Econometric models of Finnish non-industrial private forest owners' timber supply and timber stock

This dissertation examines the short- and long-run impacts of timber prices and other factors affecting NIPF owners' timber harvesting and timber stocking decisions. The utility-based Faustmann model provides testable hypotheses of the exogenous variables retained in the timber supply analysis. The timber stock function, derived from a two-period biomass harvesting model, is estimated using a two-step GMM estimator based on balanced panel data from 1983 to 1991. Timber supply functions are estimated using a Tobit model adjusted for heteroscedasticity and nonnormality of errors based on panel data from 1994 to 1998. Results show that if specification analysis of the Tobit model is ignored, inconsistency and biasedness can have a marked effect on parameter estimates. The empirical results show that owner's age is the single most important factor determining timber stock; timber price is the single most important factor in harvesting decision. The results of the timber supply estimations can be interpreted using utility-based Faustmann model of a forest owner who values a growing timber in situ.

Deformation and stability regression models for soil nail walls

Lateral displacement and global stability are the two main stability criteria for soil nail walls. Conventional design methods do not adequately address the deformation behaviour of soil nail walls, owing to the complexity involved in handling a large number of influencing factors. Consequently, limited methods of deformation estimates based on empirical relationships and in situ performance monitoring are available in the literature. It is therefore desirable that numerical techniques and statistical methods are used in order to gain a better insight into the deformation behaviour of soil nail walls. In the present study numerical experiments are conducted using a 2 4 factorial design method. Based on analysis of the maximum lateral deformation and factor-of-safety observations from the numerical experiments, regression models for maximum lateral deformation and factor-of-safety prediction are developed and checked for adequacy. Selection of suitable design factors for the 2 4 factorial design of numerical experiments enabled the use of the proposed regression models over a practical range of soil nail wall heights and in situ soil variability. It is evident from the model adequacy analyses and illustrative example that the proposed regression models provided a reasonably good estimate of the lateral deformation and global factor of safety of the soil nail walls.

Death pathways activated in the neurotrophic factor-deprived neurons

Programed cell death (PCD) is a fundamental biological process that is as essential for the development and tissue homeostasis as cell proliferation, differentiation and adaptation. The main mode of PCD - apoptosis - occurs via specifi c pathways, such as mitochondrial or death receptor pathway. In the developing nervous system, programed death broadly occurs, mainly triggered by the defi ciency of different survival-promoting neurotrophic factors, but the respective death pathways are poorly studied. In one of the best-characterized models, sympathetic neurons deprived of nerve growth factor (NGF) die via the classical mitochondrial apoptotic pathway. The main aim of this study was to describe the death programs activated in these and other neuronal populations by using neuronal cultures deprived of other neurotrophic factors. First, this study showed that the cultured sympathetic neurons deprived of glial cell line-derived neurotrophic factor (GDNF) die via a novel non-classical death pathway, in which mitochondria and death receptors are not involved. Indeed, cytochrome c was not released into the cytosol, Bax, caspase-9, and caspase-3 were not involved, and Bcl-xL overexpression did not prevent the death. This pathway involved activation of mixed lineage kinases and c-jun, and crucially requires caspase-2 and -7. Second, it was shown that deprivation of neurotrophin-3 (NT-3) from cultured sensory neurons of the dorsal root ganglia kills them via a dependence receptor pathway, including cleavage of the NT- 3 receptor TrkC and liberation of a pro-apoptotic dependence domain. Indeed, death of NT-3-deprived neurons was blocked by a dominant-negative construct interfering with TrkC cleavage. Also, the uncleavable mutant of TrkC, replacing the siRNA-silenced endogeneous TrkC, was not able to trigger death upon NT-3 removal. Such a pathway was not activated in another subpopulation of sensory neurons deprived of NGF. Third, it was shown that cultured midbrain dopaminergic neurons deprived of GDNF or brainderived neurotrophic factor (BDNF) kills them by still a different pathway, in which death receptors and caspases, but not mitochondria, are activated. Indeed, cytochrome c was not released into the cytosol, Bax was not activated, and Bcl-xL did not block the death, but caspases were necessary for the death of these neurons. Blocking the components of the death receptor pathway - caspase-8, FADD, or Fas - blocked the death, whereas activation of Fas accelerated it. The activity of Fas in the dopaminergic neurons could be controlled by the apoptosis inhibitory molecule FAIML. For these studies we developed a novel assay to study apoptosis in the transfected dopaminergic neurons. Thus, a novel death pathway, characteristic for the dopaminergic neurons was described. The study suggests death receptors as possible targets for the treatment of Parkinson s disease, which is caused by the degeneration of dopaminergic neurons.

