Welcome
OPARU is the OPen Access Repository of Ulm University and Ulm University of Applied Sciences.
Members and affiliates of Ulm University and Ulm University of Applied Sciences can publish via OPARU and thereby make their publications accessible worldwide free of charge. In addition to traditional publication formats, research data can also be published on OPARU. Publications can also be indexed as "metadata only" entries. This means that publication lists can be completely integrated in OPARU.
The bibliography of Ulm University and the bibliography of Ulm University of Applied Sciences are integrated in OPARU and include all publications that originated at the respective institution. Both bibliographies are continuously maintained by the kiz and the THU, respectively.
Via OPARU you can comply with the recommendation of the Open Access Resolution of Ulm University and the Open Access Policy of the THU to self-archive your publications on the institutional repository.
Learn more about OPARU (instructions, features...)
for members and affiliates of Ulm University >>
for THU members >>
Communities
Select a community to browse its collections.
Recently Added
-
Context and Culture affect the Psychometrics of Questionnaires evaluating Speech-based Assistants
(2021)Beitrag zu einer Konferenz
-
An aged bone marrow niche restrains rejuvenated hematopoietic stem cells
(2021)Wissenschaftlicher Artikel
-
A wave equation interpolating between classical and quantum mechanics
(2015)Wissenschaftlicher Artikel
-
A lithium‐free energy‐storage device based on an alkyne‐substituted‐porphyrin complex
(2019)Wissenschaftlicher Artikel
-
The Riemann hypothesis illuminated by the Newton flow of ζ☆We dedicate this paper to the memory of Richard Lewis Arnowitt and his many contributions to general relativity and high energy physics.
(2015)Wissenschaftlicher Artikel
-
Influence of micro-patterning of the growth template on defect reduction and optical properties of non-polar (112ˉ0) GaN
(2020)Wissenschaftlicher Artikel
-
Knockdown of UTX/KDM6A enriches precursor cell populations in urothelial cell cultures and cell lines
(2020)Wissenschaftlicher Artikel
-
Mining digital traces of facebook activity for the prediction of individual differences in tendencies toward social networks use disorder: a machine learning approach
(2022)Wissenschaftlicher Artikel
-
Deep neural networks and machine learning radiomics modelling for prediction of relapse in mantle cell lymphoma
(2022)Wissenschaftlicher Artikel
-
Retrospektive Studie zur Betrachtung von klinischer und endosonographischer Krankheitsaktivität bei PatientInnen mit chronischer Pankreatitis
(2022)Dissertation