Multiwavelength studies of regolith effects in planetary remote sensing

A large proportion of our knowledge about the surfaces of atmosphereless solar-system bodies is obtained through remote-sensing measurements. The measurements can be carried out either as ground-based telescopic observations or space-based observations from orbiting spacecraft. In both cases, the measurement geometry normally varies during the observations due to the orbital motion of the target body, the spacecraft, etc.. As a result, the data are acquired over a variety of viewing and illumination angles. Surfaces of planetary bodies are usually covered with a layer of loose, broken-up rock material called the regolith whose physical properties affect the directional dependence of remote-sensed measurements. It is of utmost importance for correct interpretation of the remote-sensed data to understand the processes behind this alteration. In the thesis, the multi-angular effects that the physical properties of the regolith have on remote-sensing measurements are studied in two regimes of electromagnetic radiation, visible to near infrared and soft X-rays. These effects are here termed generally the regolith effects in remote sensing. Although the physical mechanisms that are important in these regions are largely different, notable similarities arise in the methodology that is used in the study of the regolith effects, including the characterization of the regolith both in experimental studies and in numerical simulations. Several novel experimental setups have been constructed for the thesis. Alongside the experimental work, theoretical modelling has been carried out, and results from both approaches are presented. Modelling of the directional behaviour of light scattered from a regolith is utilized to obtain shape and spin-state information of several asteroids from telescopic observations and to assess the surface roughness and single-scattering properties of lunar maria from spacecraft observations. One of the main conclusions is that the azimuthal direction is an important factor in detailed studies of planetary surfaces. In addition, even a single parameter, such as porosity, can alter the light scattering properties of a regolith significantly. Surface roughness of the regolith is found to alter the elemental fluorescence line ratios of a surface obtained through planetary soft X-ray spectrometry. The results presented in the thesis are among the first to report this phenomenon. Regolith effects need to be taken into account in the analysis of remote-sensed data, providing opportunities for retrieving physical parameters of the surface through inverse methods.

Inverse Problem for Fractional Brownian Motion with Discrete Data

The problem of recovering information from measurement data has already been studied for a long time. In the beginning, the methods were mostly empirical, but already towards the end of the sixties Backus and Gilbert started the development of mathematical methods for the interpretation of geophysical data. The problem of recovering information about a physical phenomenon from measurement data is an inverse problem. Throughout this work, the statistical inversion method is used to obtain a solution. Assuming that the measurement vector is a realization of fractional Brownian motion, the goal is to retrieve the amplitude and the Hurst parameter. We prove that under some conditions, the solution of the discretized problem coincides with the solution of the corresponding continuous problem as the number of observations tends to infinity. The measurement data is usually noisy, and we assume the data to be the sum of two vectors: the trend and the noise. Both vectors are supposed to be realizations of fractional Brownian motions, and the goal is to retrieve their parameters using the statistical inversion method. We prove a partial uniqueness of the solution. Moreover, with the support of numerical simulations, we show that in certain cases the solution is reliable and the reconstruction of the trend vector is quite accurate.

Renormalization methods in KAM theory

It is well known that an integrable (in the sense of Arnold-Jost) Hamiltonian system gives rise to quasi-periodic motion with trajectories running on invariant tori. These tori foliate the whole phase space. If we perturb an integrable system, the Kolmogorow-Arnold-Moser (KAM) theorem states that, provided some non-degeneracy condition and that the perturbation is sufficiently small, most of the invariant tori carrying quasi-periodic motion persist, getting only slightly deformed. The measure of the persisting invariant tori is large together with the inverse of the size of the perturbation. In the first part of the thesis we shall use a Renormalization Group (RG) scheme in order to prove the classical KAM result in the case of a non analytic perturbation (the latter will only be assumed to have continuous derivatives up to a sufficiently large order). We shall proceed by solving a sequence of problems in which theperturbations are analytic approximations of the original one. We will finally show that the approximate solutions will converge to a differentiable solution of our original problem. In the second part we will use an RG scheme using continuous scales, so that instead of solving an iterative equation as in the classical RG KAM, we will end up solving a partial differential equation. This will allow us to reduce the complications of treating a sequence of iterative equations to the use of the Banach fixed point theorem in a suitable Banach space.

