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Institution

Leibniz University of Hanover

EducationHanover, Niedersachsen, Germany
About: Leibniz University of Hanover is a education organization based out in Hanover, Niedersachsen, Germany. It is known for research contribution in the topics: Finite element method & Population. The organization has 14283 authors who have published 29845 publications receiving 682152 citations.


Papers
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Journal ArticleDOI
TL;DR: The field of metal–organic framework based mixed matrix membranes (M4s) is critically reviewed, with special emphasis on their application in CO2 capture during energy generation.
Abstract: The field of metal–organic framework based mixed matrix membranes (M4s) is critically reviewed, with special emphasis on their application in CO2 capture during energy generation. After introducing the most relevant parameters affecting membrane performance, we define targets in terms of selectivity and productivity based on existing literature on process design for pre- and post-combustion CO2 capture. Subsequently, the state of the art in M4s is reviewed against these targets. Because final application of these membranes will only be possible if thin separation layers can be produced, the latest advances in the manufacture of M4 hollow fibers are discussed. Finally, the recent efforts in understanding the separation performance of these complex composite materials and future research directions are outlined.

673 citations

Journal ArticleDOI
TL;DR: The remarkable progress made in the preparation and characterization of zeolite membranes during the last few years has stimulated several industrial R&D projects exploiting the shape-selectivity of ZO membranes in mass separation as mentioned in this paper.

665 citations

Journal ArticleDOI
TL;DR: The authors examined consumer confidence as a proxy for individual investor sentiment and found that when sentiment is high, future stock returns tend to be lower and vice versa, and employed a cross-sectional perspective and provided evidence that the impact of sentiment on stock returns is higher for countries which have less market integrity and which are culturally more prone to herd-like behavior and overreaction.

658 citations

Book ChapterDOI
08 Sep 2018
TL;DR: This work proposes a method that combines a single hand-held camera and a set of Inertial Measurement Units (IMUs) attached at the body limbs to estimate accurate 3D poses in the wild and obtains an accuracy of 26 mm, which makes it accurate enough to serve as a benchmark for image-based 3D pose estimation in theWild.
Abstract: In this work, we propose a method that combines a single hand-held camera and a set of Inertial Measurement Units (IMUs) attached at the body limbs to estimate accurate 3D poses in the wild. This poses many new challenges: the moving camera, heading drift, cluttered background, occlusions and many people visible in the video. We associate 2D pose detections in each image to the corresponding IMU-equipped persons by solving a novel graph based optimization problem that forces 3D to 2D coherency within a frame and across long range frames. Given associations, we jointly optimize the pose of a statistical body model, the camera pose and heading drift using a continuous optimization framework. We validated our method on the TotalCapture dataset, which provides video and IMU synchronized with ground truth. We obtain an accuracy of 26 mm, which makes it accurate enough to serve as a benchmark for image-based 3D pose estimation in the wild. Using our method, we recorded 3D Poses in the Wild (3DPW), a new dataset consisting of more than 51, 000 frames with accurate 3D pose in challenging sequences, including walking in the city, going up-stairs, having coffee or taking the bus. We make the reconstructed 3D poses, video, IMU and 3D models available for research purposes at http://virtualhumans.mpi-inf.mpg.de/3DPW.

649 citations

Journal ArticleDOI
Marnix H. Medema1, Marnix H. Medema2, Renzo Kottmann2, Pelin Yilmaz2  +161 moreInstitutions (84)
TL;DR: This work proposes the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard, to facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters.
Abstract: A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.

633 citations


Authors

Showing all 14621 results

NameH-indexPapersCitations
Hyun-Chul Kim1764076183227
Peter Zoller13473476093
J. R. Smith1341335107641
Chao Zhang127311984711
Benjamin William Allen12480787750
J. F. J. van den Brand12377793070
J. H. Hough11790489697
Hans-Peter Seidel112121351080
Karsten Danzmann11275480032
Bruce D. Hammock111140957401
Benno Willke10950874673
Roman Schnabel10858971938
Jan Harms10844776132
Hartmut Grote10843472781
Ik Siong Heng10742371830
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023221
2022520
20212,280
20202,210
20192,105
20181,959