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Bubble generation and air entrainment on ocean surfaces and behind ships are complex phenomena which usually accompany turbulent flows. Non-linear wave-breaking events entrain air and generate turbulence. Turbulence consequently fragments the entrained air into smaller bubbles. This process drastically increases the flux of air into the oceans and rivers, which is important for both aerating the water bodies and reducing greenhouse gases from the atmosphere. Wave breaking and bubble generation behind ships also have important effects on the hydrodynamics of ships and on their performance. The bubbly flow as a result of ship passage generates ship trails which remain for several minutes thereafter. Although turbulence is responsible for the fragmentation of larger bubbles into smaller ones, it cannot be the cause of the generation of micron-size bubbles. These bubbles are observed in ship wakes and natural waves and are associated with liquid-liquid impact events. These phenomena, due to their complexity, are far from being completely understood. In addition, there is missing quantitative connection between the large-scale non-linear wave-breaking events and the micron-size bubble generation as a result of impact events. There is a large-scale separation between these two phenomena which makes elucidation of the problem very challenging. The aim of this study is to use direct numerical simulations of turbulent hydraulic jumps as canonical representation of non-linear breaking waves, to study the air entrainment and large bubble generation. Furthermore, this study provides statistics of liquid-liquid impact events, which are precursors to micro-bubble generation in these flows. As far as we know, the present work is the first direct numerical simulation of turbulent hydraulic jumps, as well as the first attempt to obtain interface impact statistics in a stationary turbulent breaking wave. In addition to bubble generation, we investigate turbulence statistics such as mean and turbulent velocity fluctuations, Reynolds stress tensors, turbulence production terms, energy spectra and one-dimensional energy budget of the flow. Finally, we present investigation of the effect of relevant non-dimensional parameters such as Weber number and Reynolds number on both large bubbles and impact statistics in these flows.
Bubble generation and air entrainment on ocean surfaces and behind ships are complex phenomena which usually accompany turbulent flows. Non-linear wave-breaking events entrain air and generate turbulence. Turbulence consequently fragments the entrained air into smaller bubbles. This process drastically increases the flux of air into the oceans and rivers, which is important for both aerating the water bodies and reducing greenhouse gases from the atmosphere. Wave breaking and bubble generation behind ships also have important effects on the hydrodynamics of ships and on their performance. The bubbly flow as a result of ship passage generates ship trails which remain for several minutes thereafter. Although turbulence is responsible for the fragmentation of larger bubbles into smaller ones, it cannot be the cause of the generation of micron-size bubbles. These bubbles are observed in ship wakes and natural waves and are associated with liquid-liquid impact events. These phenomena, due to their complexity, are far from being completely understood. In addition, there is missing quantitative connection between the large-scale non-linear wave-breaking events and the micron-size bubble generation as a result of impact events. There is a large-scale separation between these two phenomena which makes elucidation of the problem very challenging. The aim of this study is to use direct numerical simulations of turbulent hydraulic jumps as canonical representation of non-linear breaking waves, to study the air entrainment and large bubble generation. Furthermore, this study provides statistics of liquid-liquid impact events, which are precursors to micro-bubble generation in these flows. As far as we know, the present work is the first direct numerical simulation of turbulent hydraulic jumps, as well as the first attempt to obtain interface impact statistics in a stationary turbulent breaking wave. In addition to bubble generation, we investigate turbulence statistics such as mean and turbulent velocity fluctuations, Reynolds stress tensors, turbulence production terms, energy spectra and one-dimensional energy budget of the flow. Finally, we present investigation of the effect of relevant non-dimensional parameters such as Weber number and Reynolds number on both large bubbles and impact statistics in these flows.
Book
xv, 331 pages : illustrations ; 25 cm.
"In Classical Greek Syntax: Wackernagel's Law in Herodotus, David Goldstein offers the first theoretically-informed study of second-position clitics in Ancient Greek and challenges the long-standing belief that Greek word order is "free" or beyond the reach of systematic analysis. On the basis of Herodotus' Histories, he demonstrates that there are in fact systematic correspondences between clause structure and meaning. Crucial to this new model of the Greek clause is Wackernagel's Law, the generalization that enclitics and postpositives occur in "second position, " as these classes of words provide a stable anchor for analyzing sentence structure. The results of this work not only restore word order as an interpretive dimension of Greek texts, but also provide a framework for the investigation of other areas of syntax in Greek, as well as archaic Indo-European more broadly." -- Provided by publisher
"In Classical Greek Syntax: Wackernagel's Law in Herodotus, David Goldstein offers the first theoretically-informed study of second-position clitics in Ancient Greek and challenges the long-standing belief that Greek word order is "free" or beyond the reach of systematic analysis. On the basis of Herodotus' Histories, he demonstrates that there are in fact systematic correspondences between clause structure and meaning. Crucial to this new model of the Greek clause is Wackernagel's Law, the generalization that enclitics and postpositives occur in "second position, " as these classes of words provide a stable anchor for analyzing sentence structure. The results of this work not only restore word order as an interpretive dimension of Greek texts, but also provide a framework for the investigation of other areas of syntax in Greek, as well as archaic Indo-European more broadly." -- Provided by publisher
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PA367 .G65 2016 Unavailable In process Request
Book
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Automatic software verification is an important but hard problem. Verifiers primarily rely on static analysis to reason about all possible program behaviors, where a purely static analysis makes inferences based solely on program text. However, since verification is so hard, to be successful it seems necessary to leverage all possible sources that can provide any useful information about the program. Hence, limiting a verifier to just the program text is unnecessarily restrictive. Our thesis is that verification can be aided and significantly improved by learning from data gathered from program executions. In particular, we focus on the problem of invariant inference and its applications in verification. Invariant inference is a core problem that every software verifier must address. The traditional verifiers infer invariants by analyzing program text alone. The main contribution of this thesis is an effective technique to infer loop invariants by combining static analysis and machine learning applied to program executions.