Transforming growth factor -beta signaling through Smad3 in allergy : Studies in the mechanisms of asthma, atopic dermatitis and allergic contact reactions

Transforming growth factor β signalling through Smad3 in allergy Allergic diseases, such as atopic dermatitis, asthma, and contact dermatitis are complex diseases influenced by both genetic and environmental factors. It is still unclear why allergy and subsequent allergic disease occur in some individuals but not in others. Transforming growth factor (TGF)-β is an important immunomodulatory and fibrogenic factor that regulates cellular processes in injured and inflamed skin. TGF-β has a significant role in the regulation of the allergen-induced immune response participating in the development of allergic and asthmatic inflammation. TGF-β is known to be an immunomodulatory factor in the progression of delayed type hypersensitivity reactions and allergic contact dermatitis. TGF-β is crucial in regulating the cellular responses involved in allergy, such as differentiation, proliferation and migration. TGF-β signals are delivered from the cytoplasm to the nucleus by TGF-β signal transducers called Smads. Smad3 is a major signal transducer in TGF-β -signalling that controls the expression of target genes in the nucleus in a cell-type specific manner. The role of TGF-β-Smad3 -signalling in the immunoregulation and pathophysiology of allergic disorders is still poorly understood. In this thesis, the role of TGF-β-Smad -signalling pathway using Smad3 -deficient knock out mice in the murine models of allergic diseases; atopic dermatitis, asthma and allergic contact reactions, was examined. Smad3-pathway regulates allergen induced skin inflammation and systemic IgE antibody production in a murine model atopic dermatitis. The defect in Smad3 -signalling decreased Th2 cytokine (IL-13 and IL-5) mRNA expression in the lung, modulated allergen induced specific IgG1 response, and affected mucus production in the lung in a murine model of asthma. TGF-β / Smad3 -signalling contributed to inflammatory hypersensitivity reactions and disease progression via modulation of chemokine and cytokine expression and inflammatory cell recruitment, cell proliferation and regulation of the specific antibody response in a murine model of contact hypersensitivity. TGF-β modulates inflammatory responses - at least partly through the Smad3 pathway - but also through other compensatory, non-Smad-dependent pathways. Understanding the effects of the TGF-β signalling pathway in the immune system and in disease models can help in elucidating the multilevel effects of TGF-β. Unravelling the mechanisms of Smad3 may open new possibilities for treating and preventing allergic responses, which may lead to severe illness and loss of work ability. In the future the Smad3 signalling pathway might be a potential target in the therapy of allergic diseases.

Part I: Enzyme replacement versus neurotrophic factor viral vector-mediated gene therapy of Parkinson’s disease, Part II: The effects of orally dosed tolcapone and entacapone on dopamine metabolism in the dorsal striatum and nucleus accumbens in rats

