Toxicant distributions and impact models in environmental risk analysis of waste sites

Myrkyllisten aineiden jakaumat ja vaikutusmallit jätealueiden ympäristöriskien analyysissä.

Forest sector simulation models as methodological tools in forest policy analysis.

XVIII IUFRO World Congress, Ljubljana 1986.

Putative neuroprotective compounds in in vitro models of dopaminergic neurodegeneration

Parkinson´s disease (PD) is a debilitating age-related neurological disorder that affects various motor skills and can lead to a loss of cognitive functions. The motor symptoms are the result of the progressive degeneration of dopaminergic neurons within the substantia nigra. The factors that influence the pathogenesis and the progression of the neurodegeneration remain mostly unclear. This study investigated the role of various programmed cell death (PCD) pathways, oxidative stress, and glial cells both in dopaminergic neurodegeneration and in the protective action of various drugs. To this end, we exposed dopaminergic neuroblastoma cells (SH-SY5Y cells) to 6-OHDA, which produces oxidative stress and activates various PCD modalities that result in neuronal degeneration. Additionally, to explore the role of glia, we prepared rat midbrain primary mixed-cell cultures containing both neurons and glial cell types such as microglia and astroglia and then exposed the cultures to either MPP plus or lipopolysaccharide. Our results revealed that 6-OHDA activated several PCD pathways including apoptosis, autophagic stress, lysosomal membrane permeabilization, and perhaps paraptosis in SH-SY5Y cells. Furthermore, we found that minocycline protected SH-SY5Y cells from 6-OHDA by inhibiting both apoptotic and non-apoptotic PCD modalities. We also observed an inconsistent neuroprotective effect of various dietary anti-oxidant compounds against 6-OHDA toxicity in vitro in SH-SY5Y cells. Specifically, quercetin and curcumin exerted neuroprotection only within a narrow concentration range and a limited time frame, whereas resveratrol and epigallocatechin 3-gallate provided no protection whatsoever. Lastly, we found that molecules such as amantadine may delay or even halt the neurodegeneration in primary cell cultures by inhibiting the release of neurotoxic factors from overactivated microglia and by enhancing the pro-survival actions of astroglia. Together these data suggest that the strategy of dampening oxidative species with anti-oxidants is less effective than preventing the production of toxic factors such as oxidative and pro-inflammatory molecules by pathologically activated microglia. This would subsequently prevent the activation of various PCD modalities that cause neuronal degeneration.

Models for spin-state transitions in solids

The model for spin-state transitions described by Bari and Sivardiere (1972) is static and can be solved exactly even when the dynamics of the lattice are included; the dynamic model does not, however, show any phase transition. A coupling between the octahedra, on the other hand, leads to a phase transition in the dynamical two-sublattice displacement model. A coupling of the spin states to the cube of the sublattice displacement leads to a first-order phase transition. The most reasonable model appears to be a two-phonon model in which an ion-cage mode mixes the spin states, while a breathing mode couples to the spin states without mixing. This model explains the non-zero population of high-spin states at low temperatures, temperature-dependent variations in the inverse susceptibility and the spin-state population ratio, as well as the structural phase transitions accompanying spin-state transitions found in some systems.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Playing Games on Sets and Models

The most prominent objective of the thesis is the development of the generalized descriptive set theory, as we call it. There, we study the space of all functions from a fixed uncountable cardinal to itself, or to a finite set of size two. These correspond to generalized notions of the universal Baire space (functions from natural numbers to themselves with the product topology) and the Cantor space (functions from natural numbers to the {0,1}-set) respectively. We generalize the notion of Borel sets in three different ways and study the corresponding Borel structures with the aims of generalizing classical theorems of descriptive set theory or providing counter examples. In particular we are interested in equivalence relations on these spaces and their Borel reducibility to each other. The last chapter shows, using game-theoretic techniques, that the order of Borel equivalence relations under Borel reduciblity has very high complexity. The techniques in the above described set theoretical side of the thesis include forcing, general topological notions such as meager sets and combinatorial games of infinite length. By coding uncountable models to functions, we are able to apply the understanding of the generalized descriptive set theory to the model theory of uncountable models. The links between the theorems of model theory (including Shelah's classification theory) and the theorems in pure set theory are provided using game theoretic techniques from Ehrenfeucht-Fraïssé games in model theory to cub-games in set theory. The bottom line of the research declairs that the descriptive (set theoretic) complexity of an isomorphism relation of a first-order definable model class goes in synch with the stability theoretical complexity of the corresponding first-order theory. The first chapter of the thesis has slightly different focus and is purely concerned with a certain modification of the well known Ehrenfeucht-Fraïssé games. There we (me and my supervisor Tapani Hyttinen) answer some natural questions about that game mainly concerning determinacy and its relation to the standard EF-game

A Deterministic Optimization Approach to Protein Sequence Design Using Continuous Models

Determining the sequence of amino acid residues in a heteropolymer chain of a protein with a given conformation is a discrete combinatorial problem that is not generally amenable for gradient-based continuous optimization algorithms. In this paper we present a new approach to this problem using continuous models. In this modeling, continuous "state functions" are proposed to designate the type of each residue in the chain. Such a continuous model helps define a continuous sequence space in which a chosen criterion is optimized to find the most appropriate sequence. Searching a continuous sequence space using a deterministic optimization algorithm makes it possible to find the optimal sequences with much less computation than many other approaches. The computational efficiency of this method is further improved by combining it with a graph spectral method, which explicitly takes into account the topology of the desired conformation and also helps make the combined method more robust. The continuous modeling used here appears to have additional advantages in mimicking the folding pathways and in creating the energy landscapes that help find sequences with high stability and kinetic accessibility. To illustrate the new approach, a widely used simplifying assumption is made by considering only two types of residues: hydrophobic (H) and polar (P). Self-avoiding compact lattice models are used to validate the method with known results in the literature and data that can be practically obtained by exhaustive enumeration on a desktop computer. We also present examples of sequence design for the HP models of some real proteins, which are solved in less than five minutes on a single-processor desktop computer Some open issues and future extensions are noted.

