Stand dynamics modelling approaches for multicohort management of eastern Canadian boreal forests

Abstract

Colligation and Cross Moment-Based Approaches for Independent Component Analysis

Diplomityössä on käsitelty uudenlaisia menetelmiä riippumattomien komponenttien analyysiin(ICA): Menetelmät perustuvat colligaatioon ja cross-momenttiin. Colligaatio menetelmä perustuu painojen colligaatioon. Menetelmässä on käytetty kahden tyyppisiä todennäköisyysjakaumia yhden sijasta joka perustuu yleiseen itsenäisyyden kriteeriin. Työssä on käytetty colligaatio lähestymistapaa kahdella asymptoottisella esityksellä. Gram-Charlie ja Edgeworth laajennuksia käytetty arvioimaan todennäköisyyksiä näissä menetelmissä. Työssä on myös käytetty cross-momentti menetelmää joka perustuu neljännen asteen cross-momenttiin. Menetelmä on hyvin samankaltainen FastICA algoritmin kanssa. Molempia menetelmiä on tarkasteltu lineaarisella kahden itsenäisen muuttajan sekoituksella. Lähtö signaalit ja sekoitetut matriisit ovattuntemattomia signaali lähteiden määrää lukuunottamatta. Työssä on vertailtu colligaatio menetelmään ja sen modifikaatioita FastICA:an ja JADE:en. Työssä on myös tehty vertailu analyysi suorituskyvyn ja keskusprosessori ajan suhteen cross-momenttiin perustuvien menetelmien, FastICA:n ja JADE:n useiden sekoitettujen parien kanssa.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Carbon sequestration rates in Swedish forest soils : a comparison of three approaches

Selective papers of the workshop on "Development of models and forest soil surveys for monitoring of soil carbon", Koli, Finland, April 5-9 2006.

Developing a Comprehensive Model for Marketing Planning — Combining the Major Approaches

Mix marketing and relationships marketing are two major approaches that often form a basis for organizational marketing planning. The superiority of these approaches has been debated for long without any rational conclusion. Lately there have been studies indicating that both of the major approaches are many times used side by side in marketing planning. There have been also studies suggesting that even combining the mix marketing and relationship marketing approaches might be possible. The aim of this thesis is to provide knowledge about the usage of mix marketing and relationship marketing approaches in organizations and possibilities in combining the approaches. Also a settlement of strengths, weaknesses and risks of combining is intended to provide. The objectives were met through the literature and a case study research. In the case study, interviews were conducted in order to gain a deeper knowledge about marketing planning in various organizations. Based on this study, the combining of the major marketing approaches will be possible and even recommended when keeping in mind few aspects which might cause some troubles in the combining process.

Lipase-catalyzed Approaches towards Secondary Alcohols: Intermediates for Enantiopure Drugs

The use of enantiopure intermediates for drug synthesis is a trend in pharmaceutical industry. Different physiological effects are associated with the enantiomers of chiral molecules. Thus, the safety profile of a drug based on an enantiopure active pharmaceutical ingredient is more reliable. Biocatalysis is an important tool to access enantiopure molecules. In biocatalysis, the advantage of selectivity (chemo-, regio- and stereoselectivity) is combined with the benefits of a green synthesis strategy. Chemoenzymatic syntheses of drug molecules, obtained by combining biocatalysis with modern chemical synthesis steps usually consists of fewer reaction steps, reduced waste production and improved overall synthetic efficiency both in yields and enantio- and/or diastereoselectivities compared with classical chemical synthesis. The experimental work together with the literature review clearly indicates that lipase catalysis is highly applicable in the synthesis of enantiopure intermediates of drug molecules as the basis to infer the correct stereochemistry. By lipase catalysis, enantiopure secondary alcohols used as intermediates in the synthesis of Dorzolamide, an antiglaucoma drug, were obtained. Enantiopure _-hydroxy nitriles as potential intermediates for the synthesis of antidepressant drugs with 1-aryl-3- methylaminopropan-1-ol structure were also obtained with lipases. Kinetic resolution of racemates was the main biocatalytic approach applied. Candida Antarctica lipase B, Burkholderia cepacia lipase and Thermomyces lanuginosus lipase were applied for the acylation of alcohols and the alcoholysis of their esters in organic solvents, such as in diisopropyl ether and tert-butyl methyl ether. Candida Antarctica lipase B was used under solvent free conditions for the acylation of ethyl 3-hydroxybutanoate.

