71 research outputs found

    Data-assimilaatiomenetelmistÀ ja niiden soveltamisesta ROSE-kemiakuljetusmalllin

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    Data-assimilaatio on tekniikka, jossa havaintoja yhdistetÀÀn dynaamisiin numeerisiin malleihin tarkoituksena tuottaa optimaalista esitystÀ esimerkiksi ilmankehÀn muuttuvasta tilasta. Data-assimilaatiota kÀytetÀÀn muun muassa operaativisessa sÀÀn ennustamisessa. TÀssÀ työssÀ esitellÀÀn eri data-assimilaatiomenetelmiÀ, jotka jakautuvat pÀÀpiirteittÀin Kalmanin suotimiin ja variaatioanaalisiin menetelmiin. LisÀksi esitellÀÀn erilaisia data-assimilaatiossa tarvittavia apuvÀlineitÀ kuten optimointimenetelmiÀ. Eri data-assimilaatiomenetelmien toimintaa havainnollistetaan esimerkkien avulla. TÀssÀ työssÀ data-assimilaatiota sovelletaan muun muassa Lorenz95-malliin. KÀytÀnnön data-assimilaatio-ongelmana on GOMOS-instrumentista saatavan otsonin assimiloiminen kÀyttÀen hyvÀksi ROSE-kemiakuljetusmallia

    Regulation of gonadal steroid synthesis and reproduction : novel roles of hydroxysteroid (17ÎČ) dehydrogenase 1

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    Estrogens and androgens are critical regulators of several physiological processes,including development and reproduction. In addition, these hormones play key roles in several physiological complications and diseases, such as infertility, endometriosis, Breast cancer and prostate cancer. According to the classical view steroid hormone actions are thought to be regulated by systemic hormone levels, where endocrine glands produce the hormones and blood circulation delivers the hormones to target organs. However, accumulative evidence has shown that the control of steroid hormone actions is also regulated at the level of target cell metabolism. Due to the crucial roles of steroid hormones in physiological functions and in the etiology of several diseases, a better understanding of steroid hormone metabolism is needed. In this study, we generated a conventional global knockout mouse model, hydroxysteroid (17ÎČ) dehydrogenase 1 (hsd17b1ko), to achieve a better understanding of enzymatic regulation of steroid hormone actions and of the role of the hsd17b1 in the development of reproductive organs and fertility in females and males. This study revealed that a lack of the enzyme does not have an impact on fetal or pubertal development in either males or females. However, steroid synthesis is affected in both females and males, and enzyme deficiency leads to severely impaired fertility in females and infertility in males. Thus, this study indicates that the hsd17b1 enzyme plays a critical role in regulating steroid hormone synthesis and actions, and that a lack of the enzyme has a profound influence on mouse gonadal function in both males and females. In summary, the produced knockout mouse model provides a tool and knowledge to understand steroid hormone synthesis and actions in reproductive tissues.Estrogeenit ja androgeenit ovat tĂ€rkeitĂ€ sÀÀtelytekijöitĂ€ useissa erilaisissa fysiologisissa tapahtumissa, kuten kehityksessĂ€ ja lisÀÀntymisessĂ€. LisĂ€ksi hormonit ovat avainasemassa monissa sairauksissa, kuten hedelmĂ€ttömyydessĂ€, endometrioosissa, rintasyövĂ€ssĂ€ ja eturauhassyövĂ€ssĂ€. Hormonitasojen sÀÀtelyn on yleisesti ajateltu tapahtuvan systeemisesti siten, ettĂ€ umpieritysrauhaset tuottavat hormonit ja verenkierto vĂ€littÀÀ ne kohdekudoksiin. YhĂ€ kasvava mÀÀrĂ€ tutkimuksia on kuitenkin osoittanut, ettĂ€ hormonitoimintaa sÀÀdellÀÀn myös kohdesolutasolla. Koska hormonit ovat tĂ€rkeitĂ€ monille fysiologisille toiminnoille ja useiden sairauksien etenemiselle, syvempÀÀ ymmĂ€rrystĂ€ hormoniaineenvaihdunnasta tarvitaan. TĂ€ssĂ€ tutkimuksessa olemme tuottaneet hydroksisteroidi (17ÎČ) dehydrogenaasi 1-poistogeenisen hiirimallin. TĂ€mĂ€n mallin avulla pyrimme ymmĂ€rtĂ€mÀÀn nykyistĂ€ paremmin hormonisynteesin entsymaattista sÀÀtelyĂ€ sekĂ€ tĂ€mĂ€n entsyymin vaikutusta kehitykseen ja lisÀÀntymiseen. TĂ€ssĂ€ tutkimuksessa olemme osoittaneet, ettĂ€ HSD17B1-entsyymin puutteella ei ole vaikutusta sikiökautiseen tai puberteetin aikaiseen kehitykseen. Kuitenkin HSD17B1:n poisto on vaikuttanut kummankin sukupuolen hormonituotantoon, sekĂ€ lisĂ€ksi naarashiirten hedelmĂ€llisyys alentui huomattavasti ja uroshiiret olivat tĂ€ysin hedelmĂ€ttömiĂ€. Tutkimustuloksemme osoittavat, ettĂ€ HSD17B1-entsyymillĂ€ on tĂ€rkeĂ€ merkitys hormonisynteesin sÀÀtelyssĂ€ ja hormonitoiminnassa, ja HSD17B1-entsyymin puutos vaikuttaa merkittĂ€vĂ€sti hiiren lisÀÀntymiseen sekĂ€ uroksilla ettĂ€ naarailla. Yhteenvetona voidaan todeta, ettĂ€ kehitetty poistogeeninen hiirimalli mahdollistaa yhden lisÀÀntymiselimissĂ€ hormonisynteesiin ja hormonitoimintaan vaikuttavan entsyymin tutkimisen ja tiedon lisÀÀmisen hormonisynteesin sÀÀtelystĂ€

    Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia

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    Crude oil production activities and associated petroleum gas (APG) flaring are responsible for significant air polluting and greenhouse gas (GHG) emissions and have negative effects on the environment and climate. In Russia, one of the world's major oil producers, APG flaring remains a routine practice despite regulatory policies. We present the first analysis of nitrogen oxide and methane emissions over Tas-Yuryakh and Talakan oil fields in Sakha Republic (Eastern Siberia, Russia) using multi-satellite observations.Peer reviewe

    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

    HSD17B1 expression induces inflammation-aided rupture of mammary gland myoepithelium

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    Hydroxysteroid (17-beta) dehydrogenase type 1 (HSD17B1) converts low-active estrogen estrone to highly active estradiol. Estradiol is necessary for normal postpubertal mammary gland development; however, elevated estradiol levels increase mammary tumorigenesis. To investigate the significance of the human HSD17B1 enzyme in the mammary gland, transgenic mice universally overexpressing human HSD17B1 were used (HSD17B1TG mice). Mammary glands obtained from HSD17B1TG females at different ages were investigated for morphology and histology, and HSD17B1 activity and estrogen receptor activation in mammary gland tissue were assessed. To study the significance of HSD17B1 enzyme expression locally in mammary gland tissue, HSD17B1-expressing mammary epithelium was transplanted into cleared mammary fat pads of wild-type females, and the effects on mammary gland estradiol production, epithelial cells and the myoepithelium were investigated. HSD17B1TG females showed increased estrone to estradiol conversion and estrogen-response element-driven estrogen receptor signaling in mammary gland tissue, and they showed extensive lobuloalveolar development that was further enhanced by age along with an increase in serum prolactin concentrations. At old age, HSD17B1TG females developed mammary cancers. Mammary-restricted HSD17B1 expression induced lesions at the sites of ducts and alveoli, accompanied by peri- and intraductal inflammation and disruption of the myoepithelial cell layer. The lesions were shown to be estrogen dependent, as treatment with an antiestrogen, ICI 182,780, starting when lesions were already established reversed the phenotype. These data elucidate the ability of human HSD17B1 to enhance estrogen action in the mammary gland in vivo and indicate that HSD17B1 is a factor inducing phenotypic alterations associated with mammary tumorigenesis.</p

    Analyzing Local Carbon Dioxide and Nitrogen Oxide Emissions From Space Using the Divergence Method: An Application to the Synthetic SMARTCARB Dataset

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    Since the Paris Agreement was adopted in 2015, the role of space-based observations for monitoring anthropogenic greenhouse gas (GHG) emissions has increased. To meet the requirements for monitoring carbon dioxide (CO2) emissions, the European Copernicus programme is preparing a dedicated CO2 Monitoring (CO2M) satellite constellation that will provide CO2 and nitrogen dioxide (NO2) observations at 4 km2 resolution along a 250 km wide swath. In this paper, we adapt the recently developed divergence method to derive both CO2 and nitrogen oxide (NOx) emissions of cities and power plants from a CO2M satellite constellation by using synthetic observations from the COSMO-GHG model. Due to its long lifetime, the large CO2 atmospheric background needs to be removed to highlight the anthropogenic enhancements before calculating the divergence. Since the CO2 noise levels are large compared to the anthropogenic enhancements, we apply different denoising methods and compare the effect on the CO2 emission estimates. The annual NOx and CO2 emissions estimated from the divergence maps using the peak fitting approach are in agreement with the expected values, although with larger uncertainties for CO2. We also consider the possibility to use co-emitted NOx emission estimates for quantifying the CO2 emissions, by using source-specific NOx-to-CO2 emission ratios derived directly from satellite observations. In general, we find that the divergence method provides a promising tool for estimating CO2 emissions, alternative to typical methods based on inverse modeling or on the analysis of individual CO2 plumes
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