Generation of Flat and Curved Membranes by Inverse-BAR Domain Proteins

Biological membranes are tightly linked to the evolution of life, because they provide a way to concentrate molecules into partially closed compartments. The dynamic shaping of cellular membranes is essential for many physiological processes, including cell morphogenesis, motility, cytokinesis, endocytosis, and secretion. It is therefore essential to understand the structure of the membrane and recognize the players that directly sculpt the membrane and enable it to adopt different shapes. The actin cytoskeleton provides the force to push eukaryotic plasma membrane in order to form different protrusions or/and invaginations. It has now became evident that actin directly co-operates with many membrane sculptors, including BAR domain proteins, in these important events. However, the molecular mechanisms behind BAR domain function and the differences between the members of this large protein family remain largely unresolved. In this thesis, the structure and functions of the I-BAR domain family members IRSp53 and MIM were thoroughly analyzed. By using several methods such as electron microscopy and systematic mutagenesis, we showed that these I-BAR domain proteins bind to PI(4,5)P2-rich membranes, generate negative membrane curvature and are involved in the formation of plasma membrane protrusions in cells e.g. filopodia. Importantly, we characterized a novel member of the BAR-domain superfamily which we named Pinkbar. We revealed that Pinkbar is specifically expressed in kidney and epithelial cells, and it localizes to Rab13-positive vesicles in intestinal epithelial cells. Remarkably, we learned that the I-BAR domain of Pinkbar does not generate membrane curvature but instead stabilizes planar membranes. Based on structural, mutagenesis and biochemical work we present a model for the mechanism of the novel membrane deforming activity of Pinkbar. Collectively, this work describes the mechanism by which I-BAR domain proteins deform membranes and provides new information about the biological roles of these proteins. Intriguingly, this work also gives evidence that significant functional plasticity exists within the I-BAR domain family. I-BAR proteins can either generate negative membrane curvature or stabilize planar membrane sheets, depending on the specific structural properties of their I-BAR domains. The results presented in this thesis expand our knowledge on membrane sculpting mechanisms and shows for the first time how flat membranes can be generated in cells.

Novel Mass Spectrometric Analysis Methods for Anabolic Androgenic Steroids in Sports Drug Testing

The feasibility of different modern analytical techniques for the mass spectrometric detection of anabolic androgenic steroids (AAS) in human urine was examined in order to enhance the prevalent analytics and to find reasonable strategies for effective sports drug testing. A comparative study of the sensitivity and specificity between gas chromatography (GC) combined with low (LRMS) and high resolution mass spectrometry (HRMS) in screening of AAS was carried out with four metabolites of methandienone. Measurements were done in selected ion monitoring mode with HRMS using a mass resolution of 5000. With HRMS the detection limits were considerably lower than with LRMS, enabling detection of steroids at low 0.2-0.5 ng/ml levels. However, also with HRMS, the biological background hampered the detection of some steroids. The applicability of liquid-phase microextraction (LPME) was studied with metabolites of fluoxymesterone, 4-chlorodehydromethyltestosterone, stanozolol and danazol. Factors affecting the extraction process were studied and a novel LPME method with in-fiber silylation was developed and validated for GC/MS analysis of the danazol metabolite. The method allowed precise, selective and sensitive analysis of the metabolite and enabled simultaneous filtration, extraction, enrichment and derivatization of the analyte from urine without any other steps in sample preparation. Liquid chromatographic/tandem mass spectrometric (LC/MS/MS) methods utilizing electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI) were developed and applied for detection of oxandrolone and metabolites of stanozolol and 4-chlorodehydromethyltestosterone in urine. All methods exhibited high sensitivity and specificity. ESI showed, however, the best applicability, and a LC/ESI-MS/MS method for routine screening of nine 17-alkyl-substituted AAS was thus developed enabling fast and precise measurement of all analytes with detection limits below 2 ng/ml. The potential of chemometrics to resolve complex GC/MS data was demonstrated with samples prepared for AAS screening. Acquired full scan spectral data (m/z 40-700) were processed by the OSCAR algorithm (Optimization by Stepwise Constraints of Alternating Regression). The deconvolution process was able to dig out from a GC/MS run more than the double number of components as compared with the number of visible chromatographic peaks. Severely overlapping components, as well as components hidden in the chromatographic background could be isolated successfully. All studied techniques proved to be useful analytical tools to improve detection of AAS in urine. Superiority of different procedures is, however, compound-dependent and different techniques complement each other.

