The art of coarse Stokes: Richardson extrapolation improves the accuracy and efficiency of the method of regularized stokeslets

The method of regularised stokeslets is widely used in microscale biological fluid dynamics due to its ease of implementation, natural treatment of complex moving geometries, and removal of singular functions to integrate. The standard implementation of the method is subject to high computational cost due to the coupling of the linear system size to the numerical resolution required to resolve the rapidly-varying regularised stokeslet kernel. Here we show how Richardson extrapolation with coarse values of the regularisation parameter is ideally-suited to reduce the quadrature error, hence dramatically reducing the storage and solution costs without loss of accuracy. Numerical experiments on the resistance and mobility problems in Stokes flow support the analysis, confirming several orders of magnitude improvement in accuracy and/or efficiency.Comment: 22 pages, 4 figure

Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization

We recover a video of the motion taking place in a hidden scene by observing changes in indirect illumination in a nearby uncalibrated visible region. We solve this problem by factoring the observed video into a matrix product between the unknown hidden scene video and an unknown light transport matrix. This task is extremely ill-posed, as any non-negative factorization will satisfy the data. Inspired by recent work on the Deep Image Prior, we parameterize the factor matrices using randomly initialized convolutional neural networks trained in a one-off manner, and show that this results in decompositions that reflect the true motion in the hidden scene.Comment: 14 pages, 5 figures, Advances in Neural Information Processing Systems 201

When are Neural ODE Solutions Proper ODEs?

A key appeal of the recently proposed Neural Ordinary Differential Equation(ODE) framework is that it seems to provide a continuous-time extension of discrete residual neural networks. As we show herein, though, trained Neural ODE models actually depend on the specific numerical method used during training. If the trained model is supposed to be a flow generated from an ODE, it should be possible to choose another numerical solver with equal or smaller numerical error without loss of performance. We observe that if training relies on a solver with overly coarse discretization, then testing with another solver of equal or smaller numerical error results in a sharp drop in accuracy. In such cases, the combination of vector field and numerical method cannot be interpreted as a flow generated from an ODE, which arguably poses a fatal breakdown of the Neural ODE concept. We observe, however, that there exists a critical step size beyond which the training yields a valid ODE vector field. We propose a method that monitors the behavior of the ODE solver during training to adapt its step size, aiming to ensure a valid ODE without unnecessarily increasing computational cost. We verify this adaption algorithm on two common bench mark datasets as well as a synthetic dataset. Furthermore, we introduce a novel synthetic dataset in which the underlying ODE directly generates a classification task

Seed coating for delayed germination

The diffuse leaching of plant nutrients from agricultural soils is part of the problem of the eutrophication of fresh water systems and coastal sea waters. Among the measures taken to reduce the leaching is keeping the soil with plant cover during autumn and winter. In areas with a predominance of annual crops this can be achieved by the undersowing of catch crops. In the current work it was investigated how the time of undersowing affected the barley (Hordeum distichon L.) crop and the catch crop biomass production. As catch crops Italian ryegrass (Lolium multiflorum L.), perennial ryegrass (Lolium perenne Lam.) and red clover (Trifolium pratense L.) were used. The biomass of the catch crop was markedly reduced with delayed undersowing, but net biomass production in late autumn was generally not affected. On light soil the barley yield was only to a small extent affected by the undersown catch crop, and with delayed undersowing the yield was even less affected. On heavier soil the barley yield was only marginally affected regardless of time of catch crop undersowing. An alternative to the undersowing of catch crops would be relay cropping of two cereal crops, one spring crop and one winter crop. As their initial competitive capacities are similar there is a risk that the winter crop will affect the spring crop yield adversely. To be able to set the competitive relationship between the crops favourably for the relay cropping system to be effective, a means to delay the winter crop germination is needed. Delayed undersowing has the risk of damaging the spring crop by the drilling procedur itself, and this was also noticed in the catch crop field experiments. In a couple of experiments the technique of coating seeds with polymers to achieve delayed germination was explored. The materials used were cellulose lacquer (in one experiment with the addition of lanolin) or an acrylic plastic, a so called primer. Wheat (Triticum aestivum L.) and oil seed rape (Brassica napus L.) were coated in house with several coating levels and germinated under controlled conditions in Petri dishes. In one experiment the coated seeds were germinated under three different temperature levels and three different moisture levels. It was found that delays could be achieved and that with increasing coating level the delays increased. It was also found that at low germination temperature (5.5 °C) for plastic coated seeds there was almost no difference in temperature sum needed from sowing to germination regardless of coating level. At high germination temperature (13.9 °C) there was a marked increase in temperature sum needed to germination and it increased with increasing coating level in comparison with uncoated seed. The resulting germination pattern was hypothetically explained by the dependence of water and oxygen uptake on temperature, in relation to the permeability of the coating materials. The permeability of the materials was probably rather constant over the temperature range. To gain the necessary control of the desired germination delay further investigations are needed, in collaboration with other scientific disciplines

