Leaf Functional Traits and Forest Structure of Tropical Dry Forest Species Along a Rainfall Gradient in Florida and Puerto Rico

This study examined how different rainfall regimes affect a set of leaf functional traits related to plant stress and forest structure in tropical dry forest (TDF) species on limestone substrate. One hundred fifty eight individuals of four tree species were sampled in six ecological sites in south Florida and Puerto Rico, ranging in mean annual rainfall from 858 to 1933 mm yr-1. Leaf nitrogen content, specific leaf area (SLA), and N:P ratio of evergreen species, but not deciduous species, responded positively to increasing rainfall. Phosphorus content was unaffected in both groups. Canopy height and basal area reached maxima of 10.3 m and 31.4 m2 ha-1, respectively, at 1168 mm annual rainfall. Leaf traits reflected soil properties only to a small extent. This led us to the conclusion that water is a major limiting factor in TDF and some species that comprise TDF ecosystems are limited by nitrogen in limestone sites with less than ~1012 mm rainfall, but organismal, biological and/or abiotic forces other than rainfall control forest structure in moister sites.

Enhancement of field emission from multistage structure of carbon nanotube arrays

The field emission measurements for the multistage structured nanotubes (i.e., thin-multiwall and single wall carbon nanotubes grown on multiwall carbon nanotubes) were carried out and a low turn-on field of ~0.45 V/ μm, high emission current of 450 μA at a field of IV/μm and a large field enhancement factor of ~26200 were obtained. The thin multiwall carbon nanotubes (thin-MWNTs) and single wall carbon nanotubes (SWNTs) were grown on the regular arrays of vertically aligned multi wall carbon nanotubes (MWNTs) on porous silicon substrate by Chemical Vapor Deposition (CVD) method. The thin-MWNTs and SWNTs grown on MWNTs in this way have a multistage structure which gives higher enhancement of the electric field and hence the electron field emission.

(Table 1) Comparisons of dynamic and static Young's moduli of basalt at DSDP Holes 69-504B, 70-504B and 83-504B

Compressional- and shear-wave velocity logs (Vp and Vs, respectively) that were run to a sub-basement depth of 1013 m (1287.5 m sub-bottom) in Hole 504B suggest the presence of Layer 2A and document the presence of layers 2B and 2C on the Costa Rica Rift. Layer 2A extends from the mudline to 225 m sub-basement and is characterized by compressional-wave velocities of 4.0 km/s or less. Layer 2B extends from 225 to 900 m and may be divided into two intervals: an upper level from 225 to 600 m in which Vp decreases slowly from 5.0 to 4.8 km/s and a lower level from 600 to about 900 m in which Vp increases slowly to 6.0 km/s. In Layer 2C, which was logged for about 100 m to a depth of 1 km, Vp and Vs appear to be constant at 6.0 and 3.2 km/s, respectively. This velocity structure is consistent with, but more detailed than the structure determined by the oblique seismic experiment in the same hole. Since laboratory measurements of the compressional- and shear-wave velocity of samples from Hole 504B at Pconfining = Pdifferential average 6.0 and 3.2 km/s respectively, and show only slight increases with depth, we conclude that the velocity structure of Layer 2 is controlled almost entirely by variations in porosity and that the crack porosity of Layer 2C approaches zero. A comparison between the compressional-wave velocities determined by logging and the formation porosities calculated from the results of the large-scale resistivity experiment using Archie's Law suggest that the velocity- porosity relation derived by Hyndman et al. (1984) for laboratory samples serves as an upper bound for Vp, and the noninteractive relation derived by Toksöz et al. (1976) for cracks with an aspect ratio a = 1/32 serves as a lower bound.

Structure, Morphology, and Electrochemical Properties of Transition Metal Oxide, Hydroxide, and Phosphate Nanomaterials for Energy Storage

Energy storage technologies are crucial for efficient utilization of electricity. Supercapacitors and rechargeable batteries are of currently available energy storage systems. Transition metal oxides, hydroxides, and phosphates are the most intensely investigated electrode materials for supercapacitors and rechargeable batteries due to their high theoretical charge storage capacities resulted from reversible electrochemical reactions. Their insulating nature, however, causes sluggish electron transport kinetics within these electrode materials, hindering them from reaching the theoretical maximum. The conductivity of these transition metal based-electrode materials can be improved through three main approaches; nanostructuring, chemical substitution, and introducing carbon matrices. These approaches often lead to unique electrochemical properties when combined and balanced.