Automatic software verification is an important but hard problem. Verifiers primarily rely on static analysis to reason about all possible program behaviors, where a purely static analysis makes inferences based solely on program text. However, since verification is so hard, to be successful it seems necessary to leverage all possible sources that can provide any useful information about the program. Hence, limiting a verifier to just the program text is unnecessarily restrictive. Our thesis is that verification can be aided and significantly improved by learning from data gathered from program executions. In particular, we focus on the problem of invariant inference and its applications in verification. Invariant inference is a core problem that every software verifier must address. The traditional verifiers infer invariants by analyzing program text alone. The main contribution of this thesis is an effective technique to infer loop invariants by combining static analysis and machine learning applied to program executions.
Book
1 online resource.
Type 2 diabetes mellitus (T2DM) has reached epidemic proportions, afflicting 8% of the world's adult population, and represents a huge public health problem. It is strongly associated with obesity and is often preceded by obesity-associated insulin resistance (IR). While multiple factors have been shown to contribute to IR, chronic inflammation in adipose tissue is widely viewed as one of the major contributors. Extensive studies have elucidated the key roles of the cells of the innate immune system in promoting adipose tissue inflammation. Recently cells of the adaptive immune system, B and T lymphocytes, have also emerged as important regulators of glucose homeostasis. B and T cells are particularly interesting to study, not only for the different functions of their respective subpopulations, but because they bear antigen-specific receptors and are capable of memory responses, raising the intriguing possibility of antigen-specific autoimmune processes in the pathology of this disease. I approached this topic from two angles (introduced in Chapter 1). Because of the lack of information on how different B cell subpopulations affect insulin resistance, I began by studying the follicular B-2 cells and the innate-like B-1a subset that is most prominent in the peritoneal cavity (in Chapter 2). I found that the B-2 cell subset was pathogenic while the B-1a cells were novel regulators that ameliorated insulin resistance via secretion of IL-10 and IgM. Depleting BAFF to selectively deplete B-2 cells while leaving the B-1a compartment intact helped to improve glucose tolerance, suggesting a novel avenue of therapy for the future. Next, using next generation sequencing techniques, I studied the changes of the B cell immune repertoire to high fat diet (HFD) exposure (in Chapter 3) and found systematic changes in the antibody repertoire, particularly for the IgA isotype and particularly in the intestines. HFD led to increased proportions of IgA-expressing B cells with short and hydrophobic complementarity-determining region-3 sequences, and increased proportions of sequences lacking somatic mutation. Highly stereotyped or "convergent" antibody gene rearrangements expressed by the B cells in the visceral adipose tissue (VAT) and, to a lesser degree, intestinal tissues, could also be detected across numerous individual mice. These convergent antibody gene rearrangements in the adipose tissues of HFD mice were notable for having higher mutation levels, indicating that they have undergone somatic mutation. Taken together, these results demonstrate that HFD can cause significant changes in the systematic immunoglobulin repertoire in mice. To determine whether the repertoire changes seen above and in other studies might be due to an autoimmune response to obesity-related antigens, I tried a series of proof-of-principle experiments in animals with transgenic receptors against model antigens (in Chapter 4). While I could confirm enrichment of CD8 memory T cells in the VAT, experiments with obese mice bearing different MHCs, skewed B cell receptor and T cell receptor specificities showed no significant changes in glucose intolerance compared to wild type. I also immunized mice against a putative antigen in IR, glial fibrillary acidic protein (GFAP), and found no significant changes in glucose intolerance. While these results do not support the hypothesis that IR is caused or worsened by autoimmunity, the limited nature of studying a few model antigens means that autoantigens specific to the obese state, if they existed, could easily be missed by my experiments. The results also do not preclude the involvement of exogenous antigens, like bacterial antigens, and this will be the subject of future investigation.