An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models

In this paper we study representation of KL-divergence minimization, in the cases where integer sufficient statistics exists, using tools from polynomial algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. In particular, we also study the case of Kullback-Csiszar iteration scheme. We present implicit descriptions of these models and show that implicitization preserves specialization of prior distribution. This result leads us to a Grobner bases method to compute an implicit representation of minimum KL-divergence models.

Models of the proton spin structure

A phenomenological model of spin sharing by the constituents of a proton is constructed, based on the recent EMC measurement of the spin dependent structure function and knowledge of the unpolarized parton densities.

Mean-field theories of Hubbard and t-J models

We report novel results obtained for the Hubbard and t-J models by various mean-field approximations.

Approximate VB-MO schemes for excitation gaps in Hubbard models

The excitation gaps in the singlet and triplet manifolds for finite Hubbard models in one, two and three dimensions have been obtained using different approximate configuration interaction (CI) schemes, as a function of the correlation strength, by using valence bond (VB) functions constructed over the molecular orbital (MO) basis. These are compared with numerically exact results and it is found that the scheme in which all particle hole excitations below a given threshold are included is the method of choice. The excitation energies are well reproduced, in trend as well as magnitude, particularly when the threshold equals the bandwidth of the corresponding noninteracting system.

Lumettoman maan routaolojen mallintaminen ja ennustettavuus muuttuvassa ilmastossa

Raportissa on arvioitu ilmastonmuutoksen vaikutusta Suomen maaperän talviaikaiseen jäätymiseen lämpösummien perusteella. Laskelmat kuvaavat roudan paksuutta nimenomaisesti lumettomilla alueilla, esimerkiksi teillä, joilta satanut lumi aurataan pois. Luonnossa lämpöä eristävän lumipeitteen alla routaa on ohuemmin kuin tällaisilla lumettomilla alueilla. Toisaalta luonnollisessa ympäristössä paikalliset erot korostuvat johtuen mm. maalajeista ja kasvillisuudesta. Roudan paksuudet laskettiin ensin perusjakson 1971–2000 ilmasto-oloissa talviaikaisten säähavaintotietoihin pohjautuvien lämpötilojen perusteella. Sen jälkeen laskelmat toistettiin kolmelle tulevalle ajanjaksolle (2010–2039, 2040–2069 ja 2070–2099) kohottamalla lämpötiloja ilmastonmuutosmallien ennustamalla tavalla. Laskelman pohjana käytettiin 19 ilmastomallin A1B-skenaarioajojen keskimäärin simuloimaa lämpötilan muutosta. Tulosten herkkyyden arvioimiseksi joitakin laskelmia tehtiin myös tätä selvästi heikompaa ja voimakkaampaa lämpenemisarviota käyttäen. A1B-skenaarion mukaisen lämpötilan nousun toteutuessa nykyisiä mallituloksia vastaavasti routakerros ohenee sadan vuoden aikana Pohjois-Suomessa 30–40 %, suuressa osassa maan keski- ja eteläosissa 50–70 %. Jo lähivuosikymmeninä roudan ennustetaan ohentuvan 10–30 %, saaristossa enemmän. Mikäli lämpeneminen toteutuisi voimakkaimman tarkastellun vaihtoehdon mukaisesti, roudan syvyys pienenisi tätäkin enemmän. Roudan paksuuden vuosienvälistä vaihtelua ja sen muuttumista tulevaisuudessa pyrittiin myös arvioimaan. Leutoina talvina routa ohenee enemmän kuin normaaleina tai ankarina pakkastalvina. Päivittäistä sään vaihtelua simuloineen säägeneraattorin tuottamassa aineistoissa esiintyi kuitenkin liian vähän hyvin alhaisia ja hyvin korkeita lämpötiloja. Siksi näitten lämpötilatietojen pohjalta laskettu roudan paksuuskin ilmeisesti vaihtelee liian vähän vuodesta toiseen. Kelirikkotilanteita voi esiintyä myös kesken routakauden, jos useamman päivän suojasää ja samanaikainen runsas vesisade pääsevät sulattamaan maata. Tällaiset routakauden aikana sattuvat säätilat näyttävätkin yleistyvän lähivuosikymmeninä. Vuosisadan loppua kohti ne sen sijaan maan eteläosissa jälleen vähenevät, koska routakausi lyhenee oleellisesti. Tulevia vuosikymmeniä koskevien ilmastonmuutosennusteiden ohella routaa ja kelirikon esiintymistä on periaatteessa mahdollista ennustaa myös lähiaikojen sääennusteita hyödyntäen. Pitkät, viikkojen tai kuukausien mittaiset sääennusteet eivät tosin ole ainakaan vielä erityisen luotettavia, mutta myös lyhyemmistä ennusteista voisi olla hyötyä mm. tienpitoa suunniteltaessa.