Ethanol-mediated solvothermal synthesis we developed is found to be highly effective for controlling size and morphology of transition metal-based electrode materials for both pseudocapacitors and batteries. The morphology and the degree of crystallinity of nickel hydroxide are systematically changed by adding various amounts glucose to the solvothermal synthesis. Nickel hydroxide produced in this manner exhibited increased pseudocapacitance, which is partially attributed to the increased surface area. Interestingly, this morphology effect on cobalt doped-nickel hydroxide is found to be more effective at low cobalt contents than at high cobalt contents in terms of improving the electrochemical performance.

Moreover, a thin layer of densely packed nickel oxide flakes on carbon paper substrate was successfully prepared via the glucose-assisted solvothermal synthesis, resulting in the improved electrode conductivity. When reduced graphene oxide was used for conductive coating on as-prepared nickel oxide electrode, the electrode conductivity was only slightly improved. This finding reveals that the influence of reduced graphene oxide coating, increasing the electrode conductivity, is not that obvious when the electrode is already highly conductive to begin with.

We were able to successfully control the interlayer spacing and reduce the particle size of layered titanium hydrogeno phosphate material using our ethanol-mediated solvothermal reaction. In layered structure, interlayer spacing is the key parameter for fast ion diffusion kinetics. The nanosized layered structure prepared via our method, however, exhibited high sodium-ion storage capacity regardless of the interlayer spacing, implying that interlayer space may not be the primary factor for sodium-ion diffusion in nanostructured materials, where many interstitials are available for sodium-ion diffusion.

Our ethanol-mediated solvothermal reaction was also effective for synthesis of NaTi2(PO4)3 nanoparticles with uniform size and morphology, well connected by a carbon nanotube network. This composite electrode exhibited high capacity, which is comparable to that in aqueous electrolyte, probably due to the uniform morphology and size where the preferable surface for sodium-ion diffusion is always available in all individual particles.

Fundamental understandings of the relationship between electrode microstructures and electrochemical properties discussed in this dissertation will be important to design high performance energy storage system applications.

Ultrahigh Purcell factor in low-threshold nanolaser based on asymmetric hybrid plasmonic cavity

A low-threshold nanolaser with all three dimensions at the subwavelength scale is proposed and investigated. The nanolaser is constructed based on an asymmetric hybrid plasmonic F-P cavity with Ag-coated end facets. Lasing characteristics are calculated using finite element method at the wavelength of 1550 nm. The results show that owing to the low modal loss, large modal confinement factor of the asymmetric plasmonic cavity structure, in conjunction with the high reflectivity of the Ag reflectors, a minimum threshold gain of 240 cm−1 is predicted. Furthermore, the Purcell factor as large as 2518 is obtained with optimized structure parameters to enhance rates of spontaneous and stimulated emission.

Maternal and paternal growth regulatory factor expression in hybrid sunfish.

Unidirectional hybridization between bluegill (Lepomis macrochirus) and pumpkinseed (L. gibbosus) sunfish enables researchers to explore the relative expression of paternal and maternal alleles in hybrids. Past studies have found that the metabolic dysfunction in bluegill-pumpkinseed hybrids may be due to incompatibilities between nuclear and mitochondrial genomes. However, the consequences of hybridization on body size and muscle growth have not been examined. This topic is particularly interesting because hybrids grow larger than parentals despite the fact that they are often sired by smaller, precociously mature bluegills. In order to improve our understanding of growth dynamics in hybrid sunfish, I conducted real-time quantitative PCR using species-specific primers on the white muscle tissue of bluegills, pumpkinseeds, and hybrids collected from Lake Opinicon, ON. Five growth factors that have been linked to muscle growth and body size demonstrated similar expression for maternal and paternal alleles. While about half of the hybrids showed the same pattern with myogenin, about half showed very low levels of mRNA for the paternal (bluegill) gene. While this did not explain the heterosis seen in hybrids, it may explain the small body phenotype of the cuckholding bluegill males. I explored the upstream genetic structure of bluegill myogenin and established that four alleles exist within the population. Furthermore, I uncovered a relationship in hybrids between the proximal promoter/ 5’ UTR of myogenin and its transcript level. I found that the hybrids demonstrating low paternal myogenin expression unfailingly possessed A3 or A4 alleles, but future studies will be needed to reveal the molecular links between the genotype and the growth phenotype. A similar genotype-phenotype association was not obvious in parentals, even those that were homozygous for these alleles. Whether this relationship can provide insight into the genetic determinants of bluegill alternative mating strategies has yet to be determined.

