Hila- ja kuviotason laskennan vaikutus kuvion kokonaistilavuuteen, tallennustilaan ja laskentaaikaan teoreettista läpimittajakaumaa ja runkolukusarjaa käyttämällä

Metsäsuunnittelussa tarvittavan metsävaratiedon keräämisessä ollaan Suomessa siirtymässä kuvioittaisesta arvioinnista laserkeilaus- ja ilmakuvapohjaiseen kaukokartoitukseen. Tämän tutkimuksen tarkoitus oli selvittää kuvion kokonaistilavuuden ja läpimittajakauman ennustamisen tarkkuus koealan metsikkö- ja puustotunnuksista MSN-, PRM-, ML- ja FMM-menetelmiä sekä Weibull-jakaumaa hyödyntäen seuraavilla tavoilla: 1. PRM-menetelmällä hilatasolla, 2. PRMmenetelmällä kuviotasolla, 3. ML-menetelmällä hilatasolla ja 4. ML-menetelmällä kuviotasolla. Lisäksi kuvion kokonaistilavuuden ennustamisen tarkkuus selvitettiin hyödyntäen kuviolle tuotettua runkolukusarjaa. Tulokset laskettiin puulajikohtaisesti männylle, kuuselle, koivulle ja muille puulajeille. Puulajien tulokset laskettiin kuviotasolla yhteen. Lisäksi selvitettiin menetelmien laskenta-ajan ja tallennustilan tarve. Tutkimuksen aineistona käytettiin Hämeen ammattikorkeakoulun Evon toimipisteen metsistä mitattuja kiinteäsäteisiä ympyräkoealoja, joita oli 249 kappaletta. Hakkuukoneella mitattiin 12kuvion, joiden pinta-alat vaihtelivat välillä 0,2 – 1,94 hehtaaria, puustotiedot. Aluepohjaisen laserkeilausaineiston pulssin tiheys oli 1,8/m2 ja ilmakuvien pikselikoko 0,5 metriä. Kuvion kokonaistilavuus ennustettiin tai estimoitiin laserkeilaus- ja ilmakuva-aineiston piirteiden avulla koealojen puustotunnuksista. Tulokset laskettiin erikseen kaikille kuvioille ja kuvioille, joiden pinta-ala oli yli 0,5 hehtaaria. Yli 0,5 hehtaarin kuvioita oli 8 kappaletta. Kuvion hilojen naapureina käytettiin 1 - 10 koealaa. Menetelmästä ja naapurien määrästä riippuen kokonaistilavuuden suhteellinen RMSE ja harha vaihtelivat välillä 20,76 – 52,86 prosenttia ja -12,04 – 46,54 prosenttia. Vastaavat luvut yli 0,5 hehtaarin kuvioilla olivat 6,74 – 59,41 prosenttia ja -8,04 – 49,59 prosenttia. Laskenta-aika vaihteli menetelmien ja käytettyjen naapurien määrän mukaan voimakkaasti. Kehittyneemmällä ohjelmoinnilla ja ohjelmistolla laskenta-ajat voivat laskea merkittävästi. Tallennustila ei testatuilla menetelmillä ole rajoittava tekijä laajassakaan mittakaavassa. Läpimittajakauman perusteella PRM-menetelmä ennustaa puulajille erittäin kapean läpimittajakauman, jos koeala koostuu vain muutamasta lähes samankokoisesta puusta. Tämä vaikutti tuloksiin erityisesti menetelmällä PRM2.

Nonlinear mixture autoregressive model: economic applications

The aim of this dissertation is to model economic variables by a mixture autoregressive (MAR) model. The MAR model is a generalization of linear autoregressive (AR) model. The MAR -model consists of K linear autoregressive components. At any given point of time one of these autoregressive components is randomly selected to generate a new observation for the time series. The mixture probability can be constant over time or a direct function of a some observable variable. Many economic time series contain properties which cannot be described by linear and stationary time series models. A nonlinear autoregressive model such as MAR model can a plausible alternative in the case of these time series. In this dissertation the MAR model is used to model stock market bubbles and a relationship between inflation and the interest rate. In the case of the inflation rate we arrived at the MAR model where inflation process is less mean reverting in the case of high inflation than in the case of normal inflation. The interest rate move one-for-one with expected inflation. We use the data from the Livingston survey as a proxy for inflation expectations. We have found that survey inflation expectations are not perfectly rational. According to our results information stickiness play an important role in the expectation formation. We also found that survey participants have a tendency to underestimate inflation. A MAR model has also used to model stock market bubbles and crashes. This model has two regimes: the bubble regime and the error correction regime. In the error correction regime price depends on a fundamental factor, the price-dividend ratio, and in the bubble regime, price is independent of fundamentals. In this model a stock market crash is usually caused by a regime switch from a bubble regime to an error-correction regime. According to our empirical results bubbles are related to a low inflation. Our model also imply that bubbles have influences investment return distribution in both short and long run.

