TY  - JOUR
A1  - Tran, Duc Hung
T1  - Multiple corporate governance attributes and the cost of capital – Evidence from Germany
JF  - The British Accounting Review
N2  - This paper investigates the extent to which corporate governance affects the cost of debt and equity capital of German exchange-listed companies. I examine corporate governance along three dimensions: financial information quality, ownership structure and board structure. The results suggest that firms with high levels of financial transparency and bonus compensations face lower cost of equity. In addition, block ownership is negatively related to firms' cost of equity when the blockholders are other firms, managers or founding-family members. Consistent with the conjecture that agency costs increase with firm size, I find significant cost of debt effects only in the largest German companies. Here, the creditors demand lower cost of debt from firms with block ownerships held by corporations or banks. My findings demonstrate that a uniform set of governance attributes is unlikely to satisfy suppliers of debt and equity capital equally.
Y1  - 2018
U6  - https://doi.org/https://doi.org/10.1016/j.bar.2014.02.003
SN  - 0890-8389
VL  - 46
IS  - 2
SP  - 179
EP  - 197
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Yang, Peng-Fei
A1  - Kriechbaumer, Andreas
A1  - Albracht, Kirsten
A1  - Sanno, Maximilian
A1  - Ganse, Bergita
A1  - Koy, Timmo
A1  - Shang, Peng
A1  - brüggemann, Gert-Peter
A1  - Müller, Lars Peter
A1  - Rittweger, Jörn
T1  - A novel optical approach for assessing in vivo bone segment deformation and its application in muscle-bone relationship studies in humans
JF  - Journal of Orthopaedic Translation
Y1  - 2014
U6  - https://doi.org/10.1016/j.jot.2014.07.078
SN  - 2214-0328
SN  - 2214-031X
VL  - 2
IS  - 4
SP  - 238
EP  - 238
PB  - Elsevier
CY  - Singapore
ER  - 
TY  - JOUR
A1  - Arinkin, Vladimir
A1  - Digel, Ilya
A1  - Porst, Dariusz
A1  - Temiz Artmann, Aysegül
A1  - Artmann, Gerhard
T1  - Phenotyping date palm varieties via leaflet cross-sectional imaging and artificial neural network application
JF  - BMC bioinformatics
N2  - Background
True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).

Results
Fluorescence microscopy images of leaflet cross sections have been taken from a set of five date palm tree cultivars (Hewlat al Jouf, Khlas, Nabot Soltan, Shishi, Um Raheem). After features extraction from images, the obtained data have been fed in a multilayer perceptron ANN with backpropagation learning algorithm.

Conclusions
Overall, an accurate result in prediction and differentiation of date palm tree cultivars was achieved with average prediction in tenfold cross-validation is 89.1% and reached 100% in one of the best ANN.
Y1  - 2014
U6  - https://doi.org/10.1186/1471-2105-15-55
SN  - 1471-2105
VL  - 15
IS  - 55
SP  - 1
EP  - 8
ER  -