868 research outputs found

    Synthesis and NMR-based network structure analysis of cationic hydrogels for seawater applications

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    Superabsorbent polymers (SAPs) are hydrophilic polymer networks (i. e., hydrogels) that contain charged monomer units along the polymer backbone. Poly(sodium acrylate) (PSA), which has negatively charged carboxylate groups, is the most prominent chemical structure of SAPs. Recent studies have shown that PSA can be used as a separation medium for the desalination of salt water. This approach, however, is limited to NaCl solutions because the divalent Mg2+^{2+} and Ca2+^{2+} cations in seawater interact electrostatically with the anionic polymer backbone of PSA, inducing thereby a network collapse. To overcome this limitation, this dissertation explores the swelling and desalination capacity of cationic SAPs in seawater. Two cationic SAP model systems with distinct functional groups were synthesized. The first one is based on a poly(acrylamide) (PAM) derivative with a trimethyl quaternary ammonium group as the positively charged monomer unit. The second model system is based on poly(vinyl amine) (PVAm) bearing positively charged ammonium groups. Swelling capacity measurements reveal that divalent SO42−_{4}^{2-} anions in seawater induce a network collapse of PVAm similar to the PSA analogue. In contrast, the swelling behavior of PAM hydrogels is fully unaffected by seawater, suggesting that the quaternary ammonium moiety is essential to provide seawater resistant swelling properties of SAPs. In addition to swelling capacity studies, this dissertation aims to advance our understanding of the intriguing interplay between macroscopic, mechanical properties and molecular dynamics of the hydrogel network. Due to the inherent multi-length scale structural complexity of hydrogels, the quantitative correlation of mechanical properties with molecular dynamics remains a longstanding challenge. An advanced rheometer setup consisting of a portable low-field NMR unit that is integrated into a rheometer was used to study the gelation kinetics of acrylic acid (AAc) hydrogels. The elastic modulus G′ was studied by small amplitude oscillatory time sweeps whereas the local molecular mobility of polymer network chains was probed by T2_{2} relaxation measurements. From the in-situ G′ and T2_{2} correlation plots, it can be concluded that the elastic plateau modulus is inversely proportional to the T2_{2} relaxation time of the hydrogel. Consequently, the mechanical strength of hydrogels can be predicted based on the segmental mobility of polymer network chains, which has important implications for the further development of non-invasive and forceless mechanical characterization techniques

    BDS GNSS for Earth Observation

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    For millennia, human communities have wondered about the possibility of observing phenomena in their surroundings, and in particular those affecting the Earth on which they live. More generally, it can be conceptually defined as Earth observation (EO) and is the collection of information about the biological, chemical and physical systems of planet Earth. It can be undertaken through sensors in direct contact with the ground or airborne platforms (such as weather balloons and stations) or remote-sensing technologies. However, the definition of EO has only become significant in the last 50 years, since it has been possible to send artificial satellites out of Earth’s orbit. Referring strictly to civil applications, satellites of this type were initially designed to provide satellite images; later, their purpose expanded to include the study of information on land characteristics, growing vegetation, crops, and environmental pollution. The data collected are used for several purposes, including the identification of natural resources and the production of accurate cartography. Satellite observations can cover the land, the atmosphere, and the oceans. Remote-sensing satellites may be equipped with passive instrumentation such as infrared or cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the Earth’s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and Medium Earth Orbit (MEO), thus covering the entire Earth’s surface in a certain scan time (properly called ’temporal resolution’), i.e., in a certain number of orbits around the Earth. The first remote-sensing satellites were the American NASA/USGS Landsat Program; subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing satellite), RapidEye, the French SPOT (Satellite Pour l’Observation de laTerre), and the Canadian RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the Chinese BuFeng-1 and Fengyun-3 series. Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers worldwide for a multitude of Earth monitoring and exploration applications. On the other hand, over the past 40 years, GNSSs have become an essential part of many human activities. As is widely noted, there are currently four fully operational GNSSs; two of these were developed for military purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation Satellite System (IRNSS/NavIC), will become available in the next few years, which will have enormous potential for scientific applications and geomatics professionals. In addition to their traditional role of providing global positioning, navigation, and timing (PNT) information, GNSS navigation signals are now being used in new and innovative ways. Across the globe, new fields of scientific study are opening up to examine how signals can provide information about the characteristics of the atmosphere and even the surfaces from which they are reflected before being collected by a receiver. EO researchers monitor global environmental systems using in situ and remote monitoring tools. Their findings provide tools to support decision makers in various areas of interest, from security to the natural environment. GNSS signals are considered an important new source of information because they are a free, real-time, and globally available resource for the EO community