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.Siirretty Doriast

Ohran ja kauran folaatit ja folaatin luontainen lisääminen ohraa ja kauraa prosessoimalla

Folate, one of the B vitamins, has a well-established role in preventing neural tube defects (NTDs) in the developing foetus and megaloblastic anaemia. Folate intake is below recommended levels, especially in countries where mandatory folic acid fortification is not practiced. In these countries, interest to innovate ways for the natural enhancement of folate is high. Wholegrain cereals provide a high proportion of natural folate. Oats and barley have once again attracted attention as cereals with health potential due to their high beta-glucan contents. However, knowledge on the folate content in oats and barley and their milling fractions is limited. In turn, several microbes are potential folate producers in aqueous processes. Folate content in cereal-based products could be further improved by utilising folate-rich milling fractions or by using the ability of microbes to synthesise folate. In this thesis, oats and barley were studied as sources of folate. The total folate was determined in five oat and barley cultivars over three years with a microbiological method. Different fractions were produced from oats by oat processing and from barley by scarification and industrial milling. The folate vitamer distribution in fractions was examined with the ultra-high performance liquid chromatography (UHPLC) method. Furthermore, bacteria isolated from cereal products, food-grade yeasts and lactic acid bacteria (LAB) were studied for their folate-production in rich medium and in aqueous processes of oat and barley bran and flour. In addition, the profile of the produced folate vitamers was studied in rich medium and in oat flour and barley bran matrices. The validated UHPLC method proved to be fast and sensitive for determining seven folate vitamers in cereal and microbe samples. New data was obtained on the folate content and its variation in oat and barley cultivars. The total folate content in barley grains was slightly higher at 770 ng/g dm, than the folate content in oats (690 ng/g dm) when determined shortly after harvest. These contents were higher than had been previously found in wheat. In addition, the variation among the cultivars in each year was moderate. This study also showed that oat and barley grains might lose folate during storage. Dry-fractionation of oats and barley yielded fractions with high folate content. Among the oat fractions, the highest folate content was found in its by-products. The folate content in the residual flour from oat flaking was 2.5-fold that of native oat grain. In barley grain 40 60% of the folate was lost during industrial dehulling and pearling processes. The total folate content in oat and barley fractions demonstrated that folate was localised in the outer layers and germ. The main folate vitamers in the oat and barley fractions were 5-methyltetrahydrofolate, 5-formyltetrahydrofolate and 5,10-methenyltetrahydrofolate. A few endogenous bacteria isolated from oat bran produced folate in rich medium more than Saccharomyces cerevisiae, which is known as a good folate producer. In cereal matrices, several food-grade yeasts produced a significant amount of folate with glucose addition, but folate production by LAB was low. Folate content in the oat flour matrix fermented with Pseudomonas sp. for 24 h and stored for 2 weeks in the cold was 9-fold that of the control sample. Bacteria and yeasts accumulated the most 5-methyltetrahydrofolate followed by tetrahydrofolate and 5,10-methenyltetrahydrofolate. The results in this thesis show that oats and barley are good sources of folate. Introducing folate-rich milling fractions into cereal products would increase the folate intake of consumers. Further, food-grade yeasts and bacteria have potential for folate enhancement in aqueous cereal processing. Particularly, the folate production by some cereal-based endogenous bacteria offers possibilities for natural folate enrichment in beta-glucan-rich oat and barley matrices.Folaatit ovat vesiliukoisia B-vitamiiniyhdisteitä, joita tarvitaan yhden hiiliyksikön siirtoreaktioissa DNA:n ja RNA:n synteesissä sekä aminohappoaineenvaihdunnassa. Folaatti esiintyy luonnossa monina eri muotoina. Foolihappo on synteettisesti valmistettu, biologisesti aktiivinen folaattimuoto, jota käytetään farmaseuttisissa valmisteissa ja elintarvikkeiden rikastamisessa. Riittämätön folaatin saanti aiheuttaa megaloblastista anemiaa sekä