Importance of risk factor management in diabetic patients and reduction in Stage B heart failure

BACKGROUND: A number of studies have demonstrated the presence of a diabetic cardiomyopathy, increasing the risk of heart failure development in this population. Improvements in present-day risk factor control may have modified the risk of diabetes-associated cardiomyopathy.

AIM: We sought to determine the contemporary impact of diabetes mellitus (DM) on the prevalence of cardiomyopathy in at-risk patients with and without adjustment for risk factor control.

DESIGN: A cross-sectional study in a population at risk for heart failure.

METHODS: Those with diabetes were compared to those with other cardiovascular risk factors, unmatched, matched for age and gender and then matched for age, gender, body mass index, systolic blood pressure and low density lipoprotein cholesterol.

RESULTS: In total, 1399 patients enrolled in the St Vincent's Screening to Prevent Heart Failure (STOP-HF) cohort were included. About 543 participants had an established history of DM. In the whole sample, Stage B heart failure (asymptomatic cardiomyopathy) was not found more frequently among the diabetic cohort compared to those without diabetes [113 (20.8%) vs. 154 (18.0%), P = 0.22], even when matched for age and gender. When controlling for these risk factors and risk factor control Stage B was found to be more prevalent in those with diabetes [88 (22.2%)] compared to those without diabetes [65 (16.4%), P = 0.048].

CONCLUSION: In this cohort of patients with established risk factors for Stage B heart failure superior risk factor management among the diabetic population appears to dilute the independent diabetic insult to left ventricular structure and function, underlining the importance and benefit of effective risk factor control in this population on cardiovascular outcomes.

The large- and small-scale Ca IIK structure of the Milky Way from observations of Galactic and Magellanic sightlines

Aims. The large and small-scale (pc) structure of the Galactic interstellar medium can be investigated by utilising spectra of early-type stellar probes of known distances in the same region of the sky. This paper determines the variation in line strength of Ca ii at 3933.661 Å as a function of probe separation for a large sample of stars, including a number of sightlines in the Magellanic Clouds. 

Methods. FLAMES-GIRAFFE data taken with the Very Large Telescope towards early-type stars in 3 Galactic and 4 Magellanic open clusters in Ca ii are used to obtain the velocity, equivalent width, column density, and line width of interstellar Galactic calcium for a total of 657 stars, of which 443 are Magellanic Cloud sightlines. In each cluster there are between 43 and 111 stars observed. Additionally, FEROS and UVES Ca ii K and Na i D spectra of 21 Galactic and 154 Magellanic early-type stars are presented and combined with data from the literature to study the calcium column density - parallax relationship. 

Results. For the four Magellanic clusters studied with FLAMES, the strength of the Galactic interstellar Ca ii K equivalent width on transverse scales from ∼0.05-9 pc is found to vary by factors of ∼1.8-3.0, corresponding to column density variations of ∼0.3-0.5 dex in the optically-thin approximation. Using FLAMES, FEROS, and UVES archive spectra, the minimum and maximum reduced equivalent widths for Milky Way gas are found to lie in the range ∼35-125 mÅ and ∼30-160 mÅ for Ca ii K and Na i D, respectively. The range is consistent with a previously published simple model of the interstellar medium consisting of spherical cloudlets of filling factor ∼0.3, although other geometries are not ruled out. Finally, the derived functional form for parallax (π) and Ca ii column density (N_CaII) is found to be π(mas) = 1 / (2.39 × 10^-13 × N_CaII (cm^-2) + 0.11). Our derived parallax is ∼25 per cent lower than predicted by Megier et al. (2009, A&A, 507, 833) at a distance of ∼100 pc and ∼15 percent lower at a distance of ∼200 pc, reflecting inhomogeneity in the Ca ii distribution in the different sightlines studied.

Investigation of the Effect of Speed on the Dynamic Impact Factor for Bridges with Different Entrance Conditions, 2016

The dynamic interaction of vehicles and bridges results in live loads being induced into bridges that are greater than the vehicle’s static weight. To limit this dynamic effect, the Iowa Department of Transportation (DOT) currently requires that permitted trucks slow to five miles per hour and span the roadway centerline when crossing bridges. However, this practice has other negative consequences such as the potential for crashes, impracticality for bridges with high traffic volumes, and higher fuel consumption. The main objective of this work was to provide information and guidance on the allowable speeds for permitted vehicles and loads on bridges .A field test program was implemented on five bridges (i.e., two steel girder bridges, two pre-stressed concrete girder bridges, and one concrete slab bridge) to investigate the dynamic response of bridges due to vehicle loadings. The important factors taken into account during the field tests included vehicle speed, entrance conditions, vehicle characteristics (i.e., empty dump truck, full dump truck, and semi-truck), and bridge geometric characteristics (i.e., long span and short span). Three entrance conditions were used: As-is and also Level 1 and Level 2, which simulated rough entrance conditions with a fabricated ramp placed 10 feet from the joint between the bridge end and approach slab and directly next to the joint, respectively. The researchers analyzed and utilized the field data to derive the dynamic impact factors (DIFs) for all gauges installed on each bridge under the different loading scenarios.