Type 2 diabetes mellitus (T2DM) has reached epidemic proportions, afflicting 8% of the world's adult population, and represents a huge public health problem. It is strongly associated with obesity and is often preceded by obesity-associated insulin resistance (IR). While multiple factors have been shown to contribute to IR, chronic inflammation in adipose tissue is widely viewed as one of the major contributors. Extensive studies have elucidated the key roles of the cells of the innate immune system in promoting adipose tissue inflammation. Recently cells of the adaptive immune system, B and T lymphocytes, have also emerged as important regulators of glucose homeostasis. B and T cells are particularly interesting to study, not only for the different functions of their respective subpopulations, but because they bear antigen-specific receptors and are capable of memory responses, raising the intriguing possibility of antigen-specific autoimmune processes in the pathology of this disease. I approached this topic from two angles (introduced in Chapter 1). Because of the lack of information on how different B cell subpopulations affect insulin resistance, I began by studying the follicular B-2 cells and the innate-like B-1a subset that is most prominent in the peritoneal cavity (in Chapter 2). I found that the B-2 cell subset was pathogenic while the B-1a cells were novel regulators that ameliorated insulin resistance via secretion of IL-10 and IgM. Depleting BAFF to selectively deplete B-2 cells while leaving the B-1a compartment intact helped to improve glucose tolerance, suggesting a novel avenue of therapy for the future. Next, using next generation sequencing techniques, I studied the changes of the B cell immune repertoire to high fat diet (HFD) exposure (in Chapter 3) and found systematic changes in the antibody repertoire, particularly for the IgA isotype and particularly in the intestines. HFD led to increased proportions of IgA-expressing B cells with short and hydrophobic complementarity-determining region-3 sequences, and increased proportions of sequences lacking somatic mutation. Highly stereotyped or "convergent" antibody gene rearrangements expressed by the B cells in the visceral adipose tissue (VAT) and, to a lesser degree, intestinal tissues, could also be detected across numerous individual mice. These convergent antibody gene rearrangements in the adipose tissues of HFD mice were notable for having higher mutation levels, indicating that they have undergone somatic mutation. Taken together, these results demonstrate that HFD can cause significant changes in the systematic immunoglobulin repertoire in mice. To determine whether the repertoire changes seen above and in other studies might be due to an autoimmune response to obesity-related antigens, I tried a series of proof-of-principle experiments in animals with transgenic receptors against model antigens (in Chapter 4). While I could confirm enrichment of CD8 memory T cells in the VAT, experiments with obese mice bearing different MHCs, skewed B cell receptor and T cell receptor specificities showed no significant changes in glucose intolerance compared to wild type. I also immunized mice against a putative antigen in IR, glial fibrillary acidic protein (GFAP), and found no significant changes in glucose intolerance. While these results do not support the hypothesis that IR is caused or worsened by autoimmunity, the limited nature of studying a few model antigens means that autoantigens specific to the obese state, if they existed, could easily be missed by my experiments. The results also do not preclude the involvement of exogenous antigens, like bacterial antigens, and this will be the subject of future investigation.
Book
1 online resource.
The work in this doctoral dissertation is divided into two parts. First, the synthesis and characterization of oxidized metal-salen complexes as models for galactose oxidase, a metalloenzyme that relies on ligand redox "non-innocence" for its activity, is explored. It is shown that simple changes to the salen ligand structure can dramatically affect the locus of oxidation with a variety of metal centers. A series of one- and two-electron oxidized copper(II)-salen complexes are characterized using a variety of spectroscopic, electrochemical, and theoretical methods. The second part of this dissertation explores the use of amine-functionalized mesoporous materials for carbon dioxide capture. We have investigated the thermodynamics and kinetics of carbon dioxide adsorption/desorption reactions for a series of diamine-functionalized SBA-15 materials. Enthalpic and entropic contributions to the free energy of carbon dioxide adsorption/desorption are correlated to the structure and surface distribution of sorbent molecules. Additionally, a novel and highly reproducible method for the bromomethylation of mesoporous carbon materials is reported. Bromomethylated materials can be derivatized further by a variety of methods to yield novel functional materials. Specifically, carbon materials functionalized further with diamines are capable of carbon dioxide capture by a process similar to that observed for diamine-functionalized SBA-15 materials.
The work in this doctoral dissertation is divided into two parts. First, the synthesis and characterization of oxidized metal-salen complexes as models for galactose oxidase, a metalloenzyme that relies on ligand redox "non-innocence" for its activity, is explored. It is shown that simple changes to the salen ligand structure can dramatically affect the locus of oxidation with a variety of metal centers. A series of one- and two-electron oxidized copper(II)-salen complexes are characterized using a variety of spectroscopic, electrochemical, and theoretical methods. The second part of this dissertation explores the use of amine-functionalized mesoporous materials for carbon dioxide capture. We have investigated the thermodynamics and kinetics of carbon dioxide adsorption/desorption reactions for a series of diamine-functionalized SBA-15 materials. Enthalpic and entropic contributions to the free energy of carbon dioxide adsorption/desorption are correlated to the structure and surface distribution of sorbent molecules. Additionally, a novel and highly reproducible method for the bromomethylation of mesoporous carbon materials is reported. Bromomethylated materials can be derivatized further by a variety of methods to yield novel functional materials. Specifically, carbon materials functionalized further with diamines are capable of carbon dioxide capture by a process similar to that observed for diamine-functionalized SBA-15 materials.
Book
1 online resource.
The continued demand for efficient chemo-, regio-, and stereoselective organic transformations motivates the development of new chemical reactions. Transition metal catalysis represents a powerful method for the construction of carbon-carbon, carbon-hydrogen, and carbon-heteroatom bonds in a highly selective fashion. This dissertation describes the development of several new transition metal-catalyzed organic reactions useful in the preparation of various chiral small molecules, including both fundamental organic "building block" compounds and structurally complex natural products and pharmaceutical agents. We report a new strategy for the synthesis of chiral beta-alkynyl esters, ketones, and sulfones via sequential palladium-catalyzed carbon-carbon bond formation and copper-catalyzed carbon-hydrogen bond formation. The process is operationally straightforward, compatible with a broad range of substrates, and delivers the targets in high yields with excellent levels of enantioselectivity. It is compatible with both oxygen and nitrogen functionality, and this enabled the rapid elaboration of the products into a diverse set of chiral heterocycles. The sequential catalysis protocol was employed in a concise, enantioselective synthesis of AMG 837, a potent agonist of G-protein coupled receptor 40. Recognizing both the biological relevance of chiral alkaloids and the synthetic challenges associated with the construction of quaternary, all-carbon stereocenters, we pursued a palladium-catalyzed asymmetric allylic alkylation that effected carbon-carbon bond formation on prochiral oxindole nucleophiles. Although prior research has demonstrated that allylic alkylation reactions of geminal dicarboxylate electrophiles typically yield branched products as the result of ipso-addition, we identify conditions wherein oxindoles react with a dipivaloyl electrophile to afford linear enol pivalate compounds. A mild hydrolysis reaction converts these products into the aldehyde that formally results from asymmetric conjugate addition to acrolein, a challenging transformation with limited literature precedent. These adducts are established precursors to tricyclic alkaloid scaffolds of pharmaceutical interest. Chiral gamma-heteroatom-substituted cycloalkenones are well-established organic "building blocks" that are widely used in the synthesis of complex molecules. The exposure of meso-1,4-allylic dibenzoates to chiral phosphine-ligated palladium salts in the presence of a potassium nitronate nucleophile promotes a unique oxidative desymmetrization reaction. This process yields enantiopure gamma-benzoyloxy cyclopentenones, cyclohexenones, and cycloheptenones. We describe the elaboration of these products into diverse, enantioenriched oxygen- and nitrogen-substituted cycloalkenones via subsequent palladium-catalyzed allylic alkylation reactions involving heteroatom nucleophiles. Separately, we employ enantiopure gamma-benzoyloxy cyclohexenones in short, asymmetric syntheses of enantio- and diastereomerically diverse epoxyquinoid natural products. We further highlight the utility of palladium catalysis in complex molecule synthesis through the development of a unique, intramolecular carbon-carbon bond-forming reaction that generates a strained enyne and through an asymmetric formal synthesis of aliskiren, a renin inhibitor used in the treatment of hypertension.
