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Institution

Tallinn University of Technology

EducationTallinn, Estonia
About: Tallinn University of Technology is a education organization based out in Tallinn, Estonia. It is known for research contribution in the topics: European union & Oil shale. The organization has 3688 authors who have published 10313 publications receiving 145058 citations. The organization is also known as: Tallinn Technical University & Tallinna Tehnikaülikool.


Papers
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Journal ArticleDOI
01 Jan 2009
TL;DR: This paper deals with approximations by the interpolating generalized Shannon sampling series by solving the inequality of the following type: For α ≥ 1, β ≥ 1 using the LaSalle-Bouchut inequality.
Abstract: This paper deals with approximations of bounded, uniformly continuous on the whole real axis, functions by the interpolating Shannon sampling operators. These interpolating operators are defined by the kernels obtained by dilation from known ones, in particular, such as Rogosinski and Blackman-Harris kernels. The focus of our study is on estimates for operator norms and approximation orders via moduli of continuity.

46 citations

Journal ArticleDOI
TL;DR: The results of this study strongly suggest that using the O3/PS process is a promising solution to reduce SMX-TMP contamination in water matrices.

46 citations

Journal ArticleDOI
TL;DR: In this paper, the stability of vitamers: thiamine, riboflavin, nicotinic acid and nicotinamide, Pantothenic acid, pyridoxine and pyrithoxal, as well as soluble and insoluble dietary fiber was studied in a rye sourdough bread process.

46 citations

Journal ArticleDOI
TL;DR: The results suggest new mechanisms involved in endometrial maturation, involving genes like LINC01320, SLC8A1 and GGTA1P, described for the first time in context ofendometrial receptivity.
Abstract: Study question Does cellular composition of the endometrial biopsy affect the gene expression profile of endometrial whole-tissue samples? Summary answer The differences in epithelial and stromal cell proportions in endometrial biopsies modify the whole-tissue gene expression profiles and affect the results of differential expression analyses. What is already known Each cell type has its unique gene expression profile. The proportions of epithelial and stromal cells vary in endometrial tissue during the menstrual cycle, along with individual and technical variation due to the method and tools used to obtain the tissue biopsy. Study design, size, duration Using cell-population specific transcriptome data and computational deconvolution approach, we estimated the epithelial and stromal cell proportions in whole-tissue biopsies taken during early secretory and mid-secretory phases. The estimated cellular proportions were used as covariates in whole-tissue differential gene expression analysis. Endometrial transcriptomes before and after deconvolution were compared and analysed in biological context. Participants/material, setting, methods Paired early- and mid-secretory endometrial biopsies were obtained from 35 healthy, regularly cycling, fertile volunteers, aged 23-36 years, and analysed by RNA sequencing. Differential gene expression analysis was performed using two approaches. In one of them, computational deconvolution was applied as an intermediate step to adjust for the proportions of epithelial and stromal cells in the endometrial biopsy. The results were then compared to conventional differential expression analysis. Ten paired endometrial samples were analysed with qPCR to validate the results. Main results and the role of chance The estimated average proportions of stromal and epithelial cells in early secretory phase were 65% and 35%, and during mid-secretory phase, 46% and 54%, respectively, correlating well with the results of histological evaluation (r = 0.88, P = 1.1 × 10-6). Endometrial tissue transcriptomic analysis showed that approximately 26% of transcripts (n = 946) differentially expressed in receptive endometrium in cell-type unadjusted analysis also remain differentially expressed after adjustment for biopsy cellular composition. However, the other 74% (n = 2645) become statistically non-significant after adjustment for biopsy cellular composition, underlining the impact of tissue heterogeneity on differential expression analysis. The results suggest new mechanisms involved in endometrial maturation, involving genes like LINC01320, SLC8A1 and GGTA1P, described for the first time in context of endometrial receptivity. Large-scale data The RNA-seq data presented in this study is deposited in the Gene Expression Omnibus database with accession number GSE98386. Limitations reasons for caution Only dominant endometrial cell types were considered in gene expression profile deconvolution; however, other less frequent endometrial cell types also contribute to the whole-tissue gene expression profile. Wider implications of the findings The better understanding of molecular processes during transition from pre-receptive to receptive endometrium serves to improve the effectiveness and personalization of assisted reproduction protocols. Biopsy cellular composition should be taken into account in future endometrial 'omics' studies, where tissue heterogeneity could potentially influence the results. Study funding/competing interest(s) This study was funded by: Estonian Ministry of Education and Research (grant IUT34-16); Enterprise Estonia (EU48695); the EU-FP7 Eurostars program (NOTED, EU41564); the EU-FP7 Marie Curie Industry-Academia Partnerships and Pathways (SARM, EU324509); Horizon 2020 innovation program (WIDENLIFE, EU692065); MSCA-RISE-2015 project MOMENDO (No 691058) and the Miguel Servet Program Type I of Instituto de Salud Carlos III (CP13/00038); Spanish Ministry of Economy, Industry and Competitiveness (MINECO) and European Regional Development Fund (FEDER): grants RYC-2016-21199 and ENDORE SAF2017-87526. Authors confirm no competing interests.

46 citations

Journal ArticleDOI
TL;DR: In this article, the lattice parameters for all powders were calculated from X-ray diffraction (XRD), Raman spectroscopy, photoluminescence (PL) and quantum efficiency (QE) measurements.

46 citations


Authors

Showing all 3757 results

NameH-indexPapersCitations
James Chapman8248336468
Alexandre Alexakis6754017247
Bernard Waeber5637035335
Peter A. Andrekson5457312042
Charles S. Peirce5116711998
Lars M. Blank493018011
Fushuan Wen494659189
Mati Karelson4820710210
Ago Samoson461198807
Zebo Peng453597312
Petru Eles443006749
Vijai Kumar Gupta433016901
Eero Vasar432636930
Rik Ossenkoppele421926839
Tõnis Timmusk4110511056
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202342
2022107
2021883
2020951
2019882
2018745