Non-Markovianity and Quantum Correlations in Qubit-Systems

In this Thesis I discuss the exact dynamics of simple non-Markovian systems. I focus on fundamental questions at the core of non-Markovian theory and investigate the dynamics of quantum correlations under non-Markovian decoherence. In the first context I present the connection between two different non-Markovian approaches, and compare two distinct definitions of non-Markovianity. The general aim is to characterize in exemplary cases which part of the environment is responsible for the feedback of information typical of non- Markovian dynamics. I also show how such a feedback of information is not always described by certain types of master equations commonly used to tackle non-Markovian dynamics. In the second context I characterize the dynamics of two qubits in a common non-Markovian reservoir, and introduce a new dynamical effect in a wellknown model, i.e., two qubits under depolarizing channels. In the first model the exact solution of the dynamics is found, and the entanglement behavior is extensively studied. The non-Markovianity of the reservoir and reservoirmediated-interaction between the qubits cause non-trivial dynamical features. The dynamical interplay between different types of correlations is also investigated. In the second model the study of quantum and classical correlations demonstrates the existence of a new effect: the sudden transition between classical and quantum decoherence. This phenomenon involves the complete preservation of the initial quantum correlations for long intervals of time of the order of the relaxation time of the system.

Teaching mathematics and programming : new approaches with empirical evaluation

Programming and mathematics are core areas of computer science (CS) and consequently also important parts of CS education. Introductory instruction in these two topics is, however, not without problems. Studies show that CS students find programming difficult to learn and that teaching mathematical topics to CS novices is challenging. One reason for the latter is the disconnection between mathematics and programming found in many CS curricula, which results in students not seeing the relevance of the subject for their studies. In addition, reports indicate that students' mathematical capability and maturity levels are dropping. The challenges faced when teaching mathematics and programming at CS departments can also be traced back to gaps in students' prior education. In Finland the high school curriculum does not include CS as a subject; instead, focus is on learning to use the computer and its applications as tools. Similarly, many of the mathematics courses emphasize application of formulas, while logic, formalisms and proofs, which are important in CS, are avoided. Consequently, high school graduates are not well prepared for studies in CS. Motivated by these challenges, the goal of the present work is to describe new approaches to teaching mathematics and programming aimed at addressing these issues: Structured derivations is a logic-based approach to teaching mathematics, where formalisms and justifications are made explicit. The aim is to help students become better at communicating their reasoning using mathematical language and logical notation at the same time as they become more confident with formalisms. The Python programming language was originally designed with education in mind, and has a simple syntax compared to many other popular languages. The aim of using it in instruction is to address algorithms and their implementation in a way that allows focus to be put on learning algorithmic thinking and programming instead of on learning a complex syntax. Invariant based programming is a diagrammatic approach to developing programs that are correct by construction. The approach is based on elementary propositional and predicate logic, and makes explicit the underlying mathematical foundations of programming. The aim is also to show how mathematics in general, and logic in particular, can be used to create better programs.

Verbal learning in mild cognitive impairment and alzheimer's disease : behavioural and neural approaches

The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.

Towards increased productivity and quality in software development using agile, lean and collaborative approaches