The continued demand for efficient chemo-, regio-, and stereoselective organic transformations motivates the development of new chemical reactions. Transition metal catalysis represents a powerful method for the construction of carbon-carbon, carbon-hydrogen, and carbon-heteroatom bonds in a highly selective fashion. This dissertation describes the development of several new transition metal-catalyzed organic reactions useful in the preparation of various chiral small molecules, including both fundamental organic "building block" compounds and structurally complex natural products and pharmaceutical agents. We report a new strategy for the synthesis of chiral beta-alkynyl esters, ketones, and sulfones via sequential palladium-catalyzed carbon-carbon bond formation and copper-catalyzed carbon-hydrogen bond formation. The process is operationally straightforward, compatible with a broad range of substrates, and delivers the targets in high yields with excellent levels of enantioselectivity. It is compatible with both oxygen and nitrogen functionality, and this enabled the rapid elaboration of the products into a diverse set of chiral heterocycles. The sequential catalysis protocol was employed in a concise, enantioselective synthesis of AMG 837, a potent agonist of G-protein coupled receptor 40. Recognizing both the biological relevance of chiral alkaloids and the synthetic challenges associated with the construction of quaternary, all-carbon stereocenters, we pursued a palladium-catalyzed asymmetric allylic alkylation that effected carbon-carbon bond formation on prochiral oxindole nucleophiles. Although prior research has demonstrated that allylic alkylation reactions of geminal dicarboxylate electrophiles typically yield branched products as the result of ipso-addition, we identify conditions wherein oxindoles react with a dipivaloyl electrophile to afford linear enol pivalate compounds. A mild hydrolysis reaction converts these products into the aldehyde that formally results from asymmetric conjugate addition to acrolein, a challenging transformation with limited literature precedent. These adducts are established precursors to tricyclic alkaloid scaffolds of pharmaceutical interest. Chiral gamma-heteroatom-substituted cycloalkenones are well-established organic "building blocks" that are widely used in the synthesis of complex molecules. The exposure of meso-1,4-allylic dibenzoates to chiral phosphine-ligated palladium salts in the presence of a potassium nitronate nucleophile promotes a unique oxidative desymmetrization reaction. This process yields enantiopure gamma-benzoyloxy cyclopentenones, cyclohexenones, and cycloheptenones. We describe the elaboration of these products into diverse, enantioenriched oxygen- and nitrogen-substituted cycloalkenones via subsequent palladium-catalyzed allylic alkylation reactions involving heteroatom nucleophiles. Separately, we employ enantiopure gamma-benzoyloxy cyclohexenones in short, asymmetric syntheses of enantio- and diastereomerically diverse epoxyquinoid natural products. We further highlight the utility of palladium catalysis in complex molecule synthesis through the development of a unique, intramolecular carbon-carbon bond-forming reaction that generates a strained enyne and through an asymmetric formal synthesis of aliskiren, a renin inhibitor used in the treatment of hypertension.
Book
1 online resource.
Multivalent and multifunctional proteins are abundant in nature. The avidity effect, a core principle of multivalent molecules, allows these proteins to tune biological functions and responses across a large dynamic range with varying specificity. Many protein therapeutics also take advantage of this evolvable tunability, the canonical example being the antibody. This thesis consists of two separate sections. Section One: I focus on the avidity effect of multivalent proteins and its therapeutic uses. As an illustrative case, our lab had previously created a protein variant that monomerically binds the c-MET tyrosine kinase. By dimerizing this variant, we find that we greatly increase its efficacy through increased apparent affinity to cell surface c-MET. Section Two: I focus on multispecific proteins and their uses in medical applications. Most current therapeutic protein scaffolds are single protein domains with monomeric binding and function. Combining these scaffolds to create multispecific functionality presents manufacturing challenges. Here the vascular endothelial growth factor (VEGF) protein is used as a stable, naturally bivalent scaffold for engineering bispecific proteins.
