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Institution

Aalto University

EducationEspoo, Finland
About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Carbon nanotube. The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a new hybrid thermodynamic-structural approach to the coarse-graining of polymers is proposed, which uses mainly thermodynamic properties as targets in the parameterization.
Abstract: We hereby introduce a new hybrid thermodynamic-structural approach to the coarse-graining of polymers. The new model is developed within the framework of the MARTINI force-field (Marrink et al., J. Phys. Chem. B, 2007, 111, 7812), which uses mainly thermodynamic properties as targets in the parameterization. We refine the MARTINI procedure by including one additional target property related to the structure of the polymer, namely the radius of gyration. The force-field optimization is mainly based on experimental data. We test our procedure on polystyrene, a standard benchmark for coarse-grained (CG) polymer force-fields. Our model preserves the backbone-ring structure of the molecule, with each monomer represented by four CG beads. Structural properties in the melt are well reproduced, and their scaling with chain length agrees with the available experimental data. The time conversion factor between the CG and the atomistic simulations is nearly constant over a wide temperature range, and the CG force-field shows reasonable transferability between 350 and 600 K. The model is computationally efficient and polymer melts can be simulated over length scales of tens of nanometres and time scales of tens of microseconds. Finally, we tested our model in dilute conditions. The collapse of the polymer chains in a bad solvent and the swelling in a good solvent could be reproduced.

223 citations

Journal ArticleDOI
TL;DR: Tests with practical forest inventory data show that the method performs noticeably better than other applications of k-NN estimation methods in forest inventories, and that the problem of biases in the species volume predictions can for example, almost completely be overcome with this new approach.

222 citations

Journal ArticleDOI
Paolo Giommi1, G. Polenta2, G. Polenta1, Anne Lähteenmäki3, Anne Lähteenmäki4, D. J. Thompson5, M. Capalbi1, S. Cutini1, Dario Gasparrini1, J. González-Nuevo6, Jonathan León-Tavares3, M. López-Caniego7, Mn Mazziotta8, C. Monte9, C. Monte8, M. Perri1, S. Rainò9, S. Rainò8, G. Tosti10, G. Tosti8, Andrea Tramacere11, F. Verrecchia1, Hugh D. Aller12, M. F. Aller12, E. Angelakis13, Denis Bastieri14, Denis Bastieri8, Andrei Berdyugin15, Anna Bonaldi16, Laura Bonavera17, Laura Bonavera6, Carlo Burigana2, David N. Burrows18, S. Buson8, E. Cavazzuti1, G. Chincarini19, Sergio Colafrancesco2, L. Costamante20, F. Cuttaia2, Filippo D'Ammando2, G. de Zotti2, G. de Zotti6, M. Frailis2, Lars Fuhrmann13, S. Galeotta2, F. Gargano8, N. Gehrels5, Nicola Giglietto9, Nicola Giglietto8, Francesco Giordano9, Marcello Giroletti2, E. Keihänen21, O. King22, Thomas P. Krichbaum13, Anthony Lasenby23, N. Lavonen3, Charles R. Lawrence22, C. Leto1, Elina Lindfors15, Nazzareno Mandolesi2, Marcella Massardi2, Walter Max-Moerbeck22, Peter F. Michelson20, M. G. Mingaliev24, Paolo Natoli1, Paolo Natoli25, Paolo Natoli2, I. Nestoras13, E. Nieppola3, E. Nieppola15, Kari Nilsson15, B. Partridge26, Vasiliki Pavlidou22, T. J. Pearson22, Pietro Procopio2, Jörg P. Rachen13, Anthony C. S. Readhead22, R. Reeves22, A. Reimer20, R. Reinthal15, S. Ricciardi2, Joseph L. Richards22, D. Riquelme, Jari Saarinen15, Anna Sajina27, M. Sandri2, P. Savolainen3, A. Sievers, A. Sillanpää15, Yu. V. Sotnikova24, Mark Stevenson22, G. Tagliaferri2, L. O. Takalo15, Joni Tammi3, D. Tavagnacco2, Luca Terenzi2, L. Toffolatti28, Merja Tornikoski3, Corrado Trigilio2, M. Turunen3, G. Umana2, H. Ungerechts, F. Villa2, Jingwen Wu29, Andrea Zacchei2, J. A. Zensus13, Xu Zhou29 
TL;DR: In this paper, simultaneous Planck, Swift, Fermi, and ground-based data for 105 blazars belonging to three samples with flux limits in the soft X-ray, hard Xray, and gamma-ray bands, with additional 5 GHz flux-density limits to ensure a good probability of a Planck detection.
Abstract: We present simultaneous Planck, Swift, Fermi, and ground-based data for 105 blazars belonging to three samples with flux limits in the soft X-ray, hard X-ray, and gamma-ray bands, with additional 5 GHz flux-density limits to ensure a good probability of a Planck detection. We compare our results to those of a companion paper presenting simultaneous Planck and multi-frequency observations of 104 radio-loud northern active galactic nuclei selected at radio frequencies. While we confirm several previous results, our unique data set allows us to demonstrate that the selection method strongly influences the results, producing biases that cannot be ignored. Almost all the BL Lac objects have been detected by the Fermi Large Area Telescope (LAT), whereas 30% to 40% of the flat-spectrum radio quasars (FSRQs) in the radio, soft X-ray, and hard X-ray selected samples are still below the gamma-ray detection limit even after integrating 27 months of Fermi-LAT data. The radio to sub-millimetre spectral slope of blazars is quite flat, with (alpha) approx 0 up to about 70GHz, above which it steepens to (alpha) approx -0.65. The BL Lacs have significantly flatter spectra than FSRQs at higher frequencies. The distribution of the rest-frame synchrotron peak frequency (nu(sup s)(sub peak)) in the spectral energy distribution (SED) of FSRQs is the same in all the blazar samples with (nu(sup s)(sub peak)) = 10(exp 13.1 +/- 0.1) Hz, while the mean inverse Compton peak frequency, (nu(sup IC)(sub peak)), ranges from 10(exp 21) to 10(exp 22) Hz. The distributions of nu(sup s)(sub peak) and nu(sup IC)(sub peak) of BL Lacs are much broader and are shifted to higher energies than those of FSRQs; their shapes strongly depend on the selection method. The Compton dominance of blazars. defined as the ratio of the inverse Compton to synchrotron peak luminosities, ranges from less than 0.2 to nearly 100, with only FSRQs reaching values larger than about 3. Its distribution is broad and depends strongly on the selection method, with gamma-ray selected blazars peaking at approx 7 or more, and radio-selected blazars at values close to 1, thus implying that the common assumption that the blazar power budget is largely dominated by high-energy emission is a selection effect. A comparison of our multi-frequency data with theoretical predictions shows that simple homogeneous SSC models cannot explain the simultaneous SEDs of most of the gamma-ray detected blazars in all samples. The SED of the blazars that were not detected by Fermi~LAT may instead be consistent with SSC emission. Our data challenge the correlation between bolometric luminosity and nu(sup s)(sub peak) predicted by the blazar sequence.

222 citations

Journal ArticleDOI
TL;DR: An hidden Markov model (HMM)-based speech synthesizer that utilizes glottal inverse filtering for generating natural sounding synthetic speech and the quality is clearly better compared to two HMM-based speech synthesis systems based on widely used vocoder techniques.
Abstract: This paper describes an hidden Markov model (HMM)-based speech synthesizer that utilizes glottal inverse filtering for generating natural sounding synthetic speech. In the proposed method, speech is first decomposed into the glottal source signal and the model of the vocal tract filter through glottal inverse filtering, and thus parametrized into excitation and spectral features. The source and filter features are modeled individually in the framework of HMM and generated in the synthesis stage according to the text input. The glottal excitation is synthesized through interpolating and concatenating natural glottal flow pulses, and the excitation signal is further modified according to the spectrum of the desired voice source characteristics. Speech is synthesized by filtering the reconstructed source signal with the vocal tract filter. Experiments show that the proposed system is capable of generating natural sounding speech, and the quality is clearly better compared to two HMM-based speech synthesis systems based on widely used vocoder techniques.

222 citations

Journal ArticleDOI
TL;DR: In this paper, the receiver setup for the Long Baseline observatory (LBA) is described and the authors thank J. A. Romney and R. C. Walker for valuable advice regarding the receiver for their observations.
Abstract: We thank the referee for constructive comments, which helped to improve the paper. We thank J. Romney and R. C. Walker for valuable advice regarding the receiver setup for our observations. The research at Boston University was supported by NASA through a number of Fermi Guest Investigator program grants, most recently NNX14AQ58G. The St. Petersburg University group acknowledges support from the Russian Science Foundation grant 17-12-01029. The research at the IAA-CSIC was supported in part by MINECO through grant AYA2016-80889-P, and several previous ones. I. A. acknowledges support by a Ramon y Cajal grant of the Ministerio de Economia y Competitividad (MINECO) of Spain. The VLBA is an instrument of the Long Baseline Observatory. The Long Baseline Observatory is a facility of the National Science Foundation operated by Associated Universities, Inc. (NNX14AQ58G - NASA through a number of Fermi Guest Investigator program grants; 17-12-01029 - Russian Science Foundation; AYA2016-80889-P - MINECO; Ramon y Cajal grant of the Ministerio de Economia y Competitividad (MINECO) of Spain)

221 citations


Authors

Showing all 10135 results

NameH-indexPapersCitations
John B. Goodenough1511064113741
Ashok Kumar1515654164086
Anne Lähteenmäki11648581977
Kalyanmoy Deb112713122802
Riitta Hari11149143873
Robin I. M. Dunbar11158647498
Andreas Richter11076948262
Mika Sillanpää96101944260
Muhammad Farooq92134137533
Ivo Babuška9037641465
Merja Penttilä8730322351
Andries Meijerink8742629335
T. Poutanen8612033158
Sajal K. Das85112429785
Kalle Lyytinen8442627708
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023101
2022342
20212,842
20203,030
20192,749
20182,719