On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

Modeling ecological and evolutionary processes in spatially structured populations

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

Cooperation and conflict in conspecific brood parasitism : an alternative reproductive tactic

Interactions among individuals give rise to both cooperation and conflict. Individuals will behave selfishly or altruistically depending on which gives the higher payoff. The reproductive strategies of many animals are flexible and several alternative tactics may be present from which the most suitable one is applied. Generally, alternative reproductive tactics may be defined as a response to competition from individuals of the same sex. These alternative reproductive tactics are means by which individuals may fine-tune their fitness to the reigning circumstances and which are shaped by the environment individuals are occupying as well as by the behaviour of other individuals sharing the environment. By employing such alternative ways of achieving reproductive output, individuals may alleviate competition from others. Conspecific brood parasitism (CBP) is an alternative reproductive strategy found in several egg laying animal groups, and it is especially common among waterfowl. Within this alternative reproductive strategy, four reproductive options can be identified. These four options represent a continuum from low reproductive effort coupled with low fitness returns, to high reproductive effort and consequently high benefits. It may not be evident how individuals should allocate reproductive effort between eggs laid in their own nest vs. in nests of others, however. Limited fecundity will constrain the number of eggs donated by a parasite, but also the tendency for hosts to accept parasitic eggs may affect the allocation decision. Furthermore, kinship, individual quality and the costs of breeding may play a role in complicating the allocation decision. In this thesis, I view the seemingly paradoxical effects of kinship on conflict resolution in the context of alternative reproductive tactics, examining the resulting features of cooperation and conflict. Conspecific brood parasitism sets the stage for investigating these questions. By using both empirical and theoretical approaches, I examine the nature of CBP in a brood parasitic duck, the Barrow's goldeneye (Bucephala islandica). The theoretical chapter of this thesis gives rise to four main conclusions. Firstly, variation in individual quality plays a central role in shaping breeding strategies. Secondly, kinship plays a central role in the evolution of CBP. Thirdly, egg recognition ability may affect the prevalence of parasitism. If egg recognition is perfect, higher relatedness between host and parasite facilitates CBP. Finally, I show that the relative costs of egg laying and post-laying care play a so far underestimated role in determining the prevalence of parasitism. The costs of breeding may outweigh possible inclusive fitness benefits accrued from receiving eggs from relatives. Several of the patterns brought out by the theoretical work are then confirmed empirically in the following chapters. Findings include confirmation of the central role of relatedness in determining the extent of parasitism as well as inducing a counterintuitive host clutch reduction. Furthermore, I demonstrate a cost of CBP inflicted on hosts, as well as results suggesting that host age reflects individual quality, affecting the ability to overcome costs inflicted by CBP. In summary, I demonstrate both theoretically and empirically the presence of cooperation and conflict in the interactions between conspecific parasites and their hosts. The field of CBP research has traditionally been divided, but the first steps have now been taken toward the acceptance of the opposite side of the divide. Especially the theoretical findings of chapter 1 offer the possibility to view seemingly contrasting results of various studies within the same framework, and may direct future research toward more general features underlying differences in the patterns of CBP between populations or species.

New approaches to improve the cord blood unit hematopoietic progenitor cell content

Cord blood is a well-established alternative to bone marrow and peripheral blood stem cell transplantation. To this day, over 400 000 unrelated donor cord blood units have been stored in cord blood banks worldwide. To enable successful cord blood transplantation, recent efforts have been focused on finding ways to increase the hematopoietic progenitor cell content of cord blood units. In this study, factors that may improve the selection and quality of cord blood collections for banking were identified. In 167 consecutive cord blood units collected from healthy full-term neonates and processed at a national cord blood bank, mean platelet volume (MPV) correlated with the numbers of cord blood unit hematopoietic progenitors (CD34+ cells and colony-forming units); this is a novel finding. Mean platelet volume can be thought to represent general hematopoietic activity, as newly formed platelets have been reported to be large. Stress during delivery is hypothesized to lead to the mobilization of hematopoietic progenitor cells through cytokine stimulation. Accordingly, low-normal umbilical arterial pH, thought to be associated with perinatal stress, correlated with high cord blood unit CD34+ cell and colony-forming unit numbers. The associations were closer in vaginal deliveries than in Cesarean sections. Vaginal delivery entails specific physiological changes, which may also affect the hematopoietic system. Thus, different factors may predict cord blood hematopoietic progenitor cell numbers in the two modes of delivery. Theoretical models were created to enable the use of platelet characteristics (mean platelet volume) and perinatal factors (umbilical arterial pH and placental weight) in the selection of cord blood collections with high hematopoietic progenitor cell counts. These observations could thus be implemented as a part of the evaluation of cord blood collections for banking. The quality of cord blood units has been the focus of several recent studies. However, hemostasis activation during cord blood collection is scarcely evaluated in cord blood banks. In this study, hemostasis activation was assessed with prothrombin activation fragment 1+2 (F1+2), a direct indicator of thrombin generation, and platelet factor 4 (PF4), indicating platelet activation. Altogether three sample series were collected during the set-up of the cord blood bank as well as after changes in personnel and collection equipment. The activation decreased from the first to the subsequent series, which were collected with the bank fully in operation and following international standards, and was at a level similar to that previously reported for healthy neonates. As hemostasis activation may have unwanted effects on cord blood cell contents, it should be minimized. The assessment of hemostasis activation could be implemented as a part of process control in cord blood banks. Culture assays provide information about the hematopoietic potential of the cord blood unit. In processed cord blood units prior to freezing, megakaryocytic colony growth was evaluated in semisolid cultures with a novel scoring system. Three investigators analyzed the colony assays, and the scores were highly concordant. With such scoring systems, the growth potential of various cord blood cell lineages can be assessed. In addition, erythroid cells were observed in liquid cultures of cryostored and thawed, unseparated cord blood units without exogenous erythropoietin. This was hypothesized to be due to the erythropoietic effect of thrombopoietin, endogenous erythropoietin production, and diverse cell-cell interactions in the culture. This observation underscores the complex interactions of cytokines and supporting cells in the heterogeneous cell population of the thawed cord blood unit.

