Multivariate Approaches to Classification in Extragalactic Astronomy

Clustering objects into synthetic groups is a natural activity of any science. Astrophysics is not an exception and is now facing a deluge of data. For galaxies, the one-century old Hubble classification and the Hubble tuning fork are still largely in use, together with numerous mono-or bivariate classifications most often made by eye. However, a classification must be driven by the data, and sophisticated multivariate statistical tools are used more and more often. In this paper we review these different approaches in order to situate them in the general context of unsupervised and supervised learning. We insist on the astrophysical outcomes of these studies to show that multivariate analyses provide an obvious path toward a renewal of our classification of galaxies and are invaluable tools to investigate the physics and evolution of galaxies.Comment: Open Access paper. http://www.frontiersin.org/milky\_way\_and\_galaxies/10.3389/fspas.2015.00003/abstract\>. \<10.3389/fspas.2015.00003 \&g

Multistate Markov Models for Ordinal Functional Outcomes of Acute Onset Disease: Application in Acute Stroke Therapy Trials

The modified Rankin Scale (mRS), a seven-point ordinal scale ranging from no symptoms to death, is the most commonly used outcome measures in acute stroke therapy trials. Often, one visit is chosen for the primary analysis, and the scale is dichotomized leading to loss of information. Recently, alternative methods for analyzing the mRS have been explored. In addition, acute onset conditions require immediate attention and treatment, posing a challenge to assess baseline outcome measures for clinical trials. Thus, the mRS is not obtainable at baseline. Much of the progression or recovery experienced by a patient suffering from an acute onset disease is expected to occur early on. Moreover, typically, the goal of a treatment or therapeutic action is improvement in patient health compared to their baseline measure. To accurately quantify improvement, a measure of the outcome at baseline is ideal. This dissertation first explores the feasibility of multistate Markov models for the analysis of the mRS which allow for the full ordinal scale as well as the repeated measures data to be incorporated. The operating characteristics (type I error and power) of the multistate Markov model are compared with those from repeated logistic regression. Next, a framework is developed to predict and incorporate the latent baseline mRS score in a piecewise-constant multistate model. The last part of this work applies the piecewise-constant latent baseline model to real acute stroke trial data and compares the results with alternative methods for analysis of the mRS

Statistical Degradation Models for Electronics

With increasing presence of electronics in modern systems and in every-day products, their reliability is inextricably dependent on that of their electronics. We develop reliability models for failure-time prediction under small failure-time samples and information on individual degradation history. The development of the model extends the work of Whitmore et al. 1998, to incorporate two new data-structures common to reliability testing. Reliability models traditionally use lifetime information to evaluate the reliability of a device or system. To analyze small failure-time samples within dynamic environments where failure mechanisms are unknown, there is a need for models that make use of auxiliary reliability information. In this thesis we present models suitable for reliability data, where degradation variables are latent and can be tracked by related observable variables we call markers. We provide an engineering justification for our model and develop parametric and predictive inference equations for a data-structure that includes terminal observations of the degradation variable and longitudinal marker measurements. We compare maximum likelihood estimation and prediction results obtained by Whitmore et. al. 1998 and show improvement in inference under small sample sizes. We introduce modeling of variable failure thresholds within the framework of bivariate degradation models and discuss ways of incorporating covariates. In the second part of the thesis we investigate anomaly detection through a Bayesian support vector machine and discuss its place in degradation modeling. We compute posterior class probabilities for time-indexed covariate observations, which we use as measures of degradation. Lastly, we present a multistate model used to model a recurrent event process and failure-times. We compute the expected time to failure using counting process theory and investigate the effect of the event process on the expected failure-time estimates

Nonlinear data driven techniques for process monitoring

The goal of this research is to develop process monitoring technology capable of taking advantage of the large stores of data accumulating in modern chemical plants. There is demand for new techniques for the monitoring of non-linear topology and behavior, and this research presents a topological preservation method for process monitoring using Self Organizing Maps (SOM). The novel architecture presented adapts SOM to a full spectrum of process monitoring tasks including fault detection, fault identification, fault diagnosis, and soft sensing. The key innovation of the new technique is its use of multiple SOM (MSOM) in the data modeling process as well as the use of a Gaussian Mixture Model (GMM) to model the probability density function of classes of data. For comparison, a linear process monitoring technique based on Principal Component Analysis (PCA) is also used to demonstrate the improvements SOM offers. Data for the computational experiments was generated using a simulation of the Tennessee Eastman process (TEP) created in Simulink by (Ricker 1996). Previous studies focus on step changes from normal operations, but this work adds operating regimes with time dependent dynamics not previously considered with a SOM. Results show that MSOM improves upon both linear PCA as well as the standard SOM technique using one map for fault diagnosis, and also shows a superior ability to isolate which variables in the data are responsible for the faulty condition. With respect to soft sensing, SOM and MSOM modeled the compositions equally well, showing that no information was lost in dividing the map representation of process data. Future research will attempt to validate the technique on a real chemical process

