Dispositions and Influences

Non peer reviewe

C. B. Martin's 'Limit View', Distinctions of Reason and the Metaphysics of Mind

This thesis is concerned with the 'Limit View' account of the nature of properties, first advanced by C. B. Martin, which holds that all real properties contribute to both the dispositional and the qualitative natures of the objects by which they are instantiated. According to the Limit View, the dispositional is identical to the qualitative, and both are identical to a single, unitary property. This distinctive position in the debate concerning the relative status of dispositional and categorical/qualitative properties has been charged with obscurity. This charge arises, in part, due to the manner in which Martin presented the view, and in part due to its standing in stark contrast to orthodox positions in the debate. In order to meet this charge, the aims of the first half of this thesis are threefold: first, to present a clear and thorough examination of the development and content of the Limit View as presented by Martin; second, to examine the Limit View in light of criticisms levelled against it and to defend it from such criticism; and, third, to present a viable and consistent, critical interpretation of the Limit View. Following this, the interpretation of the Limit View advanced in the first half of the thesis is applied to the debate concerning the ontology of mind and body. New responses to the Argument from Conceivability and the Knowledge Argument are developed; and what it means to characterise an entity as 'physical' or 'mental' is investigated. Based on the findings of this investigation, I argue that, if one accepts the Limit View, the position one should adopt concerning the ontology of mind and body is a new variant of neutral monism, which is outlined and distinguished from other positions in the debate in the final chapter of this thesis

Functional Cure of SIVagm Infection in Rhesus Macaques Results in Complete Recovery of CD4+ T Cells and Is Reverted by CD8+ Cell Depletion

Understanding the mechanism of infection control in elite controllers (EC) may shed light on the correlates of control of disease progression in HIV infection. However, limitations have prevented a clear understanding of the mechanisms of elite controlled infection, as these studies can only be performed at randomly selected late time points in infection, after control is achieved, and the access to tissues is limited. We report that SIVagm infection is elite-controlled in rhesus macaques (RMs) and therefore can be used as an animal model for EC HIV infection. A robust acute infection, with high levels of viral replication and dramatic mucosal CD4+ T cell depletion, similar to pathogenic HIV-1/SIV infections of humans and RMs, was followed by complete and durable control of SIVagm replication, defined as: undetectable VLs in blood and tissues beginning 72 to 90 days postinoculation (pi) and continuing at least 4 years; seroreversion; progressive recovery of mucosal CD4+ T cells, with complete recovery by 4 years pi; normal levels of T cell immune activation, proliferation, and apoptosis; and no disease progression. This “functional cure” of SIVagm infection in RMs could be reverted after 4 years of control of infection by depleting CD8 cells, which resulted in transient rebounds of VLs, thus suggesting that control may be at least in part immune mediated. Viral control was independent of MHC, partial APOBEC restriction was not involved in SIVagm control in RMs and Trim5 genotypes did not impact viral replication. This new animal model of EC lentiviral infection, in which complete control can be predicted in all cases, permits research on the early events of infection in blood and tissues, before the defining characteristics of EC are evident and when host factors are actively driving the infection towards the EC status

A meta-analysis of the investment-uncertainty relationship

In this article we use meta-analysis to investigate the investment-uncertainty relationship. We focus on the direction and statistical significance of empirical estimates. Specifically, we estimate an ordered probit model and transform the estimated coefficients into marginal effects to reflect the changes in the probability of finding a significantly negative estimate, an insignificant estimate, or a significantly positive estimate. Exploratory data analysis shows that there is little empirical evidence for a positive relationship. The regression results suggest that the source of uncertainty, the level of data aggregation, the underlying model specification, and differences between short- and long-run effects are important sources of variation in study outcomes. These findings are, by and large, robust to the introduction of a trend variable to capture publication trends in the literature. The probability of finding a significantly negative relationship is higher in more recently published studies. JEL Classification: D21, D80, E22 1

Emergence, Reduction and the Identity and Individuation of Powers

One recently popular way to characterise strong emergence is to say that emergent entities possess novel causal powers. However, there is little agreement concerning the nature of powers. One controversy involves whether powers are single- or multi-track; that is, whether each power has only one manifestation type, or whether a single power can be directed towards a number of distinct manifestations. Another concerns how powers operate: whether a lone power manifests when triggered by the presence of a suitable stimulus, or whether powers operate mutually such that several powers must ‘work together’ to bring about a particular manifestation. This paper examines how these distinctions—which can be cross-combined to frame four distinct accounts of the nature of powers—bear on the debate between emergentists and reductionists

Assessing impact of instruction treatments on positive test selection in hypothesis testing

The role of factors previously implicated as leading to confirmation bias during hypothesis testing was explored. Confirmation bias is a phenomenon in which people select cases for testing when the expected results of the case are more likely to support their current belief than falsify it. Klayman (1995) proposed three primary determinants for confirmation bias. Klayman and his colleagues proposed that a general positive testing strategy leads to the phenomenon of confirmation bias. According to Klayman’s account, participants in previous research were not actively working to support their hypothesis. Rather, they were applying a valid hypothesis testing strategy that works well outside of laboratory tasks. In laboratory tasks, such as Wason’s 2-4-6 task (Wason, 1960), the strategy failed because the nature of the task takes advantage of particular flaws in the positive testing behavior participants learned through their experience with the real-world. Given Klayman’s proposed set of determinants for the positive testing strategy phenomenon, treatments were developed that would directly violate the assumptions supporting application of the positive testing strategy. If participants were able to identify and act on these violations of the assumptions, the number of positive tests was expected to be reduced. The test selection portion of the Mynatt, Doherty, and Tweney (1977) microworld experiment was modified with additional instruction conditions and a new scenario description to investigate the impact of the treatments to reduce confirmation bias in test selection. Despite expectations, the thematic content modifications and determinant-targeting instruction conditions had no effect on participant positive test selection

Predicting the Influence of Rain on LIDAR in ADAS

While it is well known that rain may influence the performance of automotive LIDAR sensors commonly used in ADAS applications, there is a lack of quantitative analysis of this effect. In particular, there is very little published work on physically-based simulation of the influence of rain on terrestrial LIDAR performance. Additionally, there have been few quantitative studies on how rain-rate influences ADAS performance. In this work, we develop a mathematical model for the performance degradation of LIDAR as a function of rain-rate and incorporate this model into a simulation of an obstacle-detection system to show how it can be used to quantitatively predict the influence of rain on ADAS that use LIDAR

Enabling Off-Road Autonomous Navigation-Simulation of LIDAR in Dense Vegetation

Machine learning techniques have accelerated the development of autonomous navigation algorithms in recent years, especially algorithms for on-road autonomous navigation. However, off-road navigation in unstructured environments continues to challenge autonomous ground vehicles. Many off-road navigation systems rely on LIDAR to sense and classify the environment, but LIDAR sensors often fail to distinguish navigable vegetation from non-navigable solid obstacles. While other areas of autonomy have benefited from the use of simulation, there has not been a real-time LIDAR simulator that accounted for LIDAR–vegetation interaction. In this work, we outline the development of a real-time, physics-based LIDAR simulator for densely vegetated environments that can be used in the development of LIDAR processing algorithms for off-road autonomous navigation. We present a multi-step qualitative validation of the simulator, which includes the development of an improved statistical model for the range distribution of LIDAR returns in grass. As a demonstration of the simulator’s capability, we show an example of the simulator being used to evaluate autonomous navigation through vegetation. The results demonstrate the potential for using the simulation in the development and testing of algorithms for autonomous off-road navigation