Updating of Finite Element Models using static and dynamic optical strains with application to damage assessment

In the recent years, vibration-based structural damage identification has been subject of significant research in structural engineering. The basic idea of vibration-based methods is that damage induces mechanical properties changes that cause anomalies in the dynamic response of the structure, which measures allow to localize damage and its extension. Vibration measured data, such as frequencies and mode shapes, can be used in the Finite Element Model Updating in order to adjust structural parameters sensible at damage (e.g. Young’s Modulus). The novel aspect of this thesis is the introduction into the objective function of accurate measures of strains mode shapes, evaluated through FBG sensors. After a review of the relevant literature, the case of study, i.e. an irregular prestressed concrete beam destined for roofing of industrial structures, will be presented. The mathematical model was built through FE models, studying static and dynamic behaviour of the element. Another analytical model was developed, based on the ‘Ritz method’, in order to investigate the possible interaction between the RC beam and the steel supporting table used for testing. Experimental data, recorded through the contemporary use of different measurement techniques (optical fibers, accelerometers, LVDTs) were compared whit theoretical data, allowing to detect the best model, for which have been outlined the settings for the updating procedure.

Air Pollution and High Density Lipoprotein Structure and Function

Thesis (Ph.D.)--University of Washington, 2016-06

Quantifying Barriers to Meditation as a Health Behavior: Exploratory and Confirmatory Factor Analysis of the Determinants of Meditation Practice Inventory

Although the benefits of mindfulness meditation practices have been widely documented, research data suggest that there are barriers to regularly engaging in meditation behavior. In order to explore research questions pertaining to meditation initiation and adherence, psychometrically valid scales to assess barriers to meditation practice are necessary. The aim of the present study was to explore the factor structure and construct validity of the Determinants of Meditation Practice Inventory (DMPI) (Williams et al., 2011), a perceived barriers to meditation scale. Exploratory and confirmatory factor analyses along with construct validity tests were performed on data obtained from two large, community samples. Results supported the DMPI as a valid scale assessing perceived barriers with four factors, Lack of Interest, Knowledge Concerns, Pragmatic Concerns and Sociocultural Beliefs. The present study offers a DMPI-revised scale that may be reliably used to assess attitudes and beliefs that might impede meditation behavior.

Human Ezrin: Prediction of the 3D structure and interactions with mTOR

The protein Ezrin, is a member of the ERM family (Ezrin, Radixin and Moesin) that links the F-actin to the plasma membrane. The protein is made of three domains namely the FERM domain, a central α-helical domain and the CERMAD domain. The residues in Ezrin such as Ser66, Tyr145, Tyr353 and Tyr477 regulate the function of the protein through phosphorylation. The protein is found in two distinct conformations of active and dormant (inactive) state. The initial step during the conformation change is the breakage of intramolecular interaction in dormant Ezrin by phosphorylation of residue Thr567. The dormant structure of human Ezrin was predicted computationally since only partial active form structure was available. The validation analysis showed that 99.7% residues were positioned in favored, allowed and generously allowed regions of the Ramachandran plot. The Z-score of Ezrin was −7.36, G-factor was 0.1, and the QMEAN score of the model was 0.61 indicating a good model for human Ezrin. The comparison of the conformations of the activated and dormant Ezrin showed a major shift in the F2 lobe (residues 142-149 and 161-177) while changes in the conformation induced mobility shifts in lobe F3 (residues 261 to 267). The 3D positions of the phosphorylation sites Tyr145, Tyr353, Tyr477, Tyr482 and Thr567 were also located. Using targeted molecular dynamic simulation, the molecular movements during conformational change from active to dormant were visualized. The dormant Ezrin auto-inhibits itself by a head-to-tail interaction of the N-terminal and C-terminal residues. The trajectory shows the breakage of the interactions and mobility of the CERMAD domain away from the FERM domain. Protein docking and clustering analysis were used to predict the residues involved in the interaction between dormant Ezrin and mTOR. Residues Tyr477 and Tyr482 were found to be involved in interaction with mTOR.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.