Multivalent and multifunctional proteins are abundant in nature. The avidity effect, a core principle of multivalent molecules, allows these proteins to tune biological functions and responses across a large dynamic range with varying specificity. Many protein therapeutics also take advantage of this evolvable tunability, the canonical example being the antibody. This thesis consists of two separate sections. Section One: I focus on the avidity effect of multivalent proteins and its therapeutic uses. As an illustrative case, our lab had previously created a protein variant that monomerically binds the c-MET tyrosine kinase. By dimerizing this variant, we find that we greatly increase its efficacy through increased apparent affinity to cell surface c-MET. Section Two: I focus on multispecific proteins and their uses in medical applications. Most current therapeutic protein scaffolds are single protein domains with monomeric binding and function. Combining these scaffolds to create multispecific functionality presents manufacturing challenges. Here the vascular endothelial growth factor (VEGF) protein is used as a stable, naturally bivalent scaffold for engineering bispecific proteins.
Book
xv, 192 pages : illustrations, plans ; 21 cm.
SAL3 (off-campus storage)
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NA1526 .L85 2016 Available
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1 online resource.
Many industries consist of networks of interdependent firms that offer discrete products or services that together comprise a valuable solution. Within these networks, often termed ecosystems, firms depend on one another to create value, but simultaneously compete with one another to capture value. Prior research on ecosystems has generally examined firm strategy in established ecosystems, in which the identity and relationships between firms and components are known. Less is known about firm strategy in early-stage ecosystems, which are those that are in an early state of emergence or evolution. This dissertation addresses this gap through three linked studies. The first is an inductive multiple-case study of five firms in the nascent US residential solar ecosystem as it emerged from 2007 to 2014. The second is a formal mathematical model that examines how the level of competition (ecosystem vs. component) affects firms' ability to create and capture value in nascent ecosystems. The third moves from nascent to evolving ecosystems, and presents a cooperative game theory model that examines how and when firms can collaboratively resolve technological constraints that inhibit their ability to jointly create and capture value. Together, the studies in this dissertation offer rich theory regarding how firms can succeed in early-stage ecosystems, despite the uncertainty and ambiguity that characterizes these settings. Overall, this research contributes to the literatures on strategy, organizations theory, and entrepreneurship.
Many industries consist of networks of interdependent firms that offer discrete products or services that together comprise a valuable solution. Within these networks, often termed ecosystems, firms depend on one another to create value, but simultaneously compete with one another to capture value. Prior research on ecosystems has generally examined firm strategy in established ecosystems, in which the identity and relationships between firms and components are known. Less is known about firm strategy in early-stage ecosystems, which are those that are in an early state of emergence or evolution. This dissertation addresses this gap through three linked studies. The first is an inductive multiple-case study of five firms in the nascent US residential solar ecosystem as it emerged from 2007 to 2014. The second is a formal mathematical model that examines how the level of competition (ecosystem vs. component) affects firms' ability to create and capture value in nascent ecosystems. The third moves from nascent to evolving ecosystems, and presents a cooperative game theory model that examines how and when firms can collaboratively resolve technological constraints that inhibit their ability to jointly create and capture value. Together, the studies in this dissertation offer rich theory regarding how firms can succeed in early-stage ecosystems, despite the uncertainty and ambiguity that characterizes these settings. Overall, this research contributes to the literatures on strategy, organizations theory, and entrepreneurship.
Book
xv, 231 pages : illustrations ; 23 cm.
  • List of illustrations Preface Acknowledgements 1. Introduction 2. Muslim Youth Culture, Globalization, and Piety 3. Rethinking Muslim Youth Identities 4. Nasyid, Jihad And Hip-Hop 5. Tattooing The Muslim Youth Body 6. Youth Resistance Through Cultural Consumption 7. Conclusion References Index.
  • (source: Nielsen Book Data)
Globalized Muslim Youth in the Asia Pacific is a sociological study of Muslim youth culture based on original ethnographic fieldwork in two global cities in the Asia Pacific: Singapore and Sydney. Urban young Muslims in Singapore and Sydney face similar everyday challenges, such as their minority status and low socio-economic position relative to the larger society. These are complicated by the broader processes of globalization that bring together the September 11 generation living in the Information Age. Comparing young Muslims living in these secular, multicultural cities across three domains of popular culture - hip-hop music, tattooing, and cultural consumption - this study illuminates the range of attitudes and strategies they adopt to reconcile popular youth culture with piety.
(source: Nielsen Book Data)
  • List of illustrations Preface Acknowledgements 1. Introduction 2. Muslim Youth Culture, Globalization, and Piety 3. Rethinking Muslim Youth Identities 4. Nasyid, Jihad And Hip-Hop 5. Tattooing The Muslim Youth Body 6. Youth Resistance Through Cultural Consumption 7. Conclusion References Index.
  • (source: Nielsen Book Data)
Globalized Muslim Youth in the Asia Pacific is a sociological study of Muslim youth culture based on original ethnographic fieldwork in two global cities in the Asia Pacific: Singapore and Sydney. Urban young Muslims in Singapore and Sydney face similar everyday challenges, such as their minority status and low socio-economic position relative to the larger society. These are complicated by the broader processes of globalization that bring together the September 11 generation living in the Information Age. Comparing young Muslims living in these secular, multicultural cities across three domains of popular culture - hip-hop music, tattooing, and cultural consumption - this study illuminates the range of attitudes and strategies they adopt to reconcile popular youth culture with piety.
(source: Nielsen Book Data)
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BP188.18 .Y68 K36 2016 Unknown
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xi, 281 pages ; 24 cm.
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198 pages ; 24 cm.
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256 pages, 16 unnumbered pages of plates : 25 color photos ; 25 cm.
