8 resultados para test case optimization
em Duke University
Resumo:
© 2013 The Association for the Study of Animal Behaviour.Social complexity, often estimated by group size, is seen as driving the complexity of vocal signals, but its relation to olfactory signals, which arguably arose to function in nonsocial realms, remains underappreciated. That olfactory signals also may mediate within-group interaction, vary with social complexity and promote social cohesion underscores a potentially crucial link with sociality. To examine that link, we integrated chemical and behavioural analyses to ask whether olfactory signals facilitate reproductive coordination in a strepsirrhine primate, the Coquerel's sifaka, Propithecus coquereli. Belonging to a clade comprising primarily solitary, nocturnal species, the diurnal, group-living sifaka represents an interesting test case. Convergent with diurnal, group-living lemurids, sifakas expressed chemically rich scent signals, consistent with the social complexity hypothesis for communication. These signals minimally encoded the sex of the signaller and varied with female reproductive state. Likewise, sex and female fertility were reflected in within-group scent investigation, scent marking and overmarking. We further asked whether, within breeding pairs, the stability or quality of the pair's bond influences the composition of glandular signals and patterns of investigatory or scent-marking behaviour. Indeed, reproductively successful pairs tended to show greater similarity in their scent signals than did reproductively unsuccessful pairs, potentially through chemical convergence. Moreover, scent marking was temporally coordinated within breeding pairs and was influenced by past reproductive success. That olfactory signalling reflects social bondedness or reproductive history lends support to recent suggestions that the quality of relationships may be a more valuable proxy than group size for estimating social complexity. We suggest that olfactory signalling in sifakas is more complex than previously recognized and, as in other socially integrated species, can be a crucial mechanism for promoting group cohesion and maintaining social bonds. Thus, the evolution of sociality may well be reflected in the complexity of olfactory signalling.
Resumo:
The high energetic costs of building and maintaining large brains are thought to constrain encephalization. The 'expensive-tissue hypothesis' (ETH) proposes that primates (especially humans) overcame this constraint through reduction of another metabolically expensive tissue, the gastrointestinal tract. Small guts characterize animals specializing on easily digestible diets. Thus, the hypothesis may be tested via the relationship between brain size and diet quality. Platyrrhine primates present an interesting test case, as they are more variably encephalized than other extant primate clades (excluding Hominoidea). We find a high degree of phylogenetic signal in the data for diet quality, endocranial volume and body size. Controlling for phylogenetic effects, we find no significant correlation between relative diet quality and relative endocranial volume. Thus, diet quality fails to account for differences in platyrrhine encephalization. One taxon, in particular, Brachyteles, violates predictions made by ETH in having a large brain and low-quality diet. Dietary reconstructions of stem platyrrhines further indicate that a relatively high-quality diet was probably in place prior to increases in encephalization. Therefore, it is unlikely that a shift in diet quality was a primary constraint release for encephalization in platyrrhines and, by extrapolation, humans.
Resumo:
In this dissertation, I offer a pedagogical proposal for learning the Christian Scriptures guided by respect for the nature of the reader and the integrity of the biblical text. Christian educators have profitably developed recent theoretical interest in the body’s role in human meaning with regard to worship and praxis methodologies, but the implications of this research for communal study of the biblical text merit further development. I make the case for adopting scriptural imagination as the goal of pedagogically constructed encounters with the Christian Scriptures. The argument proceeds through a series of questions addressing both sides of the text/reader encounter.
Chapter one considers the question “what is the nature of the reader and, subsequently, the shape of the reader’s ways of knowing?” This investigation into recent literature on the body’s involvement in human knowing includes related epistemological shifts with Christian education. On the basis of this survey, imagination emerges as a compelling designator of an incorporative, constructive creaturely capacity that gives rise to a way of being in the world. Teachers of Scripture who intend to participate in Christian formation should account for the imagination’s centrality for all knowing. After briefly situating this proposal within a theological account of creatureliness, I make the initial case for Scriptural imagination as a pedagogical aim.
Imagination as creaturely capacity addresses the first guiding value, but does this proposal also respect the integrity and nature of the biblical text, and specifically of biblical narratives? In response, in chapter two I take up the Acts of the Apostles as a potential test case and exemplar for the dynamics pertinent to the formation of imagination. Drawing on secondary literature on the genre and literary features of Acts, I conclude that Acts coheres with this project’s explicit interest in imagination as a central component of the process of Christian formation in relationship to the Scriptures.
Chapters three and four each take up a pericope from Acts to assess whether the theoretical perspectives developed in prior chapters generate any interpretive payoff. In each of these chapters, a particular story within Acts functions as a test case for readings of biblical narratives guided by a concern for scriptural imagination. Each of these chapters begins with further theoretical development of some element of imaginal formation. Chapter three provides a theoretical account of practices as they relate to imagination, bringing that theory into conversation with Peter’s engagement in hospitality practices with Cornelius in Acts 10:1-11:18. Chapter four discusses the formative power of narratives, with implications for the analysis of Paul’s shipwreck in Acts 27:1-28:16.
In the final chapter, I offer a two-part constructive pedagogical proposal for reading scriptural narratives in Christian communities. First, I suggest adopting resonance above relevance as the goal of pedagogically constructed encounters with the Scriptures. Second, I offer three ways of reading with the body, including the physical, ecclesial, and social bodies that shape all learning. I conclude by identifying the importance of scriptural imagination for Christian formation and witness in the twenty-first century.
Resumo:
Purpose: To investigate the effect of incorporating a beam spreading parameter in a beam angle optimization algorithm and to evaluate its efficacy for creating coplanar IMRT lung plans in conjunction with machine learning generated dose objectives.
