@article{JahnkeRousselHombachetal.2016,
  author    = {Jahnke, Siegfried and Roussel, Johanna and Hombach, Thomas and Kochs, Johannes and Fischbach, Andreas and Huber, Gregor and Scharr, Hanno},
  title     = {phenoSeeder - A robot system for automated handling and phenotyping of individual seeds},
  series = {Plant physiology},
  volume    = {172},
  journal   = {Plant physiology},
  number    = {3},
  publisher = {Oxford University Press},
  address   = {Oxford},
  issn      = {0032-0889},
  doi       = {10.1104/pp.16.01122},
  pages     = {1358 -- 1370},
  year      = {2016},
  abstract  = {The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning methods delivering only two-dimensional data, often termed seed size. However, three-dimensional traits, such as the volume or mass of single seeds, are very rarely determined in routine measurements. Here, we introduce a device named phenoSeeder, which enables the handling and phenotyping of individual seeds of very different sizes. The system consists of a pick-and-place robot and a modular setup of sensors that can be versatilely extended. Basic biometric traits detected for individual seeds are two-dimensional data from projections, three-dimensional data from volumetric measures, and mass, from which seed density is also calculated. Each seed is tracked by an identifier and, after phenotyping, can be planted, sorted, or individually stored for further evaluation or processing (e.g. in routine seed-to-plant tracking pipelines). By investigating seeds of Arabidopsis (Arabidopsis thaliana), rapeseed (Brassica napus), and barley (Hordeum vulgare), we observed that, even for apparently round-shaped seeds of rapeseed, correlations between the projected area and the mass of seeds were much weaker than between volume and mass. This indicates that simple projections may not deliver good proxies for seed mass. Although throughput is limited, we expect that automated seed phenotyping on a single-seed basis can contribute valuable information for applications in a wide range of wild or crop species, including seed classification, seed sorting, and assessment of seed quality.},
  language  = {en}
}
@article{BialonskiCaronSchloenetal.2016,
  author    = {Bialonski, Stephan and Caron, David A. and Schloen, Julia and Feudel, Ulrike and Kantz, Holger and Moorthi, Stefanie D.},
  title     = {Phytoplankton dynamics in the Southern California Bight indicate a complex mixture of transport and biology},
  series = {Journal of Plankton Research},
  volume    = {38},
  journal   = {Journal of Plankton Research},
  number    = {4},
  publisher = {Oxford University Press},
  address   = {Oxford},
  issn      = {1464-3774},
  doi       = {10.1093/plankt/fbv122},
  pages     = {1077 -- 1091},
  year      = {2016},
  abstract  = {The stimulation and dominance of potentially harmful phytoplankton taxa at a given locale and time are determined by local environmental conditions as well as by transport to or from neighboring regions. The present study investigated the occurrence of common harmful algal bloom (HAB) taxa within the Southern California Bight, using cross-correlation functions to determine potential dependencies between HAB taxa and environmental factors, and potential links to algal transport via local hydrography and currents. A simulation study, in which Lagrangian particles were released, was used to assess travel times due to advection by prevailing ocean currents in the bight. Our results indicate that transport of some taxa may be an important mechanism for the expansion of their distributions into other regions, which was supported by mean travel times derived from our simulation study and other literature on ocean currents in the Southern California Bight. In other cases, however, phytoplankton dynamics were rather linked to local environmental conditions, including coastal upwelling events. Overall, our study shows that complex current patterns in the Southern California Bight may contribute significantly to the formation and expansion of HABs in addition to local environmental factors determining the spatiotemporal dynamics of phytoplankton blooms.},
  language  = {en}
}
@article{DiktaReisselHarlass2016,
  author    = {Dikta, Gerhard and Reißel, Martin and Harlaß, Carsten},
  title     = {Semi-parametric survival function estimators deduced from an identifying Volterra type integral equation},
  series = {Journal of multivariate analysis},
  journal   = {Journal of multivariate analysis},
  number    = {147},
  publisher = {Elsevier},
  address   = {Amsterdam},
  doi       = {10.1016/j.jmva.2016.02.008},
  pages     = {273 -- 284},
  year      = {2016},
  abstract  = {Based on an identifying Volterra type integral equation for randomly right censored observations from a lifetime distribution function F, we solve the corresponding estimating equation by an explicit and implicit Euler scheme. While the first approach results in some known estimators, the second one produces new semi-parametric and pre-smoothed Kaplan-Meier estimators which are real distribution functions rather than sub-distribution functions as the former ones are. This property of the new estimators is particular useful if one wants to estimate the expected lifetime restricted to the support of the observation time. Specifically, we focus on estimation under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. We show that some estimated linear functionals which are based on the new semi-parametric estimator are strong consistent, asymptotically normal, and efficient under SRCM. In a small simulation study, the performance of the new estimator is illustrated under moderate sample sizes. Finally, we apply the new estimator to a well-known real dataset.},
  language  = {en}
}
@article{SteinbauerFerrein2016,
  author    = {Steinbauer, Gerald and Ferrein, Alexander},
  title     = {20 Years of RoboCup},
  series = {KI - K{\"u}nstliche Intelligenz},
  volume    = {30},
  journal   = {KI - K{\"u}nstliche Intelligenz},
  number    = {3-4},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1610-1987},
  doi       = {10.1007/s13218-016-0442-z},
  pages     = {221 -- 224},
  year      = {2016},
  language  = {en}
}