Cultural continuities and discontinuities at the Neolithic transition in Eastern Iberia: an analysis of the morphometry of geometric microliths

The main goal of this paper is to explore possible cultural continuities and discontinuities at the Neolithic transition in Eastern Iberia. To address this issue, we introduce a twofold methodology, consisting of Geometric Morphometrics and the use of the self-developed Geomeasure system, to examine evolutionary patterns in geometric microliths. These are a specific type of arrowhead shared by both the last hunter-gatherers and the first farmers from two reference sites in the region: Cueva de la Cocina and Cova de l’Or (Eastern Iberia). Although advances in research have contributed to a better comprehension of this process, there are still unanswered questions, especially when the study is approached from a regional perspective. Such is the case for the Neolithisation of the Eastern Iberian Peninsula, and the way in which the previous Mesolithic population interacted—if they interacted at all—with the first farmers. In this case, some sites present archaeological contexts that have been catalogued as acculturation contexts. This has traditionally been the case for phase C of Cueva de la Cocina (Spain), although recent research points to the possibility that the content of this specific deposit is the result of post-depositional processes. Here we try first to understand the cultural evolutionary patterns and relations between the different geometric microlith technocomplexes and, second, to address the specific problem of the interpretation of taphonomic disturbances in the archaeological record. We use the Cueva de l’Or and the Cueva de la Cocina for comparison, and our conclusions raise serious doubts about the existence of an acculturation phase at the latter

Life and death in wolverines

Developing trustworthy conservation planning for endangered species requires a deep understanding of the variations of their populations in both space and time. I used individual-based long-term location and demographic data on wolverines (Gulo gulo) in Northern Sweden, and data on reproductions from the national monitoring systems of Norway and Sweden, to analyze how wolverine demography in Scandinavia is affected by variation in habitat and management policies. Wolverines showed agerelated patterns of reproduction and reproductive costs, which were influenced by seasonal resources. The top predator Eurasian lynx (Lynx lynx) increase scavenging opportunities on reindeer (Rangifer tarandus) carrion, and wolverines and lynx selected for the same habitats when sharing prey base and sources of adult mortality. Illegal killing was a main source of adult mortality in brown bears (Ursus arctos), lynx and wolverines in northern Sweden, and the risk of being illegally killed was in general higher in national parks and on reindeer calving grounds, and lower in forest and steep terrain. At population level, the reproductive range of wolverines was set by latitude and elevation; presence of reindeer and lynx, rugged terrain and higher primary production had a positive effect; whereas human dominated habitats negatively influenced the frequency of reproductions. Different management policies influenced the frequency of wolverine reproductions; in Sweden this was 2 times higher than in Norway. Finally, I show that in Sweden, adult female wolverines were illegally killed at lower rates than males. Thus, the Swedish carnivore conservation payment system, which pays for wolverine reproductions, protects the demographic segment that is most important for population growth. Carnivores impose negative impact on rural economies and herding cultures in Scandinavia, and there will be need for continued monitoring combined with economic incentives to ensure carnivore-human coexistence. The approach of linking life histories to habitat has the potential for in-depth studies of mechanisms shaping spatial and temporal variation in populations, and should be implemented in future adaptive management for species persistence