Methods: Fifteen anonymized patient cases were each re-planned with ten values over the range of the beam spreading parameter, k, and analyzed with a Wilcoxon signed-rank test to determine whether any particular value resulted in significant improvement over the initially treated plan created by a trained dosimetrist. Dose constraints were generated by a machine learning algorithm and kept constant for each case across all k values. Parameters investigated for potential improvement included mean lung dose, V20 lung, V40 heart, 80% conformity index, and 90% conformity index.
Results: With a confidence level of 5%, treatment plans created with this method resulted in significantly better conformity indices. Dose coverage to the PTV was improved by an average of 12% over the initial plans. At the same time, these treatment plans showed no significant difference in mean lung dose, V20 lung, or V40 heart when compared to the initial plans; however, it should be noted that these results could be influenced by the small sample size of patient cases.
Conclusions: The beam angle optimization algorithm, with the inclusion of the beam spreading parameter k, increases the dose conformity of the automatically generated treatment plans over that of the initial plans without adversely affecting the dose to organs at risk. This parameter can be varied according to physician preference in order to control the tradeoff between dose conformity and OAR sparing without compromising the integrity of the plan.
Resumo:
BACKGROUND: In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many of these experiments, the scientific aim is the identification of genes for which the trajectories depend on an experimental or phenotypic factor. There is an extensive recent body of literature on statistical methodology for addressing this analytical problem. Most of the existing methods are based on estimating the time-course trajectories using parametric or non-parametric mean regression methods. The sensitivity of these regression methods to outliers, an issue that is well documented in the statistical literature, should be of concern when analyzing microarray data. RESULTS: In this paper, we propose a robust testing method for identifying genes whose expression time profiles depend on a factor. Furthermore, we propose a multiple testing procedure to adjust for multiplicity. CONCLUSIONS: Through an extensive simulation study, we will illustrate the performance of our method. Finally, we will report the results from applying our method to a case study and discussing potential extensions.
Resumo:
In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of maximizing the expected value of a payoff function when the underlying distribution is ambiguous and therefore robustness is relevant. Our primary objective is to develop this framework and relate it to the standard notion of robustness, which deals with only a single guarantee across one uncertainty set. First, we show that our approach connects closely to the theory of convex risk measures. We show that the complexity of this approach is equivalent to that of solving a small number of standard robust problems. We then investigate the conservatism benefits and downside probability guarantees implied by this approach and compare to the standard robust approach. Finally, we illustrate theme thodology on an asset allocation example consisting of historical market data over a 25-year investment horizon and find in every case we explore that relaxing standard robustness with soft robustness yields a seemingly favorable risk-return trade-off: each case results in a higher out-of-sample expected return for a relatively minor degradation of out-of-sample downside performance. © 2010 INFORMS.
Resumo:
The environment affects our health, livelihoods, and the social and political institutions within which we interact. Indeed, nearly a quarter of the global disease burden is attributed to environmental factors, and many of these factors are exacerbated by global climate change. Thus, the central research question of this dissertation is: How do people cope with and adapt to uncertainty, complexity, and change of environmental and health conditions? Specifically, I ask how institutional factors, risk aversion, and behaviors affect environmental health outcomes. I further assess the role of social capital in climate adaptation, and specifically compare individual and collective adaptation. I then analyze how policy develops accounting for both adaptation to the effects of climate and mitigation of climate-changing emissions. In order to empirically test the relationships between these variables at multiple levels, I combine multiple methods, including semi-structured interviews, surveys, and field experiments, along with health and water quality data. This dissertation uses the case of Ethiopia, Africa’s second-most populous nation, which has a large rural population and is considered very vulnerable to climate change. My fieldwork included interviews and institutional data collection at the national level, and a three-year study (2012-2014) of approximately 400 households in 20 villages in the Ethiopian Rift Valley. I evaluate the theoretical relationships between households, communities, and government in the process of adaptation to environmental stresses. Through my analyses, I demonstrate that water source choice varies by individual risk aversion and institutional context, which ultimately has implications for environmental health outcomes. I show that qualitative measures of trust predict cooperation in adaptation, consistent with social capital theory, but that measures of trust are negatively related with private adaptation by the individual. Finally, I describe how Ethiopia had some unique characteristics, significantly reinforced by international actors, that led to the development of an extensive climate policy, and yet with some challenges remaining for implementation. These results suggest a potential for adaptation through the interactions among individuals, communities, and government in the search for transformative processes when confronting environmental threats and climate change.
Resumo:
Free energy calculations are a computational method for determining thermodynamic quantities, such as free energies of binding, via simulation.
Currently, due to computational and algorithmic limitations, free energy calculations are limited in scope.
In this work, we propose two methods for improving the efficiency of free energy calculations.
First, we expand the state space of alchemical intermediates, and show that this expansion enables us to calculate free energies along lower variance paths.
We use Q-learning, a reinforcement learning technique, to discover and optimize paths at low computational cost.
Second, we reduce the cost of sampling along a given path by using sequential Monte Carlo samplers.
We develop a new free energy estimator, pCrooks (pairwise Crooks), a variant on the Crooks fluctuation theorem (CFT), which enables decomposition of the variance of the free energy estimate for discrete paths, while retaining beneficial characteristics of CFT.
Combining these two advancements, we show that for some test models, optimal expanded-space paths have a nearly 80% reduction in variance relative to the standard path.
Additionally, our free energy estimator converges at a more consistent rate and on average 1.8 times faster when we enable path searching, even when the cost of path discovery and refinement is considered.