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Natural killer (NK) cells are a unique lymphocyte lineage with remarkable agility in the rapid destruction of virus-infected cells. They are also the most poorly understood class of lymphocyte. A spectrum of activating and inhibitory receptors at the NK cell surface leads to an unusual and difficult-to-study mechanism of cellular recognition, as well as a very high capacity for diversity at the single-cell level. Here, we provide the first examination of human natural killer cell repertoire diversity. Using mass cytometry, we identify an unanticipated level of single-cell diversity within and among human subjects. In a study of monozygotic twins, we show that inhibitory receptor expression is determined primarily by genetics, while activating receptor expression is environmentally influenced. This study shows that the human NK cell repertoire is extremely diverse, with both genetic and environmental influences. We further show that this diversity is not limited to NK cells. NK receptors actually become less specific for NK cells as the immune repertoire matures. These receptors are also expressed on T cells, B cells, and monocytes, with cell type-specific changes observed upon maturation. NK cells acquire primarily inhibitory receptors when they mature, while CD8+ T cells acquire both activating and inhibitory receptors. These results show that the expression of NK receptors on multiple cell types is coordinately regulated. In a final study, we show that NK diversity is low at birth, increases by adulthood, and is stable over at least 6 months in healthy adults. It also increases in culture in response to interaction with virally infected cells. Furthermore, in a cohort of Kenyan women, a higher pre-infection level of NK diversity is predictive of a higher likelihood of HIV-1 acquisition. This data shows that NK cell diversity has functional significance and appears to be detrimental in the setting of viral acquisition. We conclude by reviewing outstanding questions in the nascent field of NK cell repertoire diversity. Finally, we look to the future, where emerging single-cell technologies will enable a new generation of rigorous and clinically relevant studies of NK cells accounting for all of their unique and diverse characteristics.
Natural killer (NK) cells are a unique lymphocyte lineage with remarkable agility in the rapid destruction of virus-infected cells. They are also the most poorly understood class of lymphocyte. A spectrum of activating and inhibitory receptors at the NK cell surface leads to an unusual and difficult-to-study mechanism of cellular recognition, as well as a very high capacity for diversity at the single-cell level. Here, we provide the first examination of human natural killer cell repertoire diversity. Using mass cytometry, we identify an unanticipated level of single-cell diversity within and among human subjects. In a study of monozygotic twins, we show that inhibitory receptor expression is determined primarily by genetics, while activating receptor expression is environmentally influenced. This study shows that the human NK cell repertoire is extremely diverse, with both genetic and environmental influences. We further show that this diversity is not limited to NK cells. NK receptors actually become less specific for NK cells as the immune repertoire matures. These receptors are also expressed on T cells, B cells, and monocytes, with cell type-specific changes observed upon maturation. NK cells acquire primarily inhibitory receptors when they mature, while CD8+ T cells acquire both activating and inhibitory receptors. These results show that the expression of NK receptors on multiple cell types is coordinately regulated. In a final study, we show that NK diversity is low at birth, increases by adulthood, and is stable over at least 6 months in healthy adults. It also increases in culture in response to interaction with virally infected cells. Furthermore, in a cohort of Kenyan women, a higher pre-infection level of NK diversity is predictive of a higher likelihood of HIV-1 acquisition. This data shows that NK cell diversity has functional significance and appears to be detrimental in the setting of viral acquisition. We conclude by reviewing outstanding questions in the nascent field of NK cell repertoire diversity. Finally, we look to the future, where emerging single-cell technologies will enable a new generation of rigorous and clinically relevant studies of NK cells accounting for all of their unique and diverse characteristics.
Book
1 online resource.
Aging is a fundamental biological process seen in nearly all organisms. While research has discovered hundreds of genes whose dosage can modify lifespan, it is unclear how many of these genes play a role in the normal transition from the young state to the old state. To better understand aging, it is critical to identify which processes are driving aging in wildtype organisms. Our approach is to search for direct regulators of molecular changes that appear over time in the nematode worm Caenorhabditis elegans. This is a quantitative, global, and relatively unbiased way to find potential drivers of aging. We begin with a set of over 1,000 gene expression changes between young and old worms. In this work, we used a computational screen to identify transcription factors that directly bind to our list of age-regulated genes. The top hit from our screen is a conserved GATA transcription factor called ELT-2 that functions during development to effect the terminal differentiation of the intestine. The expression of ELT-2 and its direct transcriptional targets decline during aging. Lifespan can be either extended or shortened by increasing or decreasing the dosage of ELT-2. Together, these findings provide strong evidence to support the idea that changes in the expression of ELT-2 drive transcriptional changes during aging and limit lifespan.
Aging is a fundamental biological process seen in nearly all organisms. While research has discovered hundreds of genes whose dosage can modify lifespan, it is unclear how many of these genes play a role in the normal transition from the young state to the old state. To better understand aging, it is critical to identify which processes are driving aging in wildtype organisms. Our approach is to search for direct regulators of molecular changes that appear over time in the nematode worm Caenorhabditis elegans. This is a quantitative, global, and relatively unbiased way to find potential drivers of aging. We begin with a set of over 1,000 gene expression changes between young and old worms. In this work, we used a computational screen to identify transcription factors that directly bind to our list of age-regulated genes. The top hit from our screen is a conserved GATA transcription factor called ELT-2 that functions during development to effect the terminal differentiation of the intestine. The expression of ELT-2 and its direct transcriptional targets decline during aging. Lifespan can be either extended or shortened by increasing or decreasing the dosage of ELT-2. Together, these findings provide strong evidence to support the idea that changes in the expression of ELT-2 drive transcriptional changes during aging and limit lifespan.
Book
xiv, 482 pages ; 25 cm.
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vi, 363 pages ; 25 cm.
SAL1&2 (on-campus shelving)
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SAL1&2 (on-campus shelving) Status
Stacks Request
UH705 .G7 G68 2016 Unavailable In process
Book
1 online resource.
