Institution
Tallinn University of Technology
Education•Tallinn, 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.
Topics: European union, Oil shale, Thin film, Nonlinear system, Microstructure
Papers published on a yearly basis
Papers
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01 Jan 2009TL;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
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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
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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
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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
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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
Name | H-index | Papers | Citations |
---|---|---|---|
James Chapman | 82 | 483 | 36468 |
Alexandre Alexakis | 67 | 540 | 17247 |
Bernard Waeber | 56 | 370 | 35335 |
Peter A. Andrekson | 54 | 573 | 12042 |
Charles S. Peirce | 51 | 167 | 11998 |
Lars M. Blank | 49 | 301 | 8011 |
Fushuan Wen | 49 | 465 | 9189 |
Mati Karelson | 48 | 207 | 10210 |
Ago Samoson | 46 | 119 | 8807 |
Zebo Peng | 45 | 359 | 7312 |
Petru Eles | 44 | 300 | 6749 |
Vijai Kumar Gupta | 43 | 301 | 6901 |
Eero Vasar | 43 | 263 | 6930 |
Rik Ossenkoppele | 42 | 192 | 6839 |
Tõnis Timmusk | 41 | 105 | 11056 |