864 research outputs found
Regimen durability in HIV-positive children andd adolescents initiating first-line art in a large public sector HIV cohort in South Africa
INTRODUCTION: In April 2010 tenofovir and abacavir replaced stavudine in public-sector first-line antiretroviral therapy (ART) for children under 20 years old in South Africa. The association of both abacavir and tenofovir with fewer side-effects and toxicities compared to stavudine could translate to increased durability of tenofovir or abacavir-based regimens. We evaluated changes over time in regimen durability for pediatric patients 3 to 19 years of age at 8 public sector clinics in Johannesburg, South Africa.
METHODS: Cohort analysis of treatment naïve, non-pregnant pediatric patients from 3 to 19 years old initiated on ART between April 2004-December 2013. First-line ART regimens before April 2010 consisted of stavudine or zidovudine with lamivudine and either efavirenz or nevirapine. Tenofovir and/or abacavir was substituted for stavudine after April 2010 in first-line ART. We evaluated the frequency and type of single-drug substitutions, treatment interruptions, and switches to second-line therapy. Fine and Gray competing risk regression models were used to evaluate the association of antiretroviral drug type with single-drug substitutions, treatment interruptions, and second-line switches in the first 24-months on treatment.
RESULTS: 398 (15.3%) single-drug substitutions, 187 (7.2%) treatment interruptions and 86 (3.3%) switches to second-line therapy occurred among 2602 pediatric patients over 24-months on ART. Overall, the rate of single-drug substitutions started to increase in 2009, peaked in 2011 at 25%, then declined to 10% in 2013, well after the integration of tenofovir into pediatric regimens; no patients over the age of 3 were initiated on abacavir for first-line therapy. Competing risk regression models showed patients on zidovudine or stavudine had upwards of a 5-fold increase in single-drug substitution vs. patients initiated on tenofovir in the first 24-months on ART. Older adolescents also had a 2-3-fold increase in treatment interruptions and switches to second-line therapy compared to younger patients in the first 24-months on ART.
CONCLUSIONS: The decline in single-drug substitutions is associated with introduction of tenofovir. Tenofovir use could improve regimen durability and treatment outcomes in resource-limited settings
Strategies and Interventions for Increasing Homework Completion and Accuracy
This four part thesis contains: Analytic review of literature of the work of a number of authors and researchers who discuss strategies and interventions aimed at improving students\u27 homework completion and accuracy rates. Discussion of the specific roles that students, parents, and families play and the contributions of teachers when it comes to homework. It will discuss a variety of ways that teachers can encourage students to complete their homework and do so with accuracy. A discussion of the implications for teachers including the pros and cons of several interventions. The limitations of the review and several recommendations for future research
Glimmers: Resolving the Privacy/Trust Quagmire
Many successful services rely on trustworthy contributions from users. To
establish that trust, such services often require access to privacy-sensitive
information from users, thus creating a conflict between privacy and trust.
Although it is likely impractical to expect both absolute privacy and
trustworthiness at the same time, we argue that the current state of things,
where individual privacy is usually sacrificed at the altar of trustworthy
services, can be improved with a pragmatic , which allows
services to validate user contributions in a trustworthy way without forfeiting
user privacy. We describe how trustworthy hardware such as Intel's SGX can be
used client-side -- in contrast to much recent work exploring SGX in cloud
services -- to realize the Glimmer architecture, and demonstrate how this
realization is able to resolve the tension between privacy and trust in a
variety of cases
Composable Probabilistic Inference with Blaise
Probabilistic inference provides a unified, systematic framework for specifying and solving these problems. Recent work has demonstrated the great value of probabilistic models defined over complex, structured domains. However, our ability to imagine probabilistic models has far outstripped our ability to programmatically manipulate them and to effectively implement inference, limiting the complexity of the problems that we can solve in practice.This thesis presents Blaise, a novel framework for composable probabilistic modeling and inference, designed to address these limitations. Blaise has three components: * The Blaise State-Density-Kernel (SDK) graphical modeling language that generalizes factor graphs by: (1) explicitly representing inference algorithms (and their locality) using a new type of graph node, (2) representing hierarchical composition and repeated substructures in the state space, the interest distribution, and the inference procedure, and (3) permitting the structure of the model to change during algorithm execution. * A suite of SDK graph transformations that may be used to extend a model (e.g. to construct a mixture model from a model of a mixture component), or to make inference more effective (e.g. by automatically constructing a parallel tempered version of an algorithm or by exploiting conjugacy in a model). * The Blaise Virtual Machine, a runtime environment that can efficiently execute the stochastic automata represented by Blaise SDK graphs. Blaise encourages the construction of sophisticated models by composing simpler models, allowing the designer to implement and verify small portions of the model and inference method, and to reuse model components from one task to another. Blaise decouples the implementation of the inference algorithm from the specification of the interest distribution, even in cases (such as Gibbs sampling) where the shape of the interest distribution guides the inference. This gives modelers the freedom to explore alternate models without slow, error-prone