Univariate, bivariate, and multivariate methods in corpus-based lexicography : A study of synonymy

In this dissertation, I present an overall methodological framework for studying linguistic alternations, focusing specifically on lexical variation in denoting a single meaning, that is, synonymy. As the practical example, I employ the synonymous set of the four most common Finnish verbs denoting THINK, namely ajatella, miettiä, pohtia and harkita ‘think, reflect, ponder, consider’. As a continuation to previous work, I describe in considerable detail the extension of statistical methods from dichotomous linguistic settings (e.g., Gries 2003; Bresnan et al. 2007) to polytomous ones, that is, concerning more than two possible alternative outcomes. The applied statistical methods are arranged into a succession of stages with increasing complexity, proceeding from univariate via bivariate to multivariate techniques in the end. As the central multivariate method, I argue for the use of polytomous logistic regression and demonstrate its practical implementation to the studied phenomenon, thus extending the work by Bresnan et al. (2007), who applied simple (binary) logistic regression to a dichotomous structural alternation in English. The results of the various statistical analyses confirm that a wide range of contextual features across different categories are indeed associated with the use and selection of the selected think lexemes; however, a substantial part of these features are not exemplified in current Finnish lexicographical descriptions. The multivariate analysis results indicate that the semantic classifications of syntactic argument types are on the average the most distinctive feature category, followed by overall semantic characterizations of the verb chains, and then syntactic argument types alone, with morphological features pertaining to the verb chain and extra-linguistic features relegated to the last position. In terms of overall performance of the multivariate analysis and modeling, the prediction accuracy seems to reach a ceiling at a Recall rate of roughly two-thirds of the sentences in the research corpus. The analysis of these results suggests a limit to what can be explained and determined within the immediate sentential context and applying the conventional descriptive and analytical apparatus based on currently available linguistic theories and models. The results also support Bresnan’s (2007) and others’ (e.g., Bod et al. 2003) probabilistic view of the relationship between linguistic usage and the underlying linguistic system, in which only a minority of linguistic choices are categorical, given the known context – represented as a feature cluster – that can be analytically grasped and identified. Instead, most contexts exhibit degrees of variation as to their outcomes, resulting in proportionate choices over longer stretches of usage in texts or speech.

