1,054 research outputs found

    Reconstructing Galaxy Spectral Energy Distributions from Broadband Photometry

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    We present a novel approach to photometric redshifts, one that merges the advantages of both the template fitting and empirical fitting algorithms, without any of their disadvantages. This technique derives a set of templates, describing the spectral energy distributions of galaxies, from a catalog with both multicolor photometry and spectroscopic redshifts. The algorithm is essentially using the shapes of the templates as the fitting parameters. From simulated multicolor data we show that for a small training set of galaxies we can reconstruct robustly the underlying spectral energy distributions even in the presence of substantial errors in the photometric observations. We apply these techniques to the multicolor and spectroscopic observations of the Hubble Deep Field building a set of template spectra that reproduced the observed galaxy colors to better than 10%. Finally we demonstrate that these improved spectral energy distributions lead to a photometric-redshift relation for the Hubble Deep Field that is more accurate than standard template-based approaches.Comment: 23 pages, 8 figures, LaTeX AASTeX, accepted for publication in A

    A Robust Classification of Galaxy Spectra: Dealing with Noisy and Incomplete Data

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    Over the next few years new spectroscopic surveys (from the optical surveys of the Sloan Digital Sky Survey and the 2 degree Field survey through to space-based ultraviolet satellites such as GALEX) will provide the opportunity and challenge of understanding how galaxies of different spectral type evolve with redshift. Techniques have been developed to classify galaxies based on their continuum and line spectra. Some of the most promising of these have used the Karhunen and Loeve transform (or Principal Component Analysis) to separate galaxies into distinct classes. Their limitation has been that they assume that the spectral coverage and quality of the spectra are constant for all galaxies within a given sample. In this paper we develop a general formalism that accounts for the missing data within the observed spectra (such as the removal of sky lines or the effect of sampling different intrinsic rest wavelength ranges due to the redshift of a galaxy). We demonstrate that by correcting for these gaps we can recover an almost redshift independent classification scheme. From this classification we can derive an optimal interpolation that reconstructs the underlying galaxy spectral energy distributions in the regions of missing data. This provides a simple and effective mechanism for building galaxy spectral energy distributions directly from data that may be noisy, incomplete or drawn from a number of different sources.Comment: 20 pages, 8 figures. Accepted for publication in A

    Puronvarsimetsien maakosteusolosuhteiden luokitus ja sen hyödyntäminen suojavyöhykkeiden määrittämisessä

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    Tiivistelmä. Vesiensuojelussa ja eliöstön monimuotoisuuden turvaamisessa on kysyntää uusille menetelmille, joilla voitaisiin täsmentää metsänhoidollisten metsäpurojen ja -norojen suojavyöhykkeiden suunnittelua. Maaston korkeusmallista johdettu depth-to-water- kosteusindeksi (DTW) on yksi tällainen potentiaalinen monimuotoisuuden indikaattori, sillä se pyrkii kuvastamaan vaihtelevia maankosteusolosuhteita, jotka ovat erilaisille ekosysteemeille tärkeitä. Tässä työssä tavoitteena oli verifioida DTW-indeksin kykyä kuvata todellisia maankosteusolosuhteita jatkuvatoimisten maankosteusanturien avulla. TMS4-maankosteusantureita asennettiin metsäpurojen varteen tutkimuslinjoille siten, että puroa lähestyessä laskettu DTW-arvo pääsääntöisesti pienenee ja maankosteus lisääntyy. Kosteusanturien tallentamat havainnot kalibroitiin maastossa kerättyjen maanäytteiden avulla, joista määritettiin laboratoriossa maankosteus. Tuloksia analysoitiin kuvaajien, tunnuslukujen ja tilastollisten vertailujen avulla. Pienimpiä DTW- indeksin arvoja sisältävien alueiden havainnot erosivat muista (yhdestä tai useammasta) korkeampia indeksin arvoja sisältävistä alueista maksimikosteuden, keskikosteuden, mediaanikosteuden suhteen. Lisäksi ne erosivat täysin vedellä kyllästyneen tilanteen keston ja 40 ja 60 prosentin volumetrisen kosteuden ylittämisen suhteen. Maalajin keskiarvon ylittävien kosteuksien suhteen tilastollisesti merkitsevää eroa alueiden väliltä ei löytynyt. DTW-indeksin lineaaristen mallien selitysosuudet eri tunnusluvuille olivat 14–37 prosenttia. Saturoituneisuusaika näytti laskevan jyrkästi pienillä DTW-indeksin arvoilla, joten kyseiselle tunnusluvulle olisi mahdollista määrittää vaihtelevanlevyisten suojavyöhykkeiden suunnittelua varten käyttökelpoinen kynnysarvo.The classification of soil moisture in riparian forests of headwater streams and its applicability to determination of protection zones. Abstract. In the field of water and biodiversity protection, there is demand for new measuring methods for the planning of more precise silvicultural protection zones of headwater streams. One potential indicator of biodiversity could be the depth-to-water (DTW) soil moisture index derived from digital elevation model (DEM) which aims at depicting the varying soil moisture conditions important to different ecosystems. The goal of this study was to verify the ability of DTW index to represent the actual soil moisture conditions using continuos soil moisture sensors. TMS4 soil moisture loggers were installed in riparian forests along study lines where the index value would assumingly be smaller and soil moisture greater closer to the stream. The observations recorded by the moisture sensors were calibrated according to soil samples collected from the field whose moisture content was determined in the laboratory. The results were analyzed from graphs, key figures and statistical comparisons. The observations from the zone having the smallest DTW index values differed from the (one ore more) zones having higher index values in the time of saturated state of soil, maximum moisture content, mean moisture content, median moisture content and the frequency of exceeding volumetric moisture content of 40 and 60 percent. There were no statistically significant difference between the groups in the amount of moisture observations exceeding the mean moisture of the particular type of soil. The explanatory powers (R2) of linear key figure models were 14–37 percent. The frequency of saturation sank pronouncedly with small index values so it might be possible to determine a saturation probability threshold value that could be useful in defining the borders of the riparian protection zones of varying width