Kidney transplant is a life-saving therapy for end stage renal disease, and directed living donation is one of the main sources of graft. However, it is often unavailable because the willing living donor is blood type or tissue type incompatible with the patient. Kidney Paired Donation (KPD) facilitates the exchanges among incompatible living donor-patient pairs to create opportunities for transplants. In this research, I focus on the waiting time in the KPD system. The large number of highly sensitized (hard-to-match) patients accumulated in the KPD system have considerably longer waiting time than the others, and have led to a sparsely connected compatibility graph. I show that this can negatively impact the chances for the otherwise easy-to-match patients. To address this issue, I constructed a model for the KPD system based on historical data, and examined the policy of assigning priorities using the structural knowledge of the compatibility graph. I demonstrated through simulation that when the hard-to-match pairs receive priorities their waiting time can be significantly reduced. Moreover, the prioritization of the hard-to-match pairs does not necessarily disadvantage the rest of the population. In fact, the overall waiting time can be reduced. Furthermore, using a model with uncertain match offer rejections, I quantified the imperfect information's impact on the system waiting time, and showed a need for improvement on the current implementation of KPD. Finally, I studied the prohibition clause in National Organ Transplant Act (42 U.S.C.§274e) that led to today's commonly practiced ban on human organ selling/purchasing. In doing so I pointed out that the original prohibition leaves room for interpretation, specifically regarding the validity of a contract regulating organ transplant: contrary to some's belief, it is possible that such a contract is valid and enforceable under NOTA.
Kidney transplant is a life-saving therapy for end stage renal disease, and directed living donation is one of the main sources of graft. However, it is often unavailable because the willing living donor is blood type or tissue type incompatible with the patient. Kidney Paired Donation (KPD) facilitates the exchanges among incompatible living donor-patient pairs to create opportunities for transplants. In this research, I focus on the waiting time in the KPD system. The large number of highly sensitized (hard-to-match) patients accumulated in the KPD system have considerably longer waiting time than the others, and have led to a sparsely connected compatibility graph. I show that this can negatively impact the chances for the otherwise easy-to-match patients. To address this issue, I constructed a model for the KPD system based on historical data, and examined the policy of assigning priorities using the structural knowledge of the compatibility graph. I demonstrated through simulation that when the hard-to-match pairs receive priorities their waiting time can be significantly reduced. Moreover, the prioritization of the hard-to-match pairs does not necessarily disadvantage the rest of the population. In fact, the overall waiting time can be reduced. Furthermore, using a model with uncertain match offer rejections, I quantified the imperfect information's impact on the system waiting time, and showed a need for improvement on the current implementation of KPD. Finally, I studied the prohibition clause in National Organ Transplant Act (42 U.S.C.§274e) that led to today's commonly practiced ban on human organ selling/purchasing. In doing so I pointed out that the original prohibition leaves room for interpretation, specifically regarding the validity of a contract regulating organ transplant: contrary to some's belief, it is possible that such a contract is valid and enforceable under NOTA.
Book
1 online resource.
The goal of the research presented in this dissertation is to present a data driven policy making approach in three different settings. In the first setting, we look at using data to inform policies to supply supplementary food aid for undernourished children in Guatemala. We fit a trivariate model of weight-for-age z score (WAZ), height-for-age z score (HAZ) and diarrhea status to data from an observational study of supplemen- tary feeding in 17 Guatemalan communities. We estimate how the effect of supplementary food on WAZ, HAZ and diarrhea status varies with a child's age. We find that the effect of supplementary food on all 3 metrics decreases linearly with age from 6 to 20 mo and has little effect after 20 mo. We derive 2 food allocation policies that myopically (i.e., looking ahead 2 mo) minimize either the underweight or stunting severity -- i.e., the sum of squared WAZ or HAZ scores for all children with WAZ or HAZ < 0. A simulation study based on the statistical model predicts that in a low-dose (100 kCal/day) supplementary feeding setting in Guatemala, allocating food primarily to 6-12 mo infants can reduce the severity of underweight and stunting. In the second setting, we look at analyzing how targeting interventions to the most under- nourished would perform in reducing the malaria burden amongst children in sub-Saharan Africa. We construct a malaria model with superinfection and heterogeneous susceptibility, where a portion of this susceptibility is due to undernutrition (as measured by weight-for-age z scores); so as to isolate the impact of supplementary food on malaria from the influence of confounding factors, we estimate the portion of the total susceptibility that is due to undernutrition from a large randomized trial of supplementary feeding. A simulation study based on the malaria model suggests that targeting insecticide-treated bed nets to undernutritioned children leads to fewer malaria deaths than the random distribution of bed nets in the hypoendemic and mesoendemic settings. In the third setting, we look to quantify Tuberculosis (TB) transmission risk within and outside cells using high-resolution social contact data of prisoner in a large prison in the state of Mato Grosso do Sul, Brazil. We then develop and parameterize a model of TB natural history and transmission to evaluate the impact of TB control interventions in prisons on TB incidence amongst the prisoners. A simulation study using this model suggests that any single intervention (improved case detection, decrowding or active case detection) would be insufficient to bring the TB incidence back to the TB incidence levels of the early 2000s but a combination of interventions would be necessary. The results of these studies demonstrate that mathematical modeling can be a powerful tool in understanding the interplaying factors behind the policy in question and help policy makers make informed decisions.
