Ultracompact Retrodirective Antenna Arrays With Superdirective Radiation Patterns

It is shown that the direction-of-arrival (DoA) information carried by an incident electromagnetic (EM) wave can be encoded into the evanescent near field of an electrically small resonance antenna array with a spatial rate higher than that of the incident field oscillation rate in free space. Phase conjugation of the received signal leads to the retrodirection of the near field in the antenna array environment, which in turn generates a retrodirected far-field beam toward the original DoA. This EM phenomenon enables electrically small retrodirective antenna arrays with superdirective, angular super-resolution, auto-pointing properties for an arbitrary DoA. A theoretical explanation of the phenomenon based on first principal observations is given and full-wave simulations demonstrate a realizability route for the proposed retrodirective terminal that is comprised of resonance dipole antenna elements. Specifically, it is shown that a three-element disk-loaded retrodirective dipole array with 0.15\lambda spacings can achieve a 3.4-dBi maximal gain, 3-dBi front-to-back ratio, and 13% return loss fractional bandwidth (at the 10-dB level). Then, it is demonstrated that the radiation gain of a three-element array can be improved to approximately 6 dBi at the expense of the return loss fractional bandwidth reduction (2%).

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

Constructing stability landscapes to identify alternative states in coupled social-ecological agent-based models

The resilience of a social-ecological system is measured by its ability to retain core functionality when subjected to perturbation. Resilience is contextually dependent on the state of system components, the complex interactions among these components, and the timing, location, and magnitude of perturbations. The stability landscape concept provides a useful framework for considering resilience within the specified context of a particular social-ecological system but has proven difficult to operationalize. This difficulty stems largely from the complex, multidimensional nature of the systems of interest and uncertainty in system response. Agent-based models are an effective methodology for understanding how cross-scale processes within and across social and ecological domains contribute to overall system resilience. We present the results of a stylized model of agricultural land use in a small watershed that is typical of the Midwestern United States. The spatially explicit model couples land use, biophysical models, and economic drivers with an agent-based model to explore the effects of perturbations and policy adaptations on system outcomes. By applying the coupled modeling approach within the resilience and stability landscape frameworks, we (1) estimate the sensitivity of the system to context-specific perturbations, (2) determine potential outcomes of those perturbations, (3) identify possible alternative states within state space, (4) evaluate the resilience of system states, and (5) characterize changes in system-scale resilience brought on by changes in individual land use decisions.

Assessing the influence of abiotic factors and leaf-level properties on the stability of growing-season canopy greenness in a deciduous forest

Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change

Improving the stability of an oxime based electrochemical microsensor for organo-phosphate vapor detection

A micro gas sensor has been developed by our group for the detection of organo-phosphate vapors using an aqueous oxime solution. The analyte diffuses from the high flow rate gas stream through a porous membrane to the low flow rate aqueous phase. It reacts with the oxime PBO (1-Phenyl-1,2,3,-butanetrione 2-oxime) to produce cyanide ions, which are then detected electrochemically from the change in solution potential. Previous work on this oxime based electrochemistry indicated that the optimal buffer pH for the aqueous solution was approximately 10. A basic environment is needed for the oxime anion to form and the detection reaction to take place. At this specific pH, the potential response of the sensor to an analyte (such as acetic anhydride) is maximized. However, sensor response slowly decreases as the aqueous oxime solution ages, by as much as 80% in first 24 hours. The decrease in sensor response is due to cyanide which is produced during the oxime degradation process, as evidenced by the cyanide selective electrode. Solid phase micro-extraction carried out on the oxime solution found several other possible degradation products, including acetic acid, N-hydroxy benzamide, benzoic acid, benzoyl cyanide, 1-Phenyl 1,3-butadione, 2-isonitrosoacetophenone and an imine derived from the oxime. It was concluded that degradation occurred through nucleophilic attack by a hydroxide or oxime anion to produce cyanide, as well as a nitrogen atom rearrangement similar to Beckmann rearrangement. The stability of the oxime in organic solvents is most likely due to the lack of water, and specifically hydroxide ions. The reaction between oxime and organo-phosphate to produce cyanide ions requires hydroxide ions, and therefore pure organic solvents are not compatible with the current micro-sensor electrochemistry. By combining a concentrated organic oxime solution with the basic aqueous buffer just prior to being used in the detection process, oxime degradation can be avoided while preserving the original electrochemical detection scheme. Based on beaker cell experiments with selective cyanide sensitive electrodes, ethanol was chosen as the best organic solvent due to its stabilizing effect on the oxime, minimal interference with the aqueous electrochemistry, and compatibility with the current microsensor material (PMMA). Further studies showed that ethanol had a small effect on micro-sensor performance by reducing the rate of cyanide production and decreasing the overall response time. To avoid incomplete mixing of the aqueous and organic solutions, they were pre-mixed externally at a 10:1 ratio, respectively. To adapt the microsensor design to allow for mixing to take place within the device, a small serpentine channel component was fabricated with the same dimensions and material as the original sensor. This allowed for seamless integration of the microsensor with the serpentine mixing channel. Mixing in the serpentine microchannel takes place via diffusion. Both detector potential response and diffusional mixing improve with increased liquid residence time, and thus decreased liquid flowrate. Micromixer performance was studies at a 10:1 aqueous buffer to organic solution flow rate ratio, for a total rate of 5.5 μL/min. It was found that the sensor response utilizing the integrated micromixer was nearly identical to the response when the solutions were premixed and fed at the same rate.

Applications for nanomaterials in critical technologies

This thesis is devoted to the development, synthesis, properties, and applications of nano materials for critical technologies, including three areas: (1) Microbial contamination of drinking water is a serious problem of global significance. About 51% of the waterborne disease outbreaks in the United States can be attributed to contaminated ground water. Development of metal oxide nanoparticles, as viricidal materials is of technological and fundamental scientific importance. Nanoparticles with high surface areas and ultra small particle sizes have dramatically enhanced efficiency and capacity of virus inactivation, which cannot be achieved by their bulk counterparts. A series of metal oxide nanoparticles, such as iron oxide nanoparticles, zinc oxide nanoparticles and iron oxide-silver nanoparticles, coated on fiber substrates was developed in this research for evaluation of their viricidal activity. We also carried out XRD, TEM, SEM, XPS, surface area measurements, and zeta potential of these nanoparticles. MS2 virus inactivation experiments showed that these metal oxide nanoparticle coated fibers were extremely powerful viricidal materials. Results from this research suggest that zinc oxide nanoparticles with diameter of 3.5 nm, showing an isoelectric point (IEP) at 9.0, were well dispersed on fiberglass. These fibers offer an increase in capacity by orders of magnitude over all other materials. Compared to iron oxide nanoparticles, zinc oxide nanoparticles didn’t show an improvement in inactivation kinetics but inactivation capacities did increase by two orders of magnitude to 99.99%. Furthermore, zinc oxide nanoparticles have higher affinity to viruses than the iron oxide nanoparticles in presence of competing ions. The advantages of zinc oxide depend on high surface charge density, small nanoparticle sizes and capabilities of generating reactive oxygen species. The research at its present stage of development appears to offer the best avenue to remove viruses from water. Without additional chemicals and energy input, this system can be implemented by both points of use (POU) and large-scale use water treatment technology, which will have a significant impact on the water purification industry. (2) A new family of aliphatic polyester lubricants has been developed for use in micro-electromechanical systems (MEMS), specifically for hard disk drives that operate at high spindle speeds (>15000rpm). Our program was initiated to address current problems with spin-off of the perfluoroether (PFPE) lubricants. The new polyester lubricant appears to alleviate spin-off problems and at the same time improves the chemical and thermal stability. This new system provides a low cost alternative to PFPE along with improved adhesion to the substrates. In addition, it displays a much lower viscosity, which may be of importance to stiction related problems. The synthetic route is readily scalable in case additional interest emerges in other areas including small motors. (3) The demand for increased signal transmission speed and device density for the next generation of multilevel integrated circuits has placed stringent demands on materials performance. Currently, integration of the ultra low-k materials in dual Damascene processing requires chemical mechanical polishing (CMP) to planarize the copper. Unfortunately, none of the commercially proposed dielectric candidates display the desired mechanical and thermal properties for successful CMP. A new polydiacetylene thermosetting polymer (DEB-TEB), which displays a low dielectric constant (low-k) of 2.7, was recently developed. This novel material appears to offer the only avenue for designing an ultra low k dielectric (1.85k), which can still display the desired modulus (7.7Gpa) and hardness (2.0Gpa) sufficient to withstand the process of CMP. We focused on further characterization of the thermal properties of spin-on poly (DEB-TEB) ultra-thin film. These include the coefficient of thermal expansion (CTE), biaxial thermal stress, and thermal conductivity. Thus the CTE is 2.0*10-5K-1 in the perpendicular direction and 8.0*10-6 K-1 in the planar direction. The low CTE provides a better match to the Si substrate which minimizes interfacial stress and greatly enhances the reliability of the microprocessors. Initial experiments with oxygen plasma etching suggest a high probability of success for achieving vertical profiles.