Part I: Parkinson’s disease is a slowly progressive neurodegenerative disorder in which particularly the dopaminergic neurons of the substantia nigra pars compacta degenerate and die. Current conventional treatment is based on restraining symptoms but it has no effect on the progression of the disease. Gene therapy research has focused on the possibility of restoring the lost brain function by at least two means: substitution of critical enzymes needed for the synthesis of dopamine and slowing down the progression of the disease by supporting the functions of the remaining nigral dopaminergic neurons by neurotrophic factors. The striatal levels of enzymes such as tyrosine hydroxylase, dopadecarboxylase and GTP-CH1 are decreased as the disease progresses. By replacing one or all of the enzymes, dopamine levels in the striatum may be restored to normal and behavioral impairments caused by the disease may be ameliorated especially in the later stages of the disease. The neurotrophic factors glial cell derived neurotrophic factor (GDNF) and neurturin have shown to protect and restore functions of dopaminergic cell somas and terminals as well as improve behavior in animal lesion models. This therapy may be best suited at the early stages of the disease when there are more dopaminergic neurons for neurotrophic factors to reach. Viral vector-mediated gene transfer provides a tool to deliver proteins with complex structures into specific brain locations and provides long-term protein over-expression. Part II: The aim of our study was to investigate the effects of two orally dosed COMT inhibitors entacapone (10 and 30 mg/kg) and tolcapone (10 and 30 mg/kg) with a subsequent administration of a peripheral dopadecarboxylase inhibitor carbidopa (30 mg/kg) and L- dopa (30 mg/kg) on dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens of freely moving rats using dual-probe in vivo microdialysis. Earlier similarly designed studies have only been conducted in the dorsal striatum. We also confirmed the result of earlier ex vivo studies regarding the effects of intraperitoneally dosed tolcapone (30 mg/kg) and entacapone (30 mg/kg) on striatal and hepatic COMT activity. The results obtained from the dorsal striatum were generally in line with earlier studies, where tolcapone tended to increase dopamine and DOPAC levels and decrease HVA levels. Entacapone tended to keep striatal dopamine and HVA levels elevated longer than in controls and also tended to elevate the levels of DOPAC. Surprisingly in the nucleus accumbens, dopamine levels after either dose of entacapone or tolcapone were not elevated. Accumbal DOPAC levels, especially in the tolcapone 30 mg/kg group, were elevated nearly to the same extent as measured in the dorsal striatum. Entacapone 10 mg/kg elevated accumbal HVA levels more than the dose of 30 mg/kg and the effect was more pronounced in the nucleus accumbens than in the dorsal striatum. This suggests that entacapone 30 mg/kg has minor central effects. Also our ex vivo study results obtained from the dorsal striatum suggest that entacapone 30 mg/kg has minor and transient central effects, even though central HVA levels were not suppressed below those of the control group in either brain area in the microdialysis study. Both entacapone and tolcapone suppressed hepatic COMT activity more than striatal COMT activity. Tolcapone was more effective than entacapone in the dorsal striatum. The differences between dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens may be due to different properties of the two brain areas.

Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

Nonsingular cosmological models: the massive scalar field case

The nonminimal coupling of a massive self-interacting scalar field with a gravitational field is studied. Spontaneous symmetry breaking occurs in the open universe even when the sign on the mass term is positive. In contrast to grand unified theories, symmetry breakdown is more important for the early universe and it is restored only in the limit of an infinite expansion. Symmetry breakdown is shown to occur in flat and closed universes when the mass term carries a wrong sign. The model has a naturally defined effective gravitational coupling coefficient which is rendered time-dependent due to the novel symmetry breakdown. It changes sign below a critical value of the cosmic scale factor indicating the onset of a repulsive field. The presence of the mass term severely alters the behaviour of ordinary matter and radiation in the early universe. The total energy density becomes negative in a certain domain. These features make possible a nonsingular cosm

Mammalian Mat1 subunit of Transcription Factor IIH in gene-specific and general transcription

All protein-encoding genes in eukaryotes are transcribed into messenger RNA (mRNA) by RNA Polymerase II (RNAP II), whose activity therefore needs to be tightly controlled. An important and only partially understood level of regulation is the multiple phosphorylations of RNAP II large subunit C-terminal domain (CTD). Sequential phosphorylations regulate transcription initiation and elongation, and recruit factors involved in co-transcriptional processing of mRNA. Based largely on studies in yeast models and in vitro, the kinase activity responsible for the phosphorylation of the serine-5 (Ser5) residues of RNAP II CTD has been attributed to the Mat1/Cdk7/CycH trimer as part of Transcription Factor IIH. However, due to the lack of good mammalian genetic models, the roles of both RNAP II Ser5 phosphorylation as well as TFIIH kinase in transcription have provided ambiguous results and the in vivo kinase of Ser5 has remained elusive. The primary objective of this study was to elucidate the role of mammalian TFIIH, and specifically the Mat1 subunit in CTD phosphorylation and general RNAP II-mediated transcription. The approach utilized the Cre-LoxP system to conditionally delete murine Mat1 in cardiomyocytes and hepatocytes in vivo and and in cell culture models. The results identify the TFIIH kinase as the major mammalian Ser5 kinase and demonstrate its requirement for general transcription, noted by the use of nascent mRNA labeling. Also a role for Mat1 in regulating general mRNA turnover was identified, providing a possible rationale for earlier negative findings. A secondary objective was to identify potential gene- and tissue-specific roles of Mat1 and the TFIIH kinase through the use of tissue-specific Mat1 deletion. Mat1 was found to be required for the transcriptional function of PGC-1 in cardiomyocytes. Transriptional activation of lipogenic SREBP1 target genes following Mat1 deletion in hepatocytes revealed a repressive role for Mat1apparently mediated via co-repressor DMAP1 and the DNA methyltransferase Dnmt1. Finally, Mat1 and Cdk7 were also identified as a negative regulators of adipocyte differentiation through the inhibitory phosphorylation of Peroxisome proliferator-activated receptor (PPAR) γ. Together, these results demonstrate gene- and tissue-specific roles for the Mat1 subunit of TFIIH and open up new therapeutic possibilities in the treatment of diseases such as type II diabetes, hepatosteatosis and obesity.