The goal of the research presented in this dissertation is to present a data driven policy making approach in three different settings. In the first setting, we look at using data to inform policies to supply supplementary food aid for undernourished children in Guatemala. We fit a trivariate model of weight-for-age z score (WAZ), height-for-age z score (HAZ) and diarrhea status to data from an observational study of supplemen- tary feeding in 17 Guatemalan communities. We estimate how the effect of supplementary food on WAZ, HAZ and diarrhea status varies with a child's age. We find that the effect of supplementary food on all 3 metrics decreases linearly with age from 6 to 20 mo and has little effect after 20 mo. We derive 2 food allocation policies that myopically (i.e., looking ahead 2 mo) minimize either the underweight or stunting severity -- i.e., the sum of squared WAZ or HAZ scores for all children with WAZ or HAZ < 0. A simulation study based on the statistical model predicts that in a low-dose (100 kCal/day) supplementary feeding setting in Guatemala, allocating food primarily to 6-12 mo infants can reduce the severity of underweight and stunting. In the second setting, we look at analyzing how targeting interventions to the most under- nourished would perform in reducing the malaria burden amongst children in sub-Saharan Africa. We construct a malaria model with superinfection and heterogeneous susceptibility, where a portion of this susceptibility is due to undernutrition (as measured by weight-for-age z scores); so as to isolate the impact of supplementary food on malaria from the influence of confounding factors, we estimate the portion of the total susceptibility that is due to undernutrition from a large randomized trial of supplementary feeding. A simulation study based on the malaria model suggests that targeting insecticide-treated bed nets to undernutritioned children leads to fewer malaria deaths than the random distribution of bed nets in the hypoendemic and mesoendemic settings. In the third setting, we look to quantify Tuberculosis (TB) transmission risk within and outside cells using high-resolution social contact data of prisoner in a large prison in the state of Mato Grosso do Sul, Brazil. We then develop and parameterize a model of TB natural history and transmission to evaluate the impact of TB control interventions in prisons on TB incidence amongst the prisoners. A simulation study using this model suggests that any single intervention (improved case detection, decrowding or active case detection) would be insufficient to bring the TB incidence back to the TB incidence levels of the early 2000s but a combination of interventions would be necessary. The results of these studies demonstrate that mathematical modeling can be a powerful tool in understanding the interplaying factors behind the policy in question and help policy makers make informed decisions.
Book
1 online resource.
For high performance medical diagnostics, magnetic biosensors have emerged as a suitable platform for fast and accurate protein measurements due to their very low background signal compared to optical methods. Medical applications demand biomarker panels including a larger number of protein analytes, and biosensors with larger and larger numbers of individual sensors enable measuring multiple target analytes in parallel on the same chip. Of these biosensors, Giant Magnetoresistance (GMR) sensors have been identified as one of the most promising technologies for protein detection. As with any solid state biosensor technology, on GMR sensors the effective use of each sensor is limited by its dynamic range and cross-reactivity between analytes used. Each added analyte added onto the sensor needs to be matched in terms of dynamic range of the sensor and using only reagents that do not cross react with other assay reagents. These two constraints limit the target analyte multiplexing capability of the sensor array technology. In order to use large-scale GMR sensor arrays effectively, these constraints need to be overcome. This thesis presents a microfluidic integration approach to GMR sensors which interfaces groups of sensors using individual microfluidic channels as separate compartments and thereby limits the scope of these constraints to only the compartment level and not to the whole array. In addition to overcoming dynamic range and cross-reactivity limitations in protein assays, this compartmentalization approach increases the number of samples that can be measured in parallel on a single chip from 1 up to 8 and enables more precise protein quantification. The use of microfluidics further increases the snr of larger particles with increased magnetic moments. These particles lead to an order of magnitude improvement in detection limit. Furthermore this microfluidic approach enables the integration of sample and reagent reservoirs, actuation elements and automation within the microfluidic chip. Microfluidic compartmentalization is useful for enabling an effective and flexible use of a wide range of surface-based sensor arrays. It enables the deployment of large-scale sensor arrays, which are not limited by cross-reactivity and dynamic range.
For high performance medical diagnostics, magnetic biosensors have emerged as a suitable platform for fast and accurate protein measurements due to their very low background signal compared to optical methods. Medical applications demand biomarker panels including a larger number of protein analytes, and biosensors with larger and larger numbers of individual sensors enable measuring multiple target analytes in parallel on the same chip. Of these biosensors, Giant Magnetoresistance (GMR) sensors have been identified as one of the most promising technologies for protein detection. As with any solid state biosensor technology, on GMR sensors the effective use of each sensor is limited by its dynamic range and cross-reactivity between analytes used. Each added analyte added onto the sensor needs to be matched in terms of dynamic range of the sensor and using only reagents that do not cross react with other assay reagents. These two constraints limit the target analyte multiplexing capability of the sensor array technology. In order to use large-scale GMR sensor arrays effectively, these constraints need to be overcome. This thesis presents a microfluidic integration approach to GMR sensors which interfaces groups of sensors using individual microfluidic channels as separate compartments and thereby limits the scope of these constraints to only the compartment level and not to the whole array. In addition to overcoming dynamic range and cross-reactivity limitations in protein assays, this compartmentalization approach increases the number of samples that can be measured in parallel on a single chip from 1 up to 8 and enables more precise protein quantification. The use of microfluidics further increases the snr of larger particles with increased magnetic moments. These particles lead to an order of magnitude improvement in detection limit. Furthermore this microfluidic approach enables the integration of sample and reagent reservoirs, actuation elements and automation within the microfluidic chip. Microfluidic compartmentalization is useful for enabling an effective and flexible use of a wide range of surface-based sensor arrays. It enables the deployment of large-scale sensor arrays, which are not limited by cross-reactivity and dynamic range.