    Kohdunkaulan syövän biologinen tausta

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    Tiivistelmä. Tämän työn aiheena on kohdunkaulan syöpä, joka on maailmanlaajuisesti naisten toisiksi yleisin syöpäsairaus. Työn tavoitteena oli koota yhteen kohdunkaulan syöpään vaikuttavia biologisia tekijöitä sekä siihen liittyviä muutoksia elimistössä. Työ on toteutettu kirjallisuuskatsauksen muodossa. Työssä käydään läpi yleisesti syövän syntyyn ja kehittymiseen vaikuttavia biologisia tekijöitä sekä tarkastellaan kohdunkaulan syövän taustoja biologisesta näkökulmasta. Työssä käsitellään myös HPV-virusta, joka on kohdunkaulan syövässä tärkein taustatekijä, sekä sen roolia kohdunkaulan syövän synnyssä. Ihmisen papilloomaviruksen biologiaa tutkimalla on pystytty kehittämään mm. HPV-testi ja HPV-rokote. Ne ovat suhteellisen uusia menetelmiä ja välineitä kohdunkaulan syövän esiintyvyyden laskemiseen. Perinteisempiä menetelmiä HPV-infektion ja kohdunkaulan syövän seulonnassa ja hoidossa ovat sytologia ja histologia, joiden avulla soluja ja niiden järjestäytymistä kudoksessa voidaan tarkastella mikroskooppisesti. Työssä käydään läpi näiden eri menetelmien taustoja biologian näkökulmasta. Lopuksi työssä esitellään HPV-infektion ja kohdunkaulan syövän eri vaiheiden aiheuttamia sytologisia ja histologisia muutoksia elimistössä. Syto- ja histologisia muutoksia on pyritty havainnollistamaan virtuaalimikroskooppikuvien avulla.Abstract. The topic of this thesis is cervical cancer which is the second most common cancer in women worldwide. The aim of this thesis was to review biological factors related to cervical cancer and the changes it causes in the human body. This thesis is in a form of literature review. Cancer in general, how it arises and develops and cervical cancer in specific are some of the themes of this thesis. One of the themes is the human papilloma virus which is the major cause of cervical cancer. Studying the biology of HPV has lead to some new approaches such as HPV-test and HPV-vaccine which are relatively new tools in prevention of cervical cancer. More traditional methods in HPV- and cancer screening are cytology and histology, which allow microscopic view of the cells and their organization in tissues. In this thesis these methods are elaborated from a biological point of view. Cytological and histological changes due to HPV-infection and cervical cancer together with its precursors are being discussed in the last chapter. In addition to description there are images from virtual microscope which aim to demonstrate these cytological and histological changes

    Principal manifolds and graphs in practice: from molecular biology to dynamical systems