Stonecat ecology in St. Vrain Creek, CO

2018 Fall.Includes bibliographical references.Stonecat Noturus flavus are a small-bodied native catfish found from southern Canada to the southern United States, and from the Appalachian Mountains to the Rocky Mountains. In Colorado, there are two remaining populations of Stonecat, including one geographically isolated population in St. Vrain Creek, which runs through the Front Range in Longmont, CO. There are five major drainages running through Colorado's Front Range, which is where most of the state's population is concentrated. As such, these streams are highly urbanized. When compared to the other four major Front Range streams, St. Vrain Creek contains a disproportionately high number of native fish species, including Colorado Species of Special Concern such as Stonecats. There has not yet been a quantitative analysis of population demographic parameters or individual habitat selection preferences of Stonecats. I sought to estimate both of these through a mark-recapture study using passive integrated transponder (PIT) tags. There are a number of assumptions associated with mark-recapture studies which I addressed through individual experiments, including tag loss, physical closure and detection probability of known tags. I evaluated tag loss under laboratory conditions. PIT tags were surgically implanted into the peritoneal cavity of Stonecats (n = 157) ranging from 71 mm to 213 mm through an incision closed with a single Braunamid suture and the fish were monitored for 120 weeks. After 120 weeks, there were fifteen lost tags (9.6%) and eight mortalities (5.0%). I evaluated our dataset of individual encounter histories and covariates including time since tagging, fish length and tag type in a multistate model framework using Program MARK. Time since tagging has an inverse effect on tag loss; if fish are going to lose tags, it will be relatively soon post-tagging. Additionally, fish length has a negative effect, with tag loss decreasing with fish length. These results support our assumption that using PIT tags to individually mark Stonecats is an appropriate method, and we now have a better understanding of tag loss rates over a long-term study period. I evaluated population demographic parameters and individual habitat selection preferences of Stonecats in a field experiment. PIT tags were surgically implanted in Stonecats (n = 679) ranging from 70 mm to 230 mm. I monitored tagged Stonecats with both static and mobile PIT antennae. Our results from the static antennae show that the proportion of Stonecat encounters are higher at night and during the summertime. From the mobile PIT antenna results, I determined Stonecats prefer coarse substrate at an intermediate velocity (0.29 m/s) and intermediate depth (0.3 m). Conclusions from this study will be used to inform future urban stream management in conjunction with managing for sensitive fishes such as Stonecats

The course of disability in the very old :drivers and trajectories

PhD ThesisIn recent decades the rapid growth in the numbers of the very old, those aged 85 years and above, has made them the fastest growing age group of most populations worldwide. Nevertheless we know little about their health and disability, the latter being a particularly important aspect of quality of life for individuals but also more widely as a major determinant for residential care. This thesis uses a unique study, the Newcastle 85+ Study, a longitudinal, population based cohort study of people born in 1921 and aged 85 years at first interview in 2006, to explore the disablement process in very late life through three substantive sub-studies. In the first sub-study I explore how disability unfolds through the order of loss in basic and instrumental activities of daily living [(I)ADLs, these being the building blocks of disability. (I)ADLs were lost in a specific order, activities requiring long distance mobility and balance (for example shopping) being lost first and those requiring upper body strength (e.g. dressing, feeding) last and with little difference between men and women. The second sub-study examines the impact of specific diseases on disability onset and finds that arthritis, diabetes and cognitive impairment were similarly disabling for men and women, cardiac disease was more disabling in women, and cardiovascular disease and respiratory disease disabling for women only. The final sub-study uses novel statistical techniques to uncover patterns of disability from age 85 to 90. Four distinct trajectories of disability were found for both sexes, with a disability-free trajectory being identified in men but not women, and all other trajectories showing increasing levels of disability. These sub-studies are discussed in the light of other literature, the extent to which they explain the greater disability yet survival of women (the disability-survival paradox), and the implications for the future

Spectral rate theory for projected two-state kinetics

Classical rate theories often fail in cases where the observable(s) or order parameter(s) used are poor reaction coordinates or the observed signal is deteriorated by noise, such that no clear separation between reactants and products is possible. Here, we present a general spectral two-state rate theory for ergodic dynamical systems in thermal equilibrium that explicitly takes into account how the system is observed. The theory allows the systematic estimation errors made by standard rate theories to be understood and quantified. We also elucidate the connection of spectral rate theory with the popular Markov state modeling (MSM) approach for molecular simulation studies. An optimal rate estimator is formulated that gives robust and unbiased results even for poor reaction coordinates and can be applied to both computer simulations and single-molecule experiments. No definition of a dividing surface is required. Another result of the theory is a model-free definition of the reaction coordinate quality (RCQ). The RCQ can be bounded from below by the directly computable observation quality (OQ), thus providing a measure allowing the RCQ to be optimized by tuning the experimental setup. Additionally, the respective partial probability distributions can be obtained for the reactant and product states along the observed order parameter, even when these strongly overlap. The effects of both filtering (averaging) and uncorrelated noise are also examined. The approach is demonstrated on numerical examples and experimental single-molecule force probe data of the p5ab RNA hairpin and the apo-myoglobin protein at low pH, here focusing on the case of two-state kinetics