3,687 research outputs found
Angststörungen
Angststörungen stellen in europäischen Ländern mit einer 1-Jahres-Prävalenz von ca. 14 % die häufigsten psychischen Erkrankungen in der Allgemeinbevölkerung dar (Wittchen et al. 2011). Sie umfassen gemäß der europäischen International Classification of Diseases (ICD-10) die Phobischen Störungen mit der Agoraphobie mit oder ohne Panikstörung, der Sozialen Angststörung und den Spezifischen Phobien sowie die Anderen Angststörungen mit der Panikstörung, der Generalisierten Angststörung und der Diagnose Angst und Depression gemischt. Das vorliegende Kapitel beschäftigt sich mit Besonderheiten und empirischen Befunden zu internet- und mobilbasierten Interventionen (IMIs) bei den genannten Angststörungen
Kinderrechte als Grundlage für Schule und Unterricht
Daniel Bertels, David Rott ; Herausgebende Abteilung: Abteilung Analyse, Planung und Beratun
Planonasus indicus Ebert, Akhilesh & Weigmann
<i>Planonasus indicus</i> Ebert, Akhilesh & Weigmann <p>(Figs. 4E, 15 E–H)</p> <p> Following up on an earlier report of what appeared to be a specimen of the poorly known <i>Planonasus</i> Weigmann, Stehmann & Thiel from Trincomalee Outer Harbor by Ebert <i>et al.</i> (2017), one of the fisheries we targeted was the deep-sea longline fishery in Mutur, Trincomalee Harbor in the Eastern Province. We were fortunate that on the second of the two days we spent at that location, fishers returned with dead bycatch retained for us. Fishing at 350 fathoms, their catch that day included a specimen (SL-107) of <i>Planonasus</i> allowing us to confirm the novelty of this, only the second known member of the genus. The species was recently described as <i>Planonasus indicus</i> (see Ebert <i>et al.</i> 2018). The original description was based on a holotype from India and our specimen from Sri Lanka; the latter has been designated a paratype and deposited in the BRT Ichthyology Collection (BRT-I 0029).</p> <p> Ebert <i>et al.</i> (2017) originally reported this species from Sri Lanka as <i>Planonasus parini</i> Weigmann, Stehmann & Thiel.</p>Published as part of <i>Fernando, Daniel, Bown, Rosalind M. K., Tanna, Akshay, Gobiraj, Ramajeyam, Ralicki, Hannah, Jockusch, Elizabeth L., Ebert, David A., Jensen, Kirsten & Caira, Janine N., 2019, New insights into the identities of the elasmobranch fauna of Sri Lanka, pp. 201-238 in Zootaxa 4585 (2)</i> on page 226, DOI: 10.11646/zootaxa.4585.2.1, <a href="http://zenodo.org/record/2637236">http://zenodo.org/record/2637236</a>
Digitale Phänotypisierung und künstliche Intelligenz
Seit einigen Jahren kommt es zu rasanten Fortschritten in der Mobiltechnologie und auf dem Gebiet der künstlichen Intelligenz (KI)
Web-based Prevention of Major Depression: Research on a web-based guided self-help intervention for adults with subthreshold depression
Cuijpers, W.J.M.J. [Promotor]Berking, M. [Promotor]Ebert, D.D. [Copromotor]Riper, M.M. [Copromotor
Dataset in support of the thesis 'Speech enhancement by using deep learning algorithms'
The source code and audio datasets of my PhD project.
1. https://www.openslr.org/12
LibriSpeech is a corpus of approximately 1000 hours of 16kHz read English speech, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.
Acoustic models, trained on this data set, are available at kaldi-asr.org and language models, suitable for evaluation can be found at http://www.openslr.org/11/.
For more information, see the paper "LibriSpeech: an ASR corpus based on public domain audio books", Vassil Panayotov, Guoguo Chen, Daniel Povey and Sanjeev Khudanpur, ICASSP 2015
2.https://www.openslr.org/17
MUSAN is a corpus of music, speech, and noise recordings.
This work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1232825 and by Spoken Communications.
You can cite the data using the following BibTeX entry:
@misc{musan2015,
author = {David Snyder and Guoguo Chen and Daniel Povey},
title = {{MUSAN}: {A} {M}usic, {S}peech, and {N}oise {C}orpus},
year = {2015},
eprint = {1510.08484},
note = {arXiv:1510.08484v1}
}
3. source_code.zip
The program from parts of my PhD project.
4.SJ_EXP.zip
The program of the subjective experiment corresponding to the last chapter.</span
07291 Summary – Scientific Visualization
Scientific visualization (SV) is concerned with the use of computer-generated images to aid the understanding, analysis and manipulation of data. Since its beginning in the early 90's, the techniques of SV have aided scientists, engineers, medical practitioners, and others in the study of a wide variety of data sets including, for example, high performance computing simulations, measured data from scanners (CAT, MR, confocal microscopy), internet traffic, and financial records. One of the important themes being nurtured under the aegis of Scientific Visualization is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes and simulations involving voluminous data sets across diverse scientific disciplines. Since vision dominates our sensory input, strong efforts have been made to bring the mathematical abstraction and modeling to our eyes through the mediation of computer graphics. This interplay between various application areas and their specific problem solving visualization techniques was emphasized in the proposed seminar
07291 Abstracts Collection – Scientific Visualization
From 15.07. to 20.07.07, the Dagstuhl Seminar 07291 ``Scientific Visualization'' was held in the International Conference and Research Center (IBFI),Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
Author correction: obesity and ethnicity alter gene expression in skin
Daniel Butler was omitted from the author list in the original version of this Article. The Author contributions section now reads: “J.M.W. designed, conducted, and contributed to the writing of the manuscript, prepared Fig. 1. S.G. evaluated and did statistical analysis on the skin and fat samples, prepared Figs. 2–9. J.O.A. evaluated and contributed to writing the manuscript. D.B prepared and sequenced DNA libraries for the skin microbiota data, and wrote the applicable parts of the methods section. C.M. analyzed and wrote up the skin microbiota data, prepared Fig. 10. All authors have read the manuscript and approved its contents. D.D. analyzed and wrote up the skin microbiota data. S.Z. ran and analyzed the skin metabolite data. J.S. assisted in design, analysis and wrote up the skin metabolite data. J.K. assisted in analysis write up of skin and fat data. J.L.B. assisted in analysis, interpretation and writing of the manuscript. P.R.H. designed, analyzed, interpreted the data, and was the primary author of the manuscript.” This has been corrected in the PDF and HTML versions of the Article, and in the accompanying Supplementary Information file.</p
Ethnic identity, political identity and ethnic conflict: simulating the effect of congruence between the two identities on ethnic violence and conflict
This thesis outlines and presents an alternative hypothetical process to the emergence of ethnic conflict. Ethnic conflicts, rather than being dependent upon pre-existing 'ancient hatreds', are instead the result of a congruence between ethnic and political identity which grants individuals the ability to use ethnicity to identify and eliminate political threats. This hypothesis is formed by the examination of three case studies of ethnic conflict: Lebanon, Northern Ireland and Croatia. This hypothesis is then formalised and tested using an agent based simulation in which agent interactions are dependent upon ethnic and political identity and the congruence between the two. As predicted there was a strong positive correlation between how accurately ethnic identity reflected political identity and the level of ethnically motivated violence in the simulation, although the relationship was not linear. Furthermore the effect of a shift in congruence was found to be roughly comparable to the effect of initialising agents with a moderate level of pre-existing ethnic antagonism
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