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    We present several applications of non-linear data modeling, using principal manifolds and principal graphs constructed using the metaphor of elasticity (elastic principal graph approach). These approaches are generalizations of the Kohonen's self-organizing maps, a class of artificial neural networks. On several examples we show advantages of using non-linear objects for data approximation in comparison to the linear ones. We propose four numerical criteria for comparing linear and non-linear mappings of datasets into the spaces of lower dimension. The examples are taken from comparative political science, from analysis of high-throughput data in molecular biology, from analysis of dynamical systems.Comment: 12 pages, 9 figure

    An extension of Wiener integration with the use of operator theory

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    With the use of tensor product of Hilbert space, and a diagonalization procedure from operator theory, we derive an approximation formula for a general class of stochastic integrals. Further we establish a generalized Fourier expansion for these stochastic integrals. In our extension, we circumvent some of the limitations of the more widely used stochastic integral due to Wiener and Ito, i.e., stochastic integration with respect to Brownian motion. Finally we discuss the connection between the two approaches, as well as a priori estimates and applications.Comment: 13 page

    Spectral Templates from Multicolor Redshift Surveys

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    Understanding how the physical properties of galaxies (e.g. their spectral type or age) evolve as a function of redshift relies on having an accurate representation of galaxy spectral energy distributions. While it has been known for some time that galaxy spectra can be reconstructed from a handful of orthogonal basis templates, the underlying basis is poorly constrained. The limiting factor has been the lack of large samples of galaxies (covering a wide range in spectral type) with high signal-to-noise spectrophotometric observations. To alleviate this problem we introduce here a new technique for reconstructing galaxy spectral energy distributions directly from samples of galaxies with broadband photometric data and spectroscopic redshifts. Exploiting the statistical approach of the Karhunen-Loeve expansion, our iterative training procedure increasingly improves the eigenbasis, so that it provides better agreement with the photometry. We demonstrate the utility of this approach by applying these improved spectral energy distributions to the estimation of photometric redshifts for the HDF sample of galaxies. We find that in a small number of iterations the dispersion in the photometric redshifts estimator (a comparison between predicted and measured redshifts) can decrease by up to a factor of 2.Comment: 25 pages, 9 figures, LaTeX AASTeX, accepted for publication in A

    CLU, CR1 and PICALM genes associate with Alzheimer's-related senile plaques

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    Introduction APOE is the strongest risk gene for sporadic Alzheimer's disease (AD) so far. Recent genome wide association studies found links for sporadic AD with CLU and CR1 involved in Aβ clearance, and PICALM affecting intracellular trafficking. Methods We investigated the associations of senile plaques (SP) and neurofibrillary tangles (NFT) with the proposed risk genes and APOE, in the Tampere Autopsy Study (TASTY) series (603 cases), a sample of the general population (0 to 97 yrs), who died out-of-hospital. Results Age and the APOEε4 allele associated strongly with all phenotypes of SP, as expected. In age and APOEε4 adjusted analyses, compared to the most common homozygous genotype, burnt out SP were more common among carriers of the C-allele of CLU, whereas the T-allele of PICALM and C-allele of CR1 were linked with lower SP coverage. We found no significant associations between any of the genetic variants and NFT. Conclusions Marginal effects from CLU, CR1 and PICALM suggest that these genes have minimal effects on the development of AD lesions.BioMed Central Open acces

    On dimension reduction in Gaussian filters

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    A priori dimension reduction is a widely adopted technique for reducing the computational complexity of stationary inverse problems. In this setting, the solution of an inverse problem is parameterized by a low-dimensional basis that is often obtained from the truncated Karhunen-Loeve expansion of the prior distribution. For high-dimensional inverse problems equipped with smoothing priors, this technique can lead to drastic reductions in parameter dimension and significant computational savings. In this paper, we extend the concept of a priori dimension reduction to non-stationary inverse problems, in which the goal is to sequentially infer the state of a dynamical system. Our approach proceeds in an offline-online fashion. We first identify a low-dimensional subspace in the state space before solving the inverse problem (the offline phase), using either the method of "snapshots" or regularized covariance estimation. Then this subspace is used to reduce the computational complexity of various filtering algorithms - including the Kalman filter, extended Kalman filter, and ensemble Kalman filter - within a novel subspace-constrained Bayesian prediction-and-update procedure (the online phase). We demonstrate the performance of our new dimension reduction approach on various numerical examples. In some test cases, our approach reduces the dimensionality of the original problem by orders of magnitude and yields up to two orders of magnitude in computational savings
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