Numerical approaches to new particle formation and growth in the atmosphere

Aerosols impact the planet and our daily lives through various effects, perhaps most notably those related to their climatic and health-related consequences. While there are several primary particle sources, secondary new particle formation from precursor vapors is also known to be a frequent, global phenomenon. Nevertheless, the formation mechanism of new particles, as well as the vapors participating in the process, remain a mystery. This thesis consists of studies on new particle formation specifically from the point of view of numerical modeling. A dependence of formation rate of 3 nm particles on the sulphuric acid concentration to the power of 1-2 has been observed. This suggests nucleation mechanism to be of first or second order with respect to the sulphuric acid concentration, in other words the mechanisms based on activation or kinetic collision of clusters. However, model studies have had difficulties in replicating the small exponents observed in nature. The work done in this thesis indicates that the exponents may be lowered by the participation of a co-condensing (and potentially nucleating) low-volatility organic vapor, or by increasing the assumed size of the critical clusters. On the other hand, the presented new and more accurate method for determining the exponent indicates high diurnal variability. Additionally, these studies included several semi-empirical nucleation rate parameterizations as well as a detailed investigation of the analysis used to determine the apparent particle formation rate. Due to their high proportion of the earth's surface area, oceans could potentially prove to be climatically significant sources of secondary particles. In the lack of marine observation data, new particle formation events in a coastal region were parameterized and studied. Since the formation mechanism is believed to be similar, the new parameterization was applied in a marine scenario. The work showed that marine CCN production is feasible in the presence of additional vapors contributing to particle growth. Finally, a new method to estimate concentrations of condensing organics was developed. The algorithm utilizes a Markov chain Monte Carlo method to determine the required combination of vapor concentrations by comparing a measured particle size distribution with one from an aerosol dynamics process model. The evaluation indicated excellent agreement against model data, and initial results with field data appear sound as well.

E-learning in a rural context: Alternative media and contemporary applications

This report has been written as part of the E-ruralnet –project that addresses e-learning as a means for enhancing lifelong learning opportunities in rural areas, with emphasis on SMEs, micro-enterprises, self-employed and persons seeking employment. E-ruralnet is a European network project part-funded by the European Commission in the context of the Lifelong Learning Programme, Transversal projects-ICT. This report aims to address two issues identified as requiring attention in the previous Observatory study: firstly, access to e-learning for rural areas that have not adequate ICT infrastructure; and secondly new learning approaches introduced through new interactive ICT tools such as web 2.0., wikis, podcasts etc. The possibility of using alternative technology in addition to computers is examined (mobile telephones, DVDs) as well as new approaches to learning (simulation, serious games). The first part of the report examines existing literature on e-learning and what e-learning is all about. Institutional users, learners and instructors/teachers are all looked at separately. We then turn to the implementation of e-learning from the organizational point of view and focus on quality issues related to e-learning. The report includes a separate chapter or e-learning from the rural perspective since most of Europe is geographically speaking rural and the population in those areas is that which could most benefit from the possibilities introduced by the e-learning development. The section titled “Alternative media”, in accordance with the project terminology, looks at standalone technology that is of particular use to rural areas without proper internet connection. It also evaluates the use of new tools and media in e-learning and takes a look at m-learning. Finally, the use of games, serious games and simulations in learning is considered. Practical examples and cases are displayed in a box to facilitate pleasant reading.

New computational approaches for inelastic x-ray scattering

Inelastic x-ray scattering spectroscopy is a versatile experimental technique for probing the electronic structure of materials. It provides a wealth of information on the sample's atomic-scale structure, but extracting this information from the experimental data can be challenging because there is no direct relation between the structure and the measured spectrum. Theoretical calculations can bridge this gap by explaining the structural origins of the spectral features. Reliable methods for modeling inelastic x-ray scattering require accurate electronic structure calculations. This work presents the development and implementation of new schemes for modeling the inelastic scattering of x-rays from non-periodic systems. The methods are based on density functional theory and are applicable for a wide variety of molecular materials. Applications are presented in this work for amorphous silicon monoxide and several gas phase systems. Valuable new information on their structure and properties could be extracted with the combination of experimental and computational methods.