Technische Universität Darmstadt

About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.

A plasma membrane-bound enzyme of tobacco roots catalyses the formation of nitric oxide from nitrite.

Abstract: Purified plasma membranes (PMs) of tobacco (Nicotiana tabacum L. cv. Samsun) roots exhibited a nitrite-reducing enzyme activity that resulted in nitric oxide (NO) formation. This enzyme activity was not detected in soluble protein fractions or in PM vesicles of leaves. At the pH optimum of pH 6.0, nitrite was reduced to NO with reduced cytochrome c as electron donor at a rate comparable to the nitrate-reducing activity of root-specific succinate-dependent PM-bound nitrate reductase (PM-NR). The hitherto unknown PM-bound nitrite: NO-reductase (NI-NOR) was insensitive to cyanide and anti-NR IgG and thereby proven to be different from PM-NR. Furthermore, PM-NR and NI-NOR were