameworks.