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
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TL;DR: In this paper, the authors identify key antecedents and consequences of tourism customer engagement, which remain nebulous to date, drawing on a service-dominant (S-D) logic perspective.
Abstract: Drawing on a service-dominant (S-D) logic perspective, this study identifies key antecedents and consequences of tourism customer engagement, which remain nebulous to date. We develop a structural ...
165 citations
TL;DR: Considering an excellent correlation between both formats, 96-well microplate Flash Assay can be successfully used for high throughput evaluation of harmful properties of chemicals (including organic and inorganic NPs) to bacteria.
165 citations
TL;DR: In this article, a simulation approach developed by Sugita (the computer model POLLSCAPE) which uses models based on the theory of pollen analysis is presented together with examples of application, each of which explores a possible use of the POLLANDCAL tools and a means of validating or evaluating the models with empirical data.
Abstract: Information on past land cover in terms of absolute areas of different landscape units (forest, open land, pasture land, cultivated land, etc.) at local to regional scales is needed to test hypotheses and answer questions related to climate change (e.g. feedbacks effects of land-cover change), archaeological research, and nature conservancy (e.g. management strategy). The palaeoecological technique best suited to achieve quantitative reconstruction of past vegetation is pollen analysis. A simulation approach developed by Sugita (the computer model POLLSCAPE) which uses models based on the theory of pollen analysis is presented together with examples of application. POLLSCAPE has been adopted as the central tool for POLLANDCAL (POLlen/LANdscape CALibration), an international research network focusing on this topic. The theory behind models of the pollen–vegetation relationship and POLLSCAPE is reviewed. The two model outputs which receive greatest attention in this paper are the relevant source area of pollen (RSAP) and pollen loading in mires and lakes. Six examples of application of POLLSCAPE are presented, each of which explores a possible use of the POLLANDCAL tools and a means of validating or evaluating the models with empirical data. The landscape and vegetation factors influencing the size of the RSAP, the importance of pollen productivity estimates (PPEs) for the model outputs, the detection of small and rare patches of plant taxa in pollen records, and quantitative reconstructions of past vegetation and landscapes are discussed on the basis of these examples. The simulation approach is seen to be useful both for exploring different vegetation/landscape scenarios and for refuting hypotheses.
164 citations
Imperial College London1, Central European Institute of Technology2, University of the Witwatersrand3, University of São Paulo4, University of Manchester5, University of Western Australia6, Saint Joseph's University7, Hamad Medical Corporation8, Sultan Qaboos University9, Medical University of Vienna10, Oslo University Hospital11, Institute of Chartered Accountants of Nigeria12, Gdańsk Medical University13, Hebrew University of Jerusalem14, Ljubljana University Medical Centre15, McGill University Health Centre16, Ege University17, University of Belgrade18, National University of Singapore19, University of Latvia20, University of Ioannina21, Capital Medical University22, National Health Laboratory Service23, Heidelberg University24, Kyrgyz State Medical Academy25, University of Basel26, Academy of Medical Sciences, United Kingdom27, Universiti Teknologi MARA28, University of Copenhagen29, University of Debrecen30, Vilnius University31, Sofia Medical University32, University of Zagreb33, University of Benin34, Mashhad University of Medical Sciences35, United Arab Emirates University36, National Taiwan University37, Khoo Teck Puat Hospital38, University of Malta39, The Chinese University of Hong Kong40, National Institutes of Health41, Universidad Autónoma de Guadalajara42, Tallinn University of Technology43, Slovak Medical University44, University of Helsinki45, Osaka University46, Medical University of Łódź47, Linköping University48, University of the Philippines49, Technische Universität München50, Hacettepe University51, Nanyang Technological University52, University of Milan53
TL;DR: FH is a recognised public health concern, with overall suboptimal identification and under-treatment, and efforts and initiatives to improve FH knowledge and management are underway, but support from health authorities and better funding are greatly needed.
161 citations
TL;DR: This paper explored the equilibrium levels of China's real and nominal exchange rates using a Johansen cointegration framework and found that the renminbi is somewhat undervalued against the dollar, but the misalignment is not nearly as exaggerated as many popular claims.
Abstract: Given that the value of China's currency has been hot topic recently, this paper explores the equilibrium levels of China's real and nominal exchange rates. Employing a Johansen cointegration framework, we focus on the behavioral equilibrium exchange rate (BEER) and permanent equilibrium exchange rate (PEER) models. Our results suggest that, while the renminbi is somewhat undervalued against the dollar, the misalignment is not nearly as exaggerated as many popular claims.
161 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 |