Intercepting Cyclic Dinucleotide Signaling with Small Molecules

Bacterial infections, especially the ones that are caused by multidrug-resistant strains, are becoming increasingly difficult to treat and put enormous stress on healthcare systems. Recently President Obama announced a new initiative to combat the growing problem of antibiotic resistance. New types of antibiotic drugs are always in need to catch up with the rapid speed of bacterial drug-resistance acquisition. Bacterial second messengers, cyclic dinucleotides, play important roles in signal transduction and therefore are currently generating great buzz in the microbiology community because it is believed that small molecules that inhibit cyclic dinucleotide signaling could become next-generation antibacterial agents. The first identified cyclic dinucleotide, c-di-GMP, has now been shown to regulate a large number of processes, such as virulence, biofilm formation, cell cycle, quorum sensing, etc. Recently, another cyclic dinucleotide, c-di-AMP, has emerged as a regulator of key processes in Gram-positive and mycobacteria. C-di-AMP is now known to regulate DNA damage sensing, fatty acid synthesis, potassium ion transport, cell wall homeostasis and host type I interferon response induction. Due to the central roles that cyclic dinucleotides play in bacteria, we are interested in small molecules that intercept cyclic dinucleotide signaling with the hope that these molecules would help us learn more details about cyclic dinucleotide signaling or could be used to inhibit bacterial viability or virulence. This dissertation documents the development of several small molecule inhibitors of a cyclic dinucleotide synthase (DisA from B. subtilis) and phosphodiesterases (RocR from P. aeruginosa and CdnP from M. tuberculosis). We also demonstrate that an inhibitor of RocR PDE can inhibit bacterial swarming motility, which is a virulence factor.

