Robust and Optimal Methods for Geometric Sensor Data Alignment

Geometric sensor data alignment - the problem of finding the rigid transformation that correctly aligns two sets of sensor data without prior knowledge of how the data correspond - is a fundamental task in computer vision and robotics. It is inconvenient then that outliers and non-convexity are inherent to the problem and present significant challenges for alignment algorithms. Outliers are highly prevalent in sets of sensor data, particularly when the sets overlap incompletely. Despite this, many alignment objective functions are not robust to outliers, leading to erroneous alignments. In addition, alignment problems are highly non-convex, a property arising from the objective function and the transformation. While finding a local optimum may not be difficult, finding the global optimum is a hard optimisation problem. These key challenges have not been fully and jointly resolved in the existing literature, and so there is a need for robust and optimal solutions to alignment problems. Hence the objective of this thesis is to develop tractable algorithms for geometric sensor data alignment that are robust to outliers and not susceptible to spurious local optima. This thesis makes several significant contributions to the geometric alignment literature, founded on new insights into robust alignment and the geometry of transformations. Firstly, a novel discriminative sensor data representation is proposed that has better viewpoint invariance than generative models and is time and memory efficient without sacrificing model fidelity. Secondly, a novel local optimisation algorithm is developed for nD-nD geometric alignment under a robust distance measure. It manifests a wider region of convergence and a greater robustness to outliers and sampling artefacts than other local optimisation algorithms. Thirdly, the first optimal solution for 3D-3D geometric alignment with an inherently robust objective function is proposed. It outperforms other geometric alignment algorithms on challenging datasets due to its guaranteed optimality and outlier robustness, and has an efficient parallel implementation. Fourthly, the first optimal solution for 2D-3D geometric alignment with an inherently robust objective function is proposed. It outperforms existing approaches on challenging datasets, reliably finding the global optimum, and has an efficient parallel implementation. Finally, another optimal solution is developed for 2D-3D geometric alignment, using a robust surface alignment measure. Ultimately, robust and optimal methods, such as those in this thesis, are necessary to reliably find accurate solutions to geometric sensor data alignment problems

Immune cell status, cardiorespiratory fitness and body composition among breast cancer survivors and healthy women: a cross sectional study

Methods: We examined whether immune cell profiles differ between healthy women (n = 38) and breast cancer survivors (n = 27) within 2 years of treatment, and whether any group-differences were influenced by age, cytomegalovirus infection, cardiorespiratory fitness and body composition. Using flow cytometry, CD4+ and CD8+ T cell subsets, including naïve (NA), central memory (CM) and effector cells (EM and EMRA) were identified using CD27/CD45RA. Activation was measured by HLA-DR expression. Stem cell-like memory T cells (TSCMs) were identified using CD95/CD127. B cells, including plasmablasts, memory, immature and naïve cells were identified using CD19/CD27/CD38/CD10. Effector and regulatory Natural Killer cells were identified using CD56/CD16. Results: Compared to healthy women, CD4+ CM were +Δ21% higher among survivors (p = 0.028) and CD8+ NA were −Δ25% lower (p = 0.034). Across CD4+ and CD8+ subsets, the proportion of activated (HLA-DR+) cells was +Δ31% higher among survivors: CD4+ CM (+Δ25%), CD4+ EM (+Δ32%) and CD4+ EMRA (+Δ43%), total CD8+ (+Δ30%), CD8+ EM (+Δ30%) and CD8+ EMRA (+Δ25%) (p 0.305, p < 0.019). The association between fat mass index and HLA-DR+ CD8+ EMRA T cells withstood statistical adjustment for all variables, including age, CMV serostatus, lean mass and cardiorespiratory fitness, potentially implicating these cells as contributors to inflammatory/immune-dysfunction in overweight/obesity