Dagens programvaruindustri står inför alltmer komplicerade utmaningar i en värld där programvara är nästan allstädes närvarande i våra dagliga liv. Konsumenten vill ha produkter som är pålitliga, innovativa och rika i funktionalitet, men samtidigt också förmånliga. Utmaningen för oss inom IT-industrin är att skapa mer komplexa, innovativa lösningar till en lägre kostnad. Detta är en av orsakerna till att processförbättring som forskningsområde inte har minskat i betydelse. IT-proffs ställer sig frågan: “Hur håller vi våra löften till våra kunder, samtidigt som vi minimerar vår risk och ökar vår kvalitet och produktivitet?” Inom processförbättringsområdet finns det olika tillvägagångssätt. Traditionella processförbättringsmetoder för programvara som CMMI och SPICE fokuserar på kvalitets- och riskaspekten hos förbättringsprocessen. Mer lättviktiga metoder som t.ex. lättrörliga metoder (agile methods) och Lean-metoder fokuserar på att hålla löften och förbättra produktiviteten genom att minimera slöseri inom utvecklingsprocessen. Forskningen som presenteras i denna avhandling utfördes med ett specifikt mål framför ögonen: att förbättra kostnadseffektiviteten i arbetsmetoderna utan att kompromissa med kvaliteten. Den utmaningen attackerades från tre olika vinklar. För det första förbättras arbetsmetoderna genom att man introducerar lättrörliga metoder. För det andra bibehålls kvaliteten genom att man använder mätmetoder på produktnivå. För det tredje förbättras kunskapsspridningen inom stora företag genom metoder som sätter samarbete i centrum. Rörelsen bakom lättrörliga arbetsmetoder växte fram under 90-talet som en reaktion på de orealistiska krav som den tidigare förhärskande vattenfallsmetoden ställde på IT-branschen. Programutveckling är en kreativ process och skiljer sig från annan industri i det att den största delen av det dagliga arbetet går ut på att skapa något nytt som inte har funnits tidigare. Varje programutvecklare måste vara expert på sitt område och använder en stor del av sin arbetsdag till att skapa lösningar på problem som hon aldrig tidigare har löst. Trots att detta har varit ett välkänt faktum redan i många decennier, styrs ändå många programvaruprojekt som om de vore produktionslinjer i fabriker. Ett av målen för rörelsen bakom lättrörliga metoder är att lyfta fram just denna diskrepans mellan programutvecklingens innersta natur och sättet på vilket programvaruprojekt styrs. Lättrörliga arbetsmetoder har visat sig fungera väl i de sammanhang de skapades för, dvs. små, samlokaliserade team som jobbar i nära samarbete med en engagerad kund. I andra sammanhang, och speciellt i stora, geografiskt utspridda företag, är det mera utmanande att införa lättrörliga metoder. Vi har nalkats utmaningen genom att införa lättrörliga metoder med hjälp av pilotprojekt. Detta har två klara fördelar. För det första kan man inkrementellt samla kunskap om metoderna och deras samverkan med sammanhanget i fråga. På så sätt kan man lättare utveckla och anpassa metoderna till de specifika krav som sammanhanget ställer. För det andra kan man lättare överbrygga motstånd mot förändring genom att introducera kulturella förändringar varsamt och genom att målgruppen får direkt förstahandskontakt med de nya metoderna. Relevanta mätmetoder för produkter kan hjälpa programvaruutvecklingsteam att förbättra sina arbetsmetoder. När det gäller team som jobbar med lättrörliga och Lean-metoder kan en bra uppsättning mätmetoder vara avgörande för beslutsfattandet när man prioriterar listan över uppgifter som ska göras. Vårt fokus har legat på att stöda lättrörliga och Lean-team med interna produktmätmetoder för beslutsstöd gällande så kallad omfaktorering, dvs. kontinuerlig kvalitetsförbättring av programmets kod och design. Det kan vara svårt att ta ett beslut att omfaktorera, speciellt för lättrörliga och Lean-team, eftersom de förväntas kunna rättfärdiga sina prioriteter i termer av affärsvärde. Vi föreslår ett sätt att mäta designkvaliteten hos system som har utvecklats med hjälp av det så kallade modelldrivna paradigmet. Vi konstruerar även ett sätt att integrera denna mätmetod i lättrörliga och Lean-arbetsmetoder. En viktig del av alla processförbättringsinitiativ är att sprida kunskap om den nya programvaruprocessen. Detta gäller oavsett hurdan process man försöker introducera – vare sig processen är plandriven eller lättrörlig. Vi föreslår att metoder som baserar sig på samarbete när processen skapas och vidareutvecklas är ett bra sätt att stöda kunskapsspridning på. Vi ger en översikt över författarverktyg för processer på marknaden med det förslaget i åtanke.

Lethal weapons : novel approaches for receptor-targeted cancer cell elimination

The currently used forms of cancer therapy are associated with drug resistance and toxicity to healthy tissues. Thus, more efficient methods are needed for cancer-specific induction of growth arrest and programmed cell death, also known as apoptosis. Therapeutic forms of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) are investigated in clinical trials due to the capability of TRAIL to trigger apoptosis specifically in cancer cells by activation of cell surface death receptors. Many tumors, however, have acquired resistance to TRAIL-induced apoptosis and sensitizing drugs for combinatorial treatments are, therefore, in high demand. This study demonstrates that lignans, natural polyphenols enriched in seeds and cereal, have a remarkable sensitizing effect on TRAIL-induced cell death at non-toxic lignan concentrations. In TRAIL-resistant and androgen-dependent prostate cancer cells we observe that lignans repress receptor tyrosine kinase (RTK) activity and downregulate cell survival signaling via the Akt pathway, which leads to increased TRAIL sensitivity. A structure-activity relationship analysis reveals that the γ-butyrolactone ring of the dibenzylbutyrolactone lignans is essential for the rapidly reversible TRAIL-sensitizing activity of these compounds. Furthermore, the lignan nortrachelogenin (NTG) is identified as the most efficient of the 27 tested lignans and norlignans in sensitization of androgen-deprived prostate cancer cells to TRAIL-induced apoptosis. While this combinatorial anticancer approach may leave normal cells unharmed, several efficient cancer drugs are too toxic, insoluble or unstable to be used in systemic therapy. To enable use of such drugs and to protect normal cells from cytotoxic effects, cancer-targeted drug delivery vehicles of nanometer scale have recently been generated. The newly developed nanoparticle system that we tested in vitro for cancer cell targeting combines the efficient drug-loading capacity of mesoporous silica to the versatile particle surface functionalization of hyperbranched poly(ethylene imine), PEI. The mesoporous hybrid silica nanoparticles (MSNs) were functionalized with folic acid to promote targeted internalization by folate receptor overexpressing cancer cells. The presented results demonstrate that the developed carrier system can be employed in vitro for cancer selective delivery of adsorbed or covalently conjugated molecules and furthermore, for selective induction of apoptotic cell death in folate receptor expressing cancer cells. The tested carrier system displays potential for simultaneous delivery of several anticancer agents specifically to cancer cells also in vivo.