Sparse Signal Representation in Digital and Biological Systems

Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

Synthesis and structural stability of metal-organic frameworks

Metal-organic frameworks (MOFs) have attracted significant attention during the past decade due to their high porosity, tunable structures, and controllable surface functionalities. Therefore many applications have been proposed for MOFs. All of them however are still in their infancy stage and have not yet been brought into the market place. In this thesis, the background of the MOF area is first briefly introduced. The main components and the motifs of designing MOFs are summarized, followed by their synthesis and postsynthetic modification methods. Several promising application areas of MOFs including gas storage and separation, catalysis and sensing are reviewed. The current status of commercialization of MOFs as new chemical products is also summarized. Examples of the design and synthesis of two new MOF structures Eu(4,4′,4′′,4′′′-(porphine-5,10,15,20-tetrayl)tetrakis(benzoic acid))·2H2O∙xDMF and Zn4O(azobenzene-4,4’-dicarboxylic acid)3∙xNMP are described. The first one contains free-base porphyrin centers and the second one has azobenzene components. Although the structures were synthesized as designed, unfortunately they did not possess the expected properties. The research idea to use MOFs as template materials to synthesize porous polymers is introduced. Several methods are discussed to grow PMMA into IRMOF-1 (Zn4O(benzene-1,4-dicarboxylate)3, IR stands for isoreticular) structure. High concentration of the monomers resulted in PMMA shell after MOF digestion while with low concentration of monomers no PMMA was left after digestion due to the small iii molecular weight. During the study of this chapter, Kitagawa and co-workers published several papers on the same topic, so this part of the research was terminated thereafter. Many MOFs are reported to be unstable in air due to the water molecules in air which greatly limited their applications. By incorporating a number of water repelling functional groups such as trifluoromethoxy group and methyl groups in the frameworks, the water stability of MOFs are shown to be significantly enhanced. Several MOFs inculding Banasorb-22 (Zn4O(2-trifluoromethoxybenzene-1,4-dicarboxylate)3), Banasorb-24 (Zn4O(2, 5-dimethylbenzene-1,4-dicarboxylate)3) and Banasorb-30 (Zn4O(2-methylbenzene-1,4-dicarboxylate)3) were synthesized and proved to have isostructures with IRMOF-1. Banasorb-22 was stable in boiling water steam for one week and Banasorb-30’s shelf life was over 10 months under ambient condition. For comparison, IRMOF-1’s structure collapses in air after a few hours to several days. Although MOF is a very popular research area nowadays, only a few studies have been reported on the mechanical properties of MOFs. Many of MOF’s applications involve high pressure conditions, so it is important to understand the behavior of MOFs under elivated pressures. The mechanical properties of IRMOF-1 and a new MOF structure Eu2(C12N2O4H6)3(DEF)0.87(H2O)2.13 were studied using diamond anvil cells at Advanced Photon Source. IRMOF-1 experienced an irriversible phase transtion to a nonporous phase followed by amorphization under high pressure. Eu2(C12N2O4H6)3(DEF)0.87(H2O)2.13 showed reversible compression under pressure up to 9.08GPa.

Multiscale Schemes for the BGK--Vlasov--Poisson System in the Quasi-Neutral and Fluid Limits. Stability Analysis and First Order Schemes

This paper deals with the development and the analysis of asymptotically stable and consistent schemes in the joint quasi-neutral and fluid limits for the collisional Vlasov-Poisson system. In these limits, the classical explicit schemes suffer from time step restrictions due to the small plasma period and Knudsen number. To solve this problem, we propose a new scheme stable for choices of time steps independent from the small scales dynamics and with comparable computational cost with respect to standard explicit schemes. In addition, this scheme reduces automatically to consistent discretizations of the underlying asymptotic systems. In this first work on this subject, we propose a first order in time scheme and we perform a relative linear stability analysis to deal with such problems. The framework we propose permits to extend this approach to high order schemes in the next future. We finally show the capability of the method in dealing with small scales through numerical experiments.

On the temperature stability of extracellular hemoglobin of Glossoscolex paulistus, at different oxidation states: SAXS and DLS studies