reimplementation. The compositional nature of Blaise enables novel reinterpretations of advanced Monte Carlo inference techniques (such as parallel tempering) as simple transformations of Blaise SDK graphs.In this thesis, I describe each of the components of the Blaise modeling framework, as well as validating the Blaise framework by highlighting a variety of contemporary sophisticated models that have been developed by the Blaise user community. I also present several surprising findings stemming from the Blaise modeling framework, including that an Infinite Relational Model can be built using exactly the same inference methods as a simple mixture model, that constructing a parallel tempered inference algorithm should be a point-and-click/one-line-of-code operation, and that Markov chain Monte Carlo for probabilistic models with complicated long-distance dependencies, such as a stochastic version of Scheme, can be managed using standard Blaise mechanisms
Degradation of lignin β-aryl ether units in Arabidopsis thaliana expressing LigD, LigF and LigG from Sphingomonas paucimobilis SYK-6
Lignin is a major polymer in the secondary plant cell wall and composed of hydrophobic interlinked hydroxyphenylpropanoid units. The presence of lignin hampers conversion of plant biomass into biofuels; plants with modified lignin are therefore being investigated for increased digestibility. The bacterium Sphingomonas paucimobilis produces lignin-degrading enzymes including LigD, LigF and LigG involved in cleaving the most abundant lignin interunit linkage, the beta-aryl ether bond. In this study, we expressed the LigD, LigF and LigG (LigDFG) genes in Arabidopsis thaliana to introduce postlignification modifications into the lignin structure. The three enzymes were targeted to the secretory pathway. Phenolic metabolite profiling and 2D HSQC NMR of the transgenic lines showed an increase in oxidized guaiacyl and syringyl units without concomitant increase in oxidized beta-aryl ether units, showing lignin bond cleavage. Saccharification yield increased significantly in transgenic lines expressing LigDFG, showing the applicability of our approach. Additional new information on substrate specificity of the LigDFG enzymes is also provided
Children balance theories and evidence in exploration, explanation, and learning
We look at the effect of evidence and prior beliefs on exploration, explanation and learning. In Experiment 1, we tested children both with and without differential prior beliefs about balance relationships (Center Theorists, mean: 82 months; Mass Theorists, mean: 89 months; No Theory children, mean: 62 months). Center and Mass Theory children who observed identical evidence explored the block differently depending on their beliefs. When the block was balanced at its geometric center (belief-violating to a Mass Theorist, but belief-consistent to a Center Theorist), Mass Theory children explored the block more, and Center Theory children showed the standard novelty preference; when the block was balanced at the center of mass, the pattern of results reversed. The No Theory children showed a novelty preference regardless of evidence. In Experiments 2 and 3, we follow-up on these findings, showing that both Mass and Center Theorists selectively and differentially appeal to auxiliary variables (e.g., a magnet) to explain evidence only when their beliefs are violated. We also show that children use the data to revise their predictions in the absence of the explanatory auxiliary variable but not in its presence. Taken together, these results suggest that children’s learning is at once conservative and flexible; children integrate evidence, prior beliefs, and competing causal hypotheses in their exploration, explanation, and learning.American Psychological Foundation (Elizabeth Munsterberg Koppitz Fellowship)James S. McDonnell Foundation (Collaborative Interdisciplinary Grant on Causal Reasoning)National Science Foundation (U.S.) (NSF Faculty Early Career Development Award)Templeton Foundation (Award
The rational child : theories and evidence in prediction, exploration, and explanation
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.Includes bibliographical references (p. 122-133).In this thesis, rational Bayesian models and the Theory-theory are bridged to explore ways in which children can be described as Bayesian scientists. I investigate what it means for children to take a rational approach to processes that support learning. In particular, I present empirical studies that show children making rational predictions, exploration, and explanations. I test the claim that differences in prior beliefs or changes in the observed evidence should affect these behaviors. The studies presented in this thesis encompass two manipulations: in some conditions, children's prior beliefs are equal, but the patterns of evidence are varied; in other conditions, children observe identical evidence but children's prior beliefs are varied. I incorporate an additional approach in this thesis, testing children within a variety of domains, tapping into their intuitive theories of biological kinds, psychosomatic illness, balance, and physical systems. Chapter One introduces the problem. Chapter Two explores how evidence and children's strong beliefs about biological events and psychosomatic illness influence their forced-choice explanations in a story-book task. Chapter Three presents a training study to further investigate the developmental differences discussed in Chapter Two. Chapter Four looks at how children's strong differential beliefs of balance interact with evidence to affect their predictions, play, explanations, and learning.(cont.) Chapter Five looks at children's exploratory play with a jack-in-the-box, (where children don't have strong, differential beliefs), given different patterns of evidence. Chapter Six investigates children's explanations following theory-neutral evidence about a mechanical toy. Chapter Seven concludes the thesis. The following chapters will suggest that frameworks combining evidence and theories capture children's causal learning about the world.by Elizabeth R. Bonawitz.Ph.D
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