    Response of Bats and Nocturnal Food Webs to Mountain Pine Beetle (Dendroctonous Ponderosae) Outbreaks

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    Climate change has led to increased severity and frequency of forest disturbances globally which would predictably alter species compositions in affected habitats. Bats, as important bioindicators of ecosystem health, are known to respond to changes in habitat structure and prey composition. This dissertation describes how a forest disturbance event and ensuing successional changes altered the structure of bat-associated food web components along the highly biodiverse Front Range of Colorado. Mountain pine beetles (MPB) are important drivers of forest regeneration when populations are at background levels, however, unprecedented outbreaks of MPB populations in recent decades have severely impacted over 1.3 million hectares of lodgepole pine forests in Colorado. This has resulted in widespread structural changes in these forest habitats that comprise approximately 7% of the land area in the Rocky Mountains, and there are unclear patterns in the short-term shifts occurring in vegetation community composition following the recent MPB outbreak. The first project reported here (Chapter II) examines the community structure of vegetation in lodgepole pine forests after MPB-kill and relates time-since-kill and other environmental factors to ensuing secondary successional changes using a non-metric multidimensional scaling ordination. The second project (Chapter III) investigates how these shifting baselines in vegetation community structure alter bat-associated food web interactions in lodgepole pine ecosystems. The third project (Chapter IV) investigates activity patterns of tri-colored bats in these novel MPB-killed habitats and quantifies what site and environmental factors are influencing these patterns. Tri-colored bats (Perimyotis subflavus) are extending their distributional range westward in the United States including into the Front Range of Colorado. In sum, these projects describe how secondary successional patterns in lodgepole pine forests after severe beetle-kill disturbance shapes a diverse assemblage of vegetation, bats, and insects. This knowledge will help resource managers and biologists to better understand and plan for community and assembly-level management

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Statistical Modeling: Regression, Survival Analysis, and Time Series Analysis

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    Statistical Modeling provides an introduction to regression, survival analysis, and time series analysis for students who have completed calculus-based courses in probability and mathematical statistics. The book uses the R language to fit statistical models, conduct Monte Carlo simulation experiments and generate graphics. Over 300 exercises at the end of the chapters makes this an appropriate text for a class in statistical modeling. Part 1: RegressionChapter 1: Simple Linear Regression Chapter 2: Inference in Simple Linear Regression Chapter 3: Topics in RegressionPart II: Survival Analysis Chapter 4: Probability Models in Survival AnalysisChapter 5: Statistical Methods in Survival Analysis Chapter 6: Topics in Survival Analysis Part III: Time Series Analysis Chapter 7: Basic Methods in Time Series AnalysisChapter 8: Modeling in Time Series Analysis Chapter 9: Topics in Time Series Analysi