Methods and applications for improving parameter prediction models for stand structures in Finland

This thesis report attempts to improve the models for predicting forest stand structure for practical use, e.g. forest management planning (FMP) purposes in Finland. Comparisons were made between Weibull and Johnson s SB distribution and alternative regression estimation methods. Data used for preliminary studies was local but the final models were based on representative data. Models were validated mainly in terms of bias and RMSE in the main stand characteristics (e.g. volume) using independent data. The bivariate SBB distribution model was used to mimic realistic variations in tree dimensions by including within-diameter-class height variation. Using the traditional method, diameter distribution with the expected height resulted in reduced height variation, whereas the alternative bivariate method utilized the error-term of the height model. The lack of models for FMP was covered to some extent by the models for peatland and juvenile stands. The validation of these models showed that the more sophisticated regression estimation methods provided slightly improved accuracy. A flexible prediction and application for stand structure consisted of seemingly unrelated regression models for eight stand characteristics, the parameters of three optional distributions and Näslund s height curve. The cross-model covariance structure was used for linear prediction application, in which the expected values of the models were calibrated with the known stand characteristics. This provided a framework to validate the optional distributions and the optional set of stand characteristics. Height distribution is recommended for the earliest state of stands because of its continuous feature. From the mean height of about 4 m, Weibull dbh-frequency distribution is recommended in young stands if the input variables consist of arithmetic stand characteristics. In advanced stands, basal area-dbh distribution models are recommended. Näslund s height curve proved useful. Some efficient transformations of stand characteristics are introduced, e.g. the shape index, which combined the basal area, the stem number and the median diameter. Shape index enabled SB model for peatland stands to detect large variation in stand densities. This model also demonstrated reasonable behaviour for stands in mineral soils.

Lyophilized disaccharides – the effect of water during storage

Nearly one fourth of new medicinal molecules are biopharmaceutical (protein, antibody or nucleic acid derivative) based. However, the administration of these compounds is not always that straightforward due to the fragile nature of aforementioned domains in GI-tract. In addition, these molecules often exhibit poor bioavailability when administered orally. As a result, parenteral administration is commonly preferred. In addition, shelf-life of these molecules in aqueous environments is poor, unless stored in low temperatures. Another approach is to bring these molecules to anhydrous form via lyophilization resulting in enhanced stability during storage. Proteins cannot most commonly be freeze dried by themselves so some kind of excipients are nearly always necessary. Disaccharides are commonly utilized excipients in freeze-dried formulations since they provide a rigid glassy matrix to maintain the native conformation of the protein domain. They also act as "sink"-agents, which basically mean that they can absorb some moisture from the environment and still help to protect the API itself to retain its activity and therefore offer a way to robust formulation. The aim of the present study was to investigate how four amorphous disaccharides (cellobiose, melibiose, sucrose and trehalose) behave when they are brought to different relative humidity levels. At first, solutions of each disaccharide were prepared, filled into scintillation vials and freeze dried. Initial information on how the moisture induced transformations take place, the lyophilized amorphous disaccharide cakes were placed in vacuum desiccators containing different relative humidity levels for defined period, after which selected analyzing methods were utilized to further examine the occurred transformations. Affinity to crystallization, water sorption of the disaccharides, the effect of moisture on glass transition and crystallization temperature were studied. In addition FT-IR microscopy was utilized to map the moisture distribution on a piece of lyophilized cake. Observations made during the experiments backed up the data mentioned in a previous study: melibiose and trehalose were shown to be superior over sucrose and cellobiose what comes to the ability to withstand elevated humidity and temperature, and to avoid crystallization with pharmaceutically relevant moisture contents. The difference was made evident with every utilized analyzing method. In addition, melibiose showed interesting anomalies during DVS runs, which were absent with other amorphous disaccharides. Particularly fascinating was the observation made with polarized light microscope, which revealed a possible small-scale crystallization that cannot be observed with XRPD. As a result, a suggestion can safely be made that a robust formulation is most likely obtained by utilizing either melibiose or trehalose as a stabilizing agent for biopharmaceutical freeze-dried formulations. On the other hand, more experiments should be conducted to obtain more accurate information on why these disaccharides have better tolerance for elevating humidities than others.

Microbiological characterisation of soils : Evaluation of some critical steps in data collection and experimental design

The study of soil microbiota and their activities is central to the understanding of many ecosystem processes such as decomposition and nutrient cycling. The collection of microbiological data from soils generally involves several sequential steps of sampling, pretreatment and laboratory measurements. The reliability of results is dependent on reliable methods in every step. The aim of this thesis was to critically evaluate some central methods and procedures used in soil microbiological studies in order to increase our understanding of the factors that affect the measurement results and to provide guidance and new approaches for the design of experiments. The thesis focuses on four major themes: 1) soil microbiological heterogeneity and sampling, 2) storage of soil samples, 3) DNA extraction from soil, and 4) quantification of specific microbial groups by the most-probable-number (MPN) procedure. Soil heterogeneity and sampling are discussed as a single theme because knowledge on spatial (horizontal and vertical) and temporal variation is crucial when designing sampling procedures. Comparison of adjacent forest, meadow and cropped field plots showed that land use has a strong impact on the degree of horizontal variation of soil enzyme activities and bacterial community structure. However, regardless of the land use, the variation of microbiological characteristics appeared not to have predictable spatial structure at 0.5-10 m. Temporal and soil depth-related patterns were studied in relation to plant growth in cropped soil. The results showed that most enzyme activities and microbial biomass have a clear decreasing trend in the top 40 cm soil profile and a temporal pattern during the growing season. A new procedure for sampling of soil microbiological characteristics based on stratified sampling and pre-characterisation of samples was developed. A practical example demonstrated the potential of the new procedure to reduce the analysis efforts involved in laborious microbiological measurements without loss of precision. The investigation of storage of soil samples revealed that freezing (-20 °C) of small sample aliquots retains the activity of hydrolytic enzymes and the structure of the bacterial community in different soil matrices relatively well whereas air-drying cannot be recommended as a storage method for soil microbiological properties due to large reductions in activity. Freezing below -70 °C was the preferred method of storage for samples with high organic matter content. Comparison of different direct DNA extraction methods showed that the cell lysis treatment has a strong impact on the molecular size of DNA obtained and on the bacterial community structure detected. An improved MPN method for the enumeration of soil naphthalene degraders was introduced as an alternative to more complex MPN protocols or the DNA-based quantification approach. The main advantage of the new method is the simple protocol and the possibility to analyse a large number of samples and replicates simultaneously.

Thunderstorm climatology and lightning location applications in northern Europe

Thunderstorm is a dangerous electrical phenomena in the atmosphere. Thundercloud is formed when thermal energy is transported rapidly upwards in convective updraughts. Electrification occurs in the collisions of cloud particles in the strong updraught. When the amount of charge in the cloud is large enough, electrical breakdown, better known as a flash, occurs. Lightning location is nowadays an essential tool for the detection of severe weather. Located flashes indicate in real time the movement of hazardous areas and the intensity of lightning activity. Also, an estimate for the flash peak current can be determined. The observations can be used in damage surveys. The most simple way to represent lightning data is to plot the locations on a map, but the data can be processed in more complex end-products and exploited in data fusion. Lightning data serves as an important tool also in the research of lightning-related phenomena, such as Transient Luminous Events. Most of the global thunderstorms occur in areas with plenty of heat, moisture and tropospheric instability, for example in the tropical land areas. In higher latitudes like in Finland, the thunderstorm season is practically restricted to the summer season. Particular feature of the high-latitude climatology is the large annual variation, which regards also thunderstorms. Knowing the performance of any measuring device is important because it affects the accuracy of the end-products. In lightning location systems, the detection efficiency means the ratio between located and actually occurred flashes. Because in practice it is impossible to know the true number of actually occurred flashes, the detection efficiency has to be esimated with theoretical methods.

Inverse problem for the wave equation : partial data and novel boundary sources

An inverse problem for the wave equation is a mathematical formulation of the problem to convert measurements of sound waves to information about the wave speed governing the propagation of the waves. This doctoral thesis extends the theory on the inverse problems for the wave equation in cases with partial measurement data and also considers detection of discontinuous interfaces in the wave speed. A possible application of the theory is obstetric sonography in which ultrasound measurements are transformed into an image of the fetus in its mother's uterus. The wave speed inside the body can not be directly observed but sound waves can be produced outside the body and their echoes from the body can be recorded. The present work contains five research articles. In the first and the fifth articles we show that it is possible to determine the wave speed uniquely by using far apart sound sources and receivers. This extends a previously known result which requires the sound waves to be produced and recorded in the same place. Our result is motivated by a possible application to reflection seismology which seeks to create an image of the Earth s crust from recording of echoes stimulated for example by explosions. For this purpose, the receivers can not typically lie near the powerful sound sources. In the second article we present a sound source that allows us to recover many essential features of the wave speed from the echo produced by the source. Moreover, these features are known to determine the wave speed under certain geometric assumptions. Previously known results permitted the same features to be recovered only by sequential measurement of echoes produced by multiple different sources. The reduced number of measurements could increase the number possible applications of acoustic probing. In the third and fourth articles we develop an acoustic probing method to locate discontinuous interfaces in the wave speed. These interfaces typically correspond to interfaces between different materials and their locations are of interest in many applications. There are many previous approaches to this problem but none of them exploits sound sources varying freely in time. Our use of more variable sources could allow more robust implementation of the probing.