raskauden varhaisvaiheessa sikiön hermostoputken sulkeutumishäiriöitä. Lisäksi vähäisellä folaatin saannilla on todettu olevan yhteys lisääntyneeseen riskiin sairastua tiettyihin syöpätyyppeihin, sydän- ja verisuonitauteihin ja muistisairauksiin. Folaatin saanti jää alle suositusten Suomessa ja useissa muissakin Euroopan maissa, joissa lainsäädäntö ei velvoita lisäämään foolihappoa vehnäjauhoihin. Suomessa noin lähes kolmasosa folaatista saadaan vilja- ja leipomotuotteista, mutta niiden folaattipitoisuuksia voitaisiin kuitenkin yhä lisätä. Ohran ja kauran elintarvikekäyttöä kannattaisi suosia niiden sisältämien bioaktiivisten yhdisteiden ja osittain liukoisen kuidun, beeta-glukaanin takia. Aikaisemmin on todettu, että vehnän ja rukiin jyvän uloimmat kerrokset, ns. lesekerrokset, sisältävät paljon bioaktiivisia yhdisteitä. Ohran ja kauran folaateista on kuitenkin erittäin vähän tutkimustietoa. Luontaisen folaatin tuottamiseen voitaisiin käyttää myös mikrobeja, sillä tietyt bakteerit ja hiivat syntetisoivat folaattia sopivissa kasvatusolosuhteissa. Tämän väitöskirjatutkimuksen tavoitteena oli tutkia ohraa ja kauraa folaatin lähteinä sekä selvittää, miten ohra- ja kauratuotteiden folaattipitoisuuksia voitaisiin lisätä luontaisesti. Aluksi erittäin suuren erotuskyvyn nestekromatografinen erotusmenetelmä (UHPLC) optimoitiin soveltuvaksi viljamateriaalin eri folaattimuotojen tutkimiseen. Tämän jälkeen määritettiin kaura- ja ohralajikkeiden folaattipitoisuudet kolmelta eri satokaudelta. Lisäksi selvitettiin, mihin jauhatusjakeisiin folaatit ovat rikastuneet ohran ja kauran jyvissä. Tutkimuksen toisessa osassa tutkittiin viljassa luontaisesti esiintyvien bakteereiden ja muualta eristettyjen hiivojen ja bakteereiden folaatin tuottoa synteettisessä kasvatusalustassa. Lopuksi ohran ja kauran vesiseoksia, puuroja, fermentoitiin folaattia tuottavilla mikrobeilla, joilla ei ollut todettu beeta-glukaanin rakennetta hajottavaa entsyymiaktiivisuutta. UHPLC-menetelmä määritti nopeasti ja luotettavasti eri folaattimuodot viljamateriaalista. Sillä saatujen tulosten vastaavuus mikrobiologisen menetelmän tuloksiin oli parempi kuin aikaisemmissa tutkimuksissa. Ohra ja kaura osoittautuivat hyviksi folaatin lähteiksi. Keskimäärin tuore, kuorimaton kokojyväohra sisälsi hieman enemmän folaattia (770 ng/g kuiva-ainetta kohden) kuin kuorimaton kokojyväkaura (690 ng/g) mutta sekä ohrassa että kaurassa folaattia oli hieman enemmän kuin vehnässä. Kun eri ohra- ja kauralajikkeiden folaattipitoisuuksia verrattiin satokausittain toisiinsa, voitiin tunnistaa lajikkeita, joiden folaattipitoisuus oli joka vuosi suurin tai pienin verrattuna muihin lajikkeisiin. Lisäksi todettiin, että normaalin, 2 3 vuoden varastoinnin aikana jyvät menettävät osan folaatistaan. Ohran ja kauran jyvien myllytys tuotti folaattirikkaita jakeita. Folaatti on ohran ja kauran jyvissä rikastuneena jyvän uloimpiin kerroksiin ja alkioon. Tietyt ohran jauhatusjakeet sisälsivät 5 kertaa enemmän folaattia kuin kuluttajille tarjottava ohrajauho. Lisäksi osoitettiin, että ohran teollisessa kuorikerrosten hionnassa menetetään 40 60 % hiomattoman kokojyväohran folaateista. Erityisen paljon folaattia oli myös kauran hiutaloinnissa syntyvässä jäännösjauhossa. Ohran ja kauran folaatti oli pääasiassa 5- metyylitetrahydro-, 5-formyylitetrahydro- ja 5,10-metenyylitetrahydrofolaattina. Hiivat tuottivat folaattia huomattavia määriä ohra- ja kaurapuuroissa, joihin oli lisätty glukoosia. Muutamat viljatuotteista eristetyt bakteerit osoittautuivat kuitenkin tehokkaammiksi folaatintuottajiksi kuin hyväksi tuottajaksi todettu leivinhiiva. Kaurakuidusta eristetty Pseudomonas sp. tuotti folaattia kaurapuurossa niin, että puuron folaattipitoisuus fermentoinnin ja kylmäsäilytyksen jälkeen oli yhdeksänkertainen verrattuna käsittelemättömään näytteeseen. Sen sijaan maitohappobakteereiden folaatin tuotto puuroissa oli vähäistä. Bakteerit ja hiivat tuottivat pääasiassa 5-metyylitetrahydro- ja tetrahydrofolaattia. Tämän väitöskirjatyön tulokset osoittavat, että ohra ja kaura ovat hyviä folaatin lähteitä. Niiden folaattirikkaita jauhatusjakeita voitaisiin lisätä leivontaominaisuuksien sallimissa rajoissa viljatuotteisiin, jolloin kuluttajien päivittäinen folaatin saanti paranisi. Lisäksi tutkimus selvitti, että tietyt elintarvikkeista eristetyt hiivat ja viljaperäiset bakteerit ovat erityisen hyviä folaatin tuottajia. Niitä voitaisiin hyödyntää viljapohjaisten, nestemäisten elintarvikkeiden tuotekehityksessä, kun halutaan yhdistää folaatin ja beeta-glukaanin terveyttä edistävät vaikutukset