Glossoscolex paulistus hemoglobin (HbGp) was studied by dynamic light scattering (DLS) and small angle X-ray scattering (SAXS). DLS melting curves were measured for met-HbGp at different concentrations. SAXS temperature studies were performed for oxy-, cyanomet- and met-HbGp forms, at several pH values. At pH 5.0 and 6.0, the scattering curves are identical from 20 to 60 degrees C, and R-g is 108 angstrom, independent of the oxidation form. At pH 7.0, protein denaturation and aggregation occurs above 55 degrees C and 60 degrees C, for oxy and met-HbGp, respectively. Cyanomet-HbGp, at pH 7.0, is stable up to 60 degrees C. At alkaline pH (8.0-9.0) and higher temperature, an irreversible dissociation process is observed, with a decrease of R-g, D-max and I(0). Analysis by p(r), obtained from GNOM, and OLIGOMER, was used to fit the SAXS experimental scattering curves by a combination of theoretical curves obtained for HbLt fragments from the crystal structure. Our results show clearly the increasing contribution of smaller molecular weight fragments, as a function of increasing pH and temperature, as well as, the order of thermal stabilities: cyanomet-> oxy- > met-HbGp. (C) 2012 Elsevier B.V. All rights reserved.

Stability of membrane bound reactions

We present a novel approach to the dynamics of reactions of diffusing chemical species with species fixed in space e.g. by binding to a membrane. The non-diffusing reaction partners are clustered in areas with a diameter smaller than the diffusion length of the diffusing partner. The activated fraction of the fixed species determines the size of an active sub-region of the cluster. Linear stability analysis reveals that diffusion is one of the ma jor determinants of the stability of the dynamics. We illustrate the model concept with Ca²⁺ dynamics in living cells, which has release channels as fixed reaction partners. Our results suggest that spatial and temporal structures in intracellular Ca²⁺ dynamics are caused by fluctuations due to the small number of channels per cluster.

SLOPE STABILITY ANALYSIS OF MOUNT MEAGER, SOUTH-WESTERN BRITISH COLUMBIA, CANADA

The Mount Meager Volcanic Complex (MMVC) in south-western British Columbia is a potentially active, hydrothermally altered massif comprising a series of steep, glaciated peaks. Climatic conditions and glacial retreat has led to the further weathering, exposure and de-buttressing of steep slopes composed of weak, unconsolidated material. This has resulted in an increased frequency of landslide events over the past few decades, many of which have dammed the rivers bordering the Complex. The breach of these debris dams presents a risk of flooding to the downstream communities. Preliminary mapping showed there are numerous sites around the Complex where future failure could occur. Some of these areas are currently undergoing progressive slope movement and display features to support this such as anti-scarps and tension cracks. The effect of water infiltration on stability was modelled using the Rocscience program Slide 6.0. The main site of focus was Mount Meager in the south- east of the Complex where the most recent landslide took place. Two profiles through Mount Meager were analysed along with one other location in the northern section of the MMVC, where instability had been detected. The lowest Factor of Safety (FOS) for each profile was displayed and an estimate of the volume which could be generated was deduced. A hazard map showing the inundation zones for various volumes of debris flows was created from simulations using LAHARZ. Results showed the massif is unstable, even before infiltration. Varying the amount of infiltration appears to have no significant impact on the FOS annually implying that small changes of any kind could also trigger failure. Further modelling could be done to assess the impact of infiltration over shorter time scales. The Slide models show the volume of material that could be delivered to the Lillooet River Valley to be of the order of 109 m3 which, based on the LAHARZ simulations, would completely inundate the valley and communities downstream. A major hazard of this is that the removal of such a large amount of material has the potential to trigger an explosive eruption of the geothermal system and renew volcanic activity. Although events of this size are infrequent, there is a significant risk to the communities downstream of the complex.

Calculation of mutual information for nonlinear communication channel at large signal-to-noise ratio

Using the path-integral technique we examine the mutual information for the communication channel modeled by the nonlinear Schrödinger equation with additive Gaussian noise. The nonlinear Schrödinger equation is one of the fundamental models in nonlinear physics, and it has a broad range of applications, including fiber optical communications - the backbone of the internet. At large signal-to-noise ratio we present the mutual information through the path-integral, which is convenient for the perturbative expansion in nonlinearity. In the limit of small noise and small nonlinearity we derive analytically the first nonzero nonlinear correction to the mutual information for the channel.