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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
TL;DR: In this paper, the authors developed large-scale models linking invertebrate indices of ecological quality to river basin and riparian land cover in France, Slovakia, Estonia and UK, based on Partial Least Squares regressions at national and a hydro-ecoregion (HER) scales.
Abstract: The study of large-scale pressure-impact relationships involves questions of hierarchy and scales. Answers to these questions will help managers define priorities for action to achieve the good ecological status' required by the Water Framework Directive (WFD). The main objectives of our study were 1) to establish the relative impact of pressures that degrade ecological status, especially those caused by agriculture and urbanization, 2) to identify regional patterns in these pressure-impact relationships and 3) to evaluate the relative weight of the pressures acting at the basin and riparian corridor scales, and the possible buffering effect of riparian areas. We developed large-scale models linking invertebrate indices of ecological quality to river basin and riparian land cover in France, Slovakia, Estonia and UK. Invertebrate indices, transformed to Ecological Quality Ratios (EQR), were taken from national monitoring networks. We based the models on Partial Least Squares (PLS) regressions at national and a hydro-ecoregion (HER) scales. The HERs provided a framework for grouping data in terms of natural river features and human activities. The different national methods provided consistent results that indicated the hierarchy of pressures impacting river invertebrates at the European scale. The most salient result was that artificial land cover (e.g. urban and industrial sites) in the river basin represented the pressure with the most negative impact on invertebrate indices, in all countries and regions. The impact of agricultural land cover was more variable. Arable land had a smaller impact than urban areas, and it was even insignificant in some models. The impact of vineyards depended on the natural geographical context. The effect of pastures seemed to be related to the intensity of the livestock they carried. These results supported the concept of regional pathologies for river ecosystems, as land use and anthropogenic influences are closely linked to physical landscape features. The proportion of arable land in the river basin appeared to be a weak predictor of agricultural impacts by itself; the type of cultivation and intensity as well as the proximity to the river must be taken into account. At the riparian corridor scale, the negative impact of artificial areas or arable land and the positive effects of forests and pastures were demonstrated in many regions. The protective effect of riparian forests against mixed agricultural and urban pressures was demonstrated in three regions in France. Riparian corridors appear to be manageable areas, and these results strongly support the idea of including their restoration in priority actions for achieving good ecological status.

63 citations

Journal ArticleDOI
TL;DR: In this paper, a comprehensive study of the catalytic behavior of Fe3+ in the presence of tannic acid during the Fenton-based treatment of chlorophenols-contaminated water was performed.
Abstract: A comprehensive study of the catalytic behaviour of Fe3+ in the presence of tannic acid during the Fenton-based treatment of chlorophenols-contaminated water was performed. The ability of the iron-containing sludge to catalyse the Fenton-based process was assessed and the mechanistic behaviour of tannic acid in the iron dissolution was evaluated. Tannic acid, a constituent of pulp and paper industry water effluent and natural water, enhanced the 2,4,6-trichlorophenol catalytic decomposition in Fe3+-activated H2O2 oxidation system by reducing of the Fe3+. The Fe3+ reductive mechanism by tannic acid incorporated tannic acid–Fe3+ complex formation and decay through an electron transfer reaction to form Fe2+. An indirect measurement of hydroxyl radical (HO ) by the deoxyribose method indicated a considerable increase in HO by Fe3+/H2O2 in the presence of tannic acid. A pseudo-first reaction rate constant of 2,4,6-trichlorophenol degradation by Fe2+/H2O2 was high and close to that of Fe3+/H2O2 with tannic acid. Degradation of tannic acid along with that of 2,4,6-trichlorophenol required optimization of H2O2 and Fe3+ dosages to balance HO formation and scavenging. Acidic reaction media (pH 3.0) and the presence of tannic acid favoured 2,4,6-trichlorophenol degradation by H2O2 oxidation induced by iron dissolved from ferric oxyhydroxide sludge. The reuse of ferric oxyhydroxide sludge as a catalyst source in the Fenton–based process can minimise the production of hazardous solid waste and the overall cost of the treatment. This study highlights the ability of tannic acid-Fe3+ complexes to participate in Fe3+ reductive pathway and, as a result, to allow reuse of non-regenerated ferric oxyhydroxide sludge for activation of H2O2 oxidation in wastewater treatment at acidic pH.

63 citations

Journal ArticleDOI
TL;DR: A new tree-based ensemble multi-task learning method for classication and regression (MT-ExtraTrees), based on Extremely Randomized Trees, which is able to share data between tasks minimizing negative transfer while keeping the ability to learn non-linear solutions and to scale well to large datasets.
Abstract: Multi-task learning is an important area of machine learning that tries to learn multiple tasks simultaneously to improve the accuracy of each individual task. We propose a new tree-based ensemble multi-task learning method for classication and regression (MT-ExtraTrees), based on Extremely Randomized Trees. MTExtraTrees is able to share data between tasks minimizing negative transfer while keeping the ability to learn non-linear solutions and to scale well to large datasets.

63 citations

Journal ArticleDOI
19 Oct 2017-PLOS ONE
TL;DR: Aspergillus clavatonanicus strain MJ31 has prolific antimicrobial potential against both plant and human pathogens and can be exploited for the discovery of new antimicrobial compounds and could be an alternate source for the production of secondary metabolites.
Abstract: Endophytic fungi associated with medicinal plants are reported as potent producers of diverse classes of secondary metabolites. In the present study, an endophytic fungi, Aspergillus clavatonanicus strain MJ31, exhibiting significant antimicrobial activity was isolated from roots of Mirabilis jalapa L., was identified by sequencing three nuclear genes i.e. internal transcribed spacers ribosomal RNA (ITS rRNA), 28S ribosomal RNA (28S rRNA) and translation elongation factor 1- alpha (EF 1α). Ethyl acetate extract of strain MJ31displayed significant antimicrobial potential against Bacillus subtilis, followed by Micrococccus luteus and Staphylococcus aureus with minimum inhibitory concentrations (MIC) of 0.078, 0.156 and 0.312 mg/ml respectively. In addition, the strain was evaluated for its ability to synthesize bioactive compounds by the amplification of polyketide synthase (PKS) and non ribosomal peptide synthetase (NRPS) genes. Further, seven antibiotics (miconazole, ketoconazole, fluconazole, ampicillin, streptomycin, chloramphenicol, and rifampicin) were detected and quantified using UPLC-ESI-MS/MS. Additionally, thermal desorption-gas chromatography mass spectrometry (TD-GC-MS) analysis of strain MJ31 showed the presence of 28 volatile compounds. This is the first report on A. clavatonanicus as an endophyte obtained from M. jalapa. We conclude that A. clavatonanicus strain MJ31 has prolific antimicrobial potential against both plant and human pathogens and can be exploited for the discovery of new antimicrobial compounds and could be an alternate source for the production of secondary metabolites.

63 citations

Book ChapterDOI
17 Nov 2009
TL;DR: This work describes an application of model generation in the context of the database unit testing framework of Visual Studio and uses the satisfiability modulo theories (SMT) solver Z3 in the concrete implementation.
Abstract: We study the problem of generating a database and parameters for a given parameterized SQL query satisfying a given test condition We introduce a formal background theory that includes arithmetic, tuples, and sets, and translate the generation problem into a satisfiability or model generation problem modulo the background theory We use the satisfiability modulo theories (SMT) solver Z3 in the concrete implementation We describe an application of model generation in the context of the database unit testing framework of Visual Studio

63 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