Assessment of conditional moment closure models of turbulent autoignition using DNS data

A systematic assessment of the submodels of conditional moment closure (CMC) formalism for the autoignition problem is carried out using direct numerical simulation (DNS) data. An initially non-premixed, n-heptane/air system, subjected to a three-dimensional, homogeneous, isotropic, and decaying turbulence, is considered. Two kinetic schemes, (1) a one-step and (2) a reduced four-step reaction mechanism, are considered for chemistry An alternative formulation is developed for closure of the mean chemical source term , based on the condition that the instantaneous fluctuation of excess temperature is small. With this model, it is shown that the CMC equations describe the autoignition process all the way up to near the equilibrium limit. The effect of second-order terms (namely, conditional variance of temperature excess sigma(2) and conditional correlations of species q(ij)) in modeling is examined. Comparison with DNS data shows that sigma(2) has little effect on the predicted conditional mean temperature evolution, if the average conditional scalar dissipation rate is properly modeled. Using DNS data, a correction factor is introduced in the modeling of nonlinear terms to include the effect of species fluctuations. Computations including such a correction factor show that the species conditional correlations q(ij) have little effect on model predictions with a one-step reaction, but those q(ij) involving intermediate species are found to be crucial when four-step reduced kinetics is considered. The "most reactive mixture fraction" is found to vary with time when a four-step kinetics is considered. First-order CMC results are found to be qualitatively wrong if the conditional mean scalar dissipation rate is not modeled properly. The autoignition delay time predicted by the CMC model compares excellently with DNS results and shows a trend similar to experimental data over a range of initial temperatures.

Insulin Growth Factor-2 Binding Protein 3 (IGF2BP3) Is a Glioblastoma-specific Marker That Activates Phosphatidylinositol 3-Kinase/Mitogen-activated Protein Kinase (PI3K/MAPK) Pathways by Modulating IGF-2

Glioblastoma is the most common and malignant form of primary astrocytoma. Upon investigation of the insulin-like growth factor (IGF) pathway, we found the IGF2BP3/IMP3 transcript and protein to be up-regulated in GBMs but not in lower grade astrocytomas (p<0.0001). IMP3 is an RNA binding protein known to bind to the 5'-untranslated region of IGF-2 mRNA, thereby activating its translation. Overexpression-and knockdown-based studies establish a role for IMP3 in promoting proliferation, anchorage-independent growth, invasion, and chemoresistance. IMP3 overexpressing B16F10 cells also showed increased tumor growth, angiogenesis, and metastasis, resulting in poor survival in a mouse model. Additionally, the infiltrating front, perivascular, and subpial regions in a majority of the GBMs stained positive for IMP3. Furthermore, two different murine glioma models were used to substantiate the above findings. In agreement with the translation activation functions of IMP3, we also found increased IGF-2 protein in the GBM tumor samples without a corresponding increase in its transcript levels. Also, in vitro IMP3 overexpression/knockdown modulated the IGF-2 protein levels without altering its transcript levels. Additionally, IGF-2 neutralization and supplementation studies established that the proproliferative effects of IMP3 were indeed mediated through IGF-2. Concordantly, PI3K and MAPK, the downstream effectors of IGF-2, are activated by IMP3 and are found to be essential for IMP3-induced cell proliferation. Thus, we have identified IMP3 as a GBM-specific proproliferative and proinvasive marker acting through IGF-2 resulting in the activation of oncogenic PI3K and MAPK pathways.