    PLACING THE EVOLUTIONARY HISTORY OF \u3ci\u3eDESMOGNATHUS\u3c/i\u3e SALAMANDERS IN CONTEXT: A PHYLOGEOGRAPHIC APPROACH

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    Patterns of genetic variation do not arise in a vacuum but are instead shaped by the interplay between evolutionary forces and ecological constraints. Here, I use a phylogeographic approach to examine the role that ecology played in lineage divergence in the Desmognathus quadramaculatus species complex (Family: Plethodontidae), which consists of three nominal species: D. quadramaculatus, D. marmoratus, and D. folkertsi. Previous phylogenetic studies have shown that individuals from these species do not form clades based on phenotype. My approach to reconciling phylogenetic discordance was two-fold, using (1) genome-wide markers to provide insight into the relationships among lineages and (2) geographic and climate data to provide context for patterns of genetic diversity. First, I obtained genome-wide nuclear markers using double-digest restriction-site associated DNA sequencing (ddRAD) to examine whether two morphologically divergent species, D. marmoratus and D. quadramaculatus, represent independently evolving lineages. Phylogenetic, population structure, and model testing analyses all confirmed that D. marmoratus and D. quadramaculatus do not group based on phenotype. Instead, I found that there were two cryptic genetic lineages (Nantahala and Pisgah) that each contained both phenotypes. Additionally, ecological niche modeling showed that the two genetic lineages primarily occupy geographic areas with significantly different climates, suggesting that climate may have played a role in divergence. Next, I assembled loci from publicly available sequencing data using a draft transcriptome of Desmognathus fuscus as a reference to assess the three nominal species in the quadramaculatus species complex across their entire range. I used phylogenetic and population structure analyses, alongside haplowebs and conspecificity matrices, to determine if the loci supported the hypothesis that the phenotypes represent multiple independently evolving lineages within the broader genetic clades found in the previous chapter. I found that the loci were not informative enough to determine whether the phenotypes had a genetic basis in Pisgah, but did support genetic divergence between phenotypes in Nantahala. Finally, I used ecological niche models (ENMs) and resistance modeling to place the genetic results and phenotypic diversity within the context of time and space. I found that though the quadramaculatus and marmoratus phenotypes were nearly indistinguishable in niche space in the present day, they were projected to occupy different geographic areas in the past and future. The southern portion of the study area had areas of high habitat suitability from the Last Glacial Maximum (~22 kya) to the present, which aligns with the higher genetic divergence between groups in Nantahala. Anthropogenic land use changes reduced habitat availability but likely did not drive genetic divergence in the past, and may be of more consequence to genetic diversity than climate change over the next 50 years. Like many taxa that underwent adaptive radiations, the evolutionary history of Desmognathus has been obfuscated by high rates of within-species phenotypic diversity and shared morphology between distantly related lineages. My findings emphasize the importance of interrogating complex patterns of genetic variation within the context of the dynamic, heterogeneous landscapes in which they arise

    Complex observation processes in ecology and epidemiology: general theory and specific examples

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    Complex observation processes abound in ecology and epidemiology. In order to answer the large-scale, urgent questions that are the focus of modern research, we must rely on indirect and opportunistic observation. Relating these data to the biological processes we are interested in is challenging. Statisticians working in this area need an understanding of both state-of-the-art modelling techniques and the field-specific nuances of how the data were generated. As a result, many methods to deal with complex observation processes are highly bespoke. Bespoke models are hard to translate between contexts and, because they are often presented in field-specific language, hard to learn from. Modelling of observation processes is thus a fractured area of study, leading to duplication of research effort and limiting the rate at which we can make progress. In this thesis, I aim to provide a road-map to how we might achieve some unification in this area. I begin by establishing a conceptual framework that can be used to describe observation processes and identify methods to address them. The framework defines all observation processes as a combination of issues of latency, identifiability, effort or scaling (L.I.E.S.). I illustrate the framework using motivating examples from ecology and epidemiology. The risk with conceptual frameworks is that they can be over-fitted to existing data and may fail when faced with new, real-world problems. To address this, I also approach the problem from a bottom-up perspective by tackling a series of ecological and epidemiological case studies. Each case study requires novel statistical methods to deal with the observation process. By developing new methods, I explore the world of observation processes potentially not well-captured in the literature. I then explore whether these case studies motivate revision or reassessment of my conceptual framework. While the case studies were chosen to challenge the L.I.E.S. framework, I find that they mutually reinforce each other. The framework provides a helpful scaffolding with which to describe the problems in the case studies. The case studies provide useful examples of more complex observation processes and how the four issues encoded in L.I.E.S. interact with one another. These findings illustrate the value of a framework for unifying approaches to observation processes