Genotyping for genetic association studies: Methods and applications

In this thesis, two separate single nucleotide polymorphism (SNP) genotyping techniques were set up at the Finnish Genome Center, pooled genotyping was evaluated as a screening method for large-scale association studies, and finally, the former approaches were used to identify genetic factors predisposing to two distinct complex diseases by utilizing large epidemiological cohorts and also taking environmental factors into account. The first genotyping platform was based on traditional but improved restriction-fragment-length-polymorphism (RFLP) utilizing 384-microtiter well plates, multiplexing, small reaction volumes (5 µl), and automated genotype calling. We participated in the development of the second genotyping method, based on single nucleotide primer extension (SNuPeTM by Amersham Biosciences), by carrying out the alpha- and beta tests for the chemistry and the allele-calling software. Both techniques proved to be accurate, reliable, and suitable for projects with thousands of samples and tens of markers. Pooled genotyping (genotyping of pooled instead of individual DNA samples) was evaluated with Sequenom s MassArray MALDI-TOF, in addition to SNuPeTM and PCR-RFLP techniques. We used MassArray mainly as a point of comparison, because it is known to be well suited for pooled genotyping. All three methods were shown to be accurate, the standard deviations between measurements being 0.017 for the MassArray, 0.022 for the PCR-RFLP, and 0.026 for the SNuPeTM. The largest source of error in the process of pooled genotyping was shown to be the volumetric error, i.e., the preparation of pools. We also demonstrated that it would have been possible to narrow down the genetic locus underlying congenital chloride diarrhea (CLD), an autosomal recessive disorder, by using the pooling technique instead of genotyping individual samples. Although the approach seems to be well suited for traditional case-control studies, it is difficult to apply if any kind of stratification based on environmental factors is needed. Therefore we chose to continue with individual genotyping in the following association studies. Samples in the two separate large epidemiological cohorts were genotyped with the PCR-RFLP and SNuPeTM techniques. The first of these association studies concerned various pregnancy complications among 100,000 consecutive pregnancies in Finland, of which we genotyped 2292 patients and controls, in addition to a population sample of 644 blood donors, with 7 polymorphisms in the potentially thrombotic genes. In this thesis, the analysis of a sub-study of pregnancy-related venous thromboses was included. We showed that the impact of factor V Leiden polymorphism on pregnancy-related venous thrombosis, but not the other tested polymorphisms, was fairly large (odds ratio 11.6; 95% CI 3.6-33.6), and increased multiplicatively when combined with other risk factors such as obesity or advanced age. Owing to our study design, we were also able to estimate the risks at the population level. The second epidemiological cohort was the Helsinki Birth Cohort of men and women who were born during 1924-1933 in Helsinki. The aim was to identify genetic factors that might modify the well known link between small birth size and adult metabolic diseases, such as type 2 diabetes and impaired glucose tolerance. Among ~500 individuals with detailed birth measurements and current metabolic profile, we found that an insertion/deletion polymorphism of the angiotensin converting enzyme (ACE) gene was associated with the duration of gestation, and weight and length at birth. Interestingly, the ACE insertion allele was also associated with higher indices of insulin secretion (p=0.0004) in adult life, but only among individuals who were born small (those among the lowest third of birth weight). Likewise, low birth weight was associated with higher indices of insulin secretion (p=0.003), but only among carriers of the ACE insertion allele. The association with birth measurements was also found with a common haplotype of the glucocorticoid receptor (GR) gene. Furthermore, the association between short length at birth and adult impaired glucose tolerance was confined to carriers of this haplotype (p=0.007). These associations exemplify the interaction between environmental factors and genotype, which, possibly due to altered gene expression, predisposes to complex metabolic diseases. Indeed, we showed that the common GR gene haplotype associated with reduced mRNA expression in thymus of three individuals (p=0.0002).

Variation in tracheid cross-sectional dimensions and wood viscoelasticity extent and control methods

Printing papers have been the main product of the Finnish paper industry. To improve properties and economy of printing papers, controlling of tracheid cross-sectional dimensions and wood viscoelasticity are examined in this study. Controlling is understood as any procedure which yields raw material classes with distinct properties and small internal variation. Tracheid cross-sectional dimensions, i.e., cell wall thickness and radial and tangential diameters can be controlled with methods such as sorting wood into pulpwood and sawmill chips, sorting of logs according to tree social status and fractionation of fibres. These control methods were analysed in this study with simulations, which were based on measured tracheid cross-sectional dimensions. A SilviScan device was used to measure the data set from five Norway spruce (Picea abies) and five Scots pine (Pinus sylvestris) trunks. The simulation results indicate that the sawmill chips and top pulpwood assortments have quite similar cross-sectional dimensions. Norway spruce and Scots pine are on average also relatively similar in their cross-sectional dimensions. The distributions of these species are somewhat different, but from a practical point of view, the differences are probably of minor importance. The controlling of tracheid cross-sectional dimensions can be done most efficiently with methods that can separate fibres into earlywood and latewood. Sorting of logs or partitioning of logs into juvenile and mature wood were markedly less efficient control methods than fractionation of fibres. Wood viscoelasticity affects energy consumption in mechanical pulping, and is thus an interesting control target when improving energy efficiency of the process. A literature study was made to evaluate the possibility of using viscoelasticity in controlling. The study indicates that there is considerable variation in viscoelastic properties within tree species, but unfortunately, the viscoelastic properties of important raw material lots such as top pulpwood or sawmill chips are not known. Viscoelastic properties of wood depend mainly on lignin, but also on microfibrillar angle, width of cellulose crystals and tracheid cross-sectional dimensions.

From a tree to a stand in Finnish boreal forests: biomass estimation and comparison of methods

There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61º50' N, 24º22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg/yr for understorey spruce to 7 kg/yr for dominant pine) when the trees were 100 years old. Tree biomass was estimated to be about 70 Mg/ha in Young-Stand and about 220 Mg/ha in Mature-Stand. In the region (58.00-62.13 ºN, 14-34 ºE, ≤ 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg/ha at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg/ha with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg/ha. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach.

Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data

This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.