Low-Complexity Detection in Large-Dimension MIMO-ISI Channels Using Graphical Models

In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models. A key contribution in the paper is the demonstration that near-optimal performance in MIMO-ISI channels with large dimensions can be achieved at low complexities through simple yet effective simplifications/approximations, although the graphical models that represent MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1) use of Markov random field (MRF)-based graphical model with pairwise interaction, in conjunction with message damping, and 2) use of factor graph (FG)-based graphical model with Gaussian approximation of interference (GAI). The per-symbol complexities are O(K(2)n(t)(2)) and O(Kn(t)) for the MRF and the FG with GAI approaches, respectively, where K and n(t) denote the number of channel uses per frame, and number of transmit antennas, respectively. These low-complexities are quite attractive for large dimensions, i.e., for large Kn(t). From a performance perspective, these algorithms are even more interesting in large-dimensions since they achieve increasingly closer to optimum detection performance for increasing Kn(t). Also, we show that these message passing algorithms can be used in an iterative manner with local neighborhood search algorithms to improve the reliability/performance of M-QAM symbol detection.

Spacelike pion form factor from analytic continuation and the onset of perturbative QCD

The factorization theorem for exclusive processes in perturbative QCD predicts the behavior of the pion electromagnetic form factor F(t) at asymptotic spacelike momenta t(= -Q(2)) < 0. We address the question of the onset energy using a suitable mathematical framework of analytic continuation, which uses as input the phase of the form factor below the first inelastic threshold, known with great precision through the Fermi-Watson theorem from pi pi elastic scattering, and the modulus measured from threshold up to 3 GeV by the BABAR Collaboration. The method leads to almost model-independent upper and lower bounds on the spacelike form factor. Further inclusion of the value of the charge radius and the experimental value at -2.45 GeV2 measured at JLab considerably increases the strength of the bounds in the region Q(2) less than or similar to 10 GeV2, excluding the onset of the asymptotic perturbative QCD regime for Q(2) < 7 GeV2. We also compare the bounds with available experimental data and with several theoretical models proposed for the low and intermediate spacelike region.

Factor graph based joint detection/decoding for LDPC coded large-MIMO systems

In this paper, we employ message passing algorithms over graphical models to jointly detect and decode symbols transmitted over large multiple-input multiple-output (MIMO) channels with low density parity check (LDPC) coded bits. We adopt a factor graph based technique to integrate the detection and decoding operations. A Gaussian approximation of spatial interference is used for detection. This serves as a low complexity joint detection/decoding approach for large dimensional MIMO systems coded with LDPC codes of large block lengths. This joint processing achieves significantly better performance than the individual detection and decoding scheme.

Models for the estimation of life of stator insulation in large rotating machines

Epoxy resin bonded mica splitting is the insulation of choice for machine stators. However, this system is seen to be relatively weak under time varying mechanical stress, in particular the vibration causing delamination of mica and deboning of mica from the resin matrix. The situation is accentuated under the combined action of electrical, thermal and mechanical stress. Physical and probabilistic models for failure of such systems have been proposed by one of the authors of this paper earlier. This paper presents a pragmatic accelerated failure data acquisition and analytical paradigm under multi factor coupled stress, Electrical, Thermal. The parameters of the phenomenological model so developed are estimated based on sound statistical treatment of failure data.

Evaluation of Fracture Parameters by Double-G, Double-K Models and Crack Extension Resistance for High Strength and Ultra High Strength Concrete Beams

This paper presents the advanced analytical methodologies such as Double- G and Double - K models for fracture analysis of concrete specimens made up of high strength concrete (HSC, HSC1) and ultra high strength concrete. Brief details about characterization and experimentation of HSC, HSC1 and UHSC have been provided. Double-G model is based on energy concept and couples the Griffith's brittle fracture theory with the bridging softening property of concrete. The double-K fracture model is based on stress intensity factor approach. Various fracture parameters such as cohesive fracture toughness (4), unstable fracture toughness (K-Ic(c)), unstable fracture toughness (K-Ic(un)) and initiation fracture toughness (K-Ic(ini)) have been evaluated based on linear elastic fracture mechanics and nonlinear fracture mechanics principles. Double-G and double-K method uses the secant compliance at the peak point of measured P-CMOD curves for determining the effective crack length. Bi-linear tension softening model has been employed to account for cohesive stresses ahead of the crack tip. From the studies, it is observed that the fracture parameters obtained by using double - G and double - K models are in good agreement with each other. Crack extension resistance has been estimated by using the fracture parameters obtained through double - K model. It is observed that the values of the crack extension resistance at the critical unstable point are almost equal to the values of the unstable fracture toughness K-Ic(un) of the materials. The computed fracture parameters will be useful for crack growth study, remaining life and residual strength evaluation of concrete structural components.