    Bayesian Methods for Animal Social Network Analysis

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    Over the last two decades, animal social network analysis has become central in the study of animal social systems. This methodology has given researchers a powerful set of tools to ask deep questions about the social structures of animals, and how these are linked to many other important biological processes. Animal social networks are often constructed from noisy, uncertain data, which would be well-suited to a Bayesian statistical philosophy. However, despite recent advances in Bayesian methodologies, they remain underutilised in animal social network analysis. In part this is due to unique features of animal network data that have led to the development and use of non-standard statistical procedures in the field. In this thesis I study some of the issues around existing methods, and highlight how a Bayesian methodology could substantially improve animal social network analyses. I introduce, implement, and explore a Bayesian framework for animal social network analysis. The framework makes it possible to conduct new types of analyses while accounting for both uncertainty and sampling biases. In addition to this, I have developed an R software package to allow researchers to use the new Bayesian framework to conduct animal social network analyses. The development of this framework raises new questions and opens up new opportunities in animal social network analysis, which I briefly explore towards the end of this thesis. I hope the developments made in this thesis will help to guide the future of animal social network analyses to make the most of hard-won network data, and to generate more reliable and insightful scientific inferences

    Extension de la méthode des Différences Spectrales à la combustion

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    L'amélioration des outils d'ingénierie utilisés dans le design des dispositifs industriels de combustion est indispensable afin de respecter les demandes de plus en plus restrictives pour réduire les émissions de gaz à effets de serre. Parmi eux, la mécanique des fluides numériques (CFD) est devenue essentielle pour étudier et optimiser les chambres de combustion au cours des dernières décennies. Elle se complète parfaitement aux expériences réelles qui peuvent être très couteuses et avec lesquelles il est impossible d'obtenir des informations sur n'importe quelle quantité d'intérêt en tout point de la chambre de combustion. En utilisant les simulations aux grandes échelles (LES), la CFD décrit directement l'interaction entre les flammes et les structures turbulentes avec une faible modélisation. La qualité des résultats LES est ainsi très dépendante de la discrétisation utilisée incluant à la fois le maillage et également les propriétés de dissipation et de dispersion des méthodes numériques utilisées. Cependant, la plupart des codes LES employés de nos jours dans l'industrie utilisent des schémas de discrétisation spatiale de basordre (LO) à cause de leur faible coût de calcul et leur facilité d'implémentation sur des maillages complexes. Pourtant, les méthodes numériques d'ordres élevés (HO) pour la LES sont développées depuis deux décennies et ont été appliquées sur des écoulements non-réactifs amenant à des résultats plus précis que les méthodes LO avec un plus faible coût de calcul. Bien que les méthodes HO semblent très prometteuses en combustion, en particulier pour mieux décrire le front de flamme, leur utilisation pour des écoulements réactifs restent encore à être démontrée. Au cours de ces travaux, les avantages et les bénéfices des méthodes HO en combustion sont évalués en utilisant la méthode des Différences Spectrales (SD) avec du raffinement hphp. Premièrement, il est démontré que la formulation originelle des SD est instable pour des écoulements multi-espèces avec des propriétés thermodynamiques variant avec la température et la composition. Il a été constaté que calculer les variables primitives aux points solutions puis de les extrapoler aux points flux, au lieu de faire l'inverse en extrapolant d'abord les variables conservatives, rend stable la méthode SD dans ce cas-ci. De plus, une nouvelle méthodologie, également plus stable pour calculer les flux diffusifs aux interfaces des cellules est détaillée. Enfin, les conditions aux limites caractéristiques et de murs ont été étendues aux écoulements multiespèces dans le formalisme SD. Avec ces développements, des flammes laminaires pré-mélangées 1D et 2D ont été simulées avec des mécanismes réduits à 2 réactions ou des mécanismes réduits analytiquement. Les résultats sont très proches de ceux obtenus avec des solveurs de référence bien établis en combustion. Il est montré que pour un même niveau d'erreur, il est plus efficace d'utiliser des maillages grossiers avec des grandes valeurs de pp et non l'inverse. Par conséquent, le raffinement local en pp, qui applique des grandes valeurs de pp dans les régions d'intérêts seulement, permet de garder une bonne précision à un coût de calcul plus faible. Ceci est particulièrement intéressant pour des simulations de combustion où le front de flamme est très localisé et requiert une plus grande précision que le reste de l'écoulement. Il est également observé sur ces cas simples 1D et 2D que la méthode SD est moins sensible à la discrétisation du front de flamme que les solveurs volumes finis comme AVBP. Pour terminer, deux différentes configurations de flammes 3D turbulentes ont été simulées avec l'algorithme des SD étendu aux écoulements réactifs
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