Policy Feedback and the Politics of the Affordable Care Act

There is a large body of literature devoted to how “policies create politics” and how feedback effects from existing policy legacies shape potential reforms in a particular area. Although much of this literature focuses on self‐reinforcing feedback effects that increase support for existing policies over time, Kent Weaver and his colleagues have recently drawn our attention to self‐undermining effects that can gradually weaken support for such policies. The following contribution explores both self‐reinforcing and self‐undermining policy feedback in relationship to the Affordable Care Act, the most important health‐care reform enacted in the United States since the mid‐1960s. More specifically, the paper draws on the concept of policy feedback to reflect on the political fate of the ACA since its adoption in 2010. We argue that, due in part to its sheer complexity and fragmentation, the ACA generates both self‐reinforcing and self‐undermining feedback effects that, depending of the aspect of the legislation at hand, can either facilitate or impede conservative retrenchment and restructuring. Simultaneously, through a discussion of partisan effects that shape Republican behavior in Congress, we acknowledge the limits of policy feedback in the explanation of policy stability and change

A phenomic perspective on factors influencing breast cancer treatment: integrating aging and lifestyle in blood and tissue biomarker profiling

Breast cancer is the most common malignancy among women worldwide. Over the last four decades, diagnostic and therapeutic procedures have improved substantially, giving patients with localized disease a better chance of cure, and those with more advanced cancer, longer periods of disease control and survival. However, understanding and managing heterogeneity in the clinical response exhibited by patients remains a challenge. For some treatments, biomarkers are available to inform therapeutic options, assess pathological response and predict clinical outcomes. Nevertheless, some measurements are not employed universally and lack sensitivity and specificity, which might be influenced by tissue-specific alterations associated with aging and lifestyle. The first part of this article summarizes available and emerging biomarkers for clinical use, such as measurements that can be made in tumor biopsies or blood samples, including so-called liquid biopsies. The second part of this article outlines underappreciated factors that could influence the interpretation of these clinical measurements and affect treatment outcomes. For example, it has been shown that both adiposity and physical activity can modify the characteristics of tumors and surrounding tissues. In addition, evidence shows that inflammaging and immunosenescence interact with treatment and clinical outcomes and could be considered prognostic and predictive factors independently. In summary, changes to blood and tissues that reflect aging and patient characteristics, including lifestyle, are not commonly considered clinically or in research, either for practical reasons or because the supporting evidence base is developing. Thus, an aim of this article is to encourage an integrative phenomic approach in oncology research and clinical management

Review article: Existing and potential evidence for Holocene grounding line retreat and readvance in Antarctica

Widespread existing geological records from above the modern ice sheet surface and outboard of the current ice margin show that the Antarctic Ice Sheet (AIS) was much more extensive at the Last Glacial Maximum (∼ 20 ka) than at present. However, whether it was ever smaller than present during the last few millennia, and (if so) by how much, is known only for a few locations because direct evidence lies within or beneath the ice sheet, which is challenging to access. Here, we describe how retreat and readvance (henceforth “readvance”) of AIS grounding lines during the Holocene could be detected and quantified using subglacial bedrock, subglacial sediments, marine sediment cores, relative sea-level (RSL) records, geodetic observations, radar data, and ice cores. Of these, only subglacial bedrock and subglacial sediments can provide direct evidence for readvance. Marine archives are of limited utility because readvance commonly covers evidence of earlier retreat. Nevertheless, stratigraphic transitions documenting change in environment may provide support for direct evidence from subglacial records, as can the presence of transgressions in RSL records, and isostatic subsidence. With independent age control, ice structure revealed by radar can be used to infer past changes in ice flow and geometry, and therefore potential readvance. Since ice cores capture changes in surface mass balance, elevation, and atmospheric and oceanic circulation that are known to drive grounding line migration, they also have potential for identifying readvance. A multidisciplinary approach is likely to provide the strongest evidence for or against a smaller-than-present AIS in the Holocene

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

A Many-analysts Approach to the Relation Between Religiosity and Well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N = 10, 535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β = 0.120). For the second research question, this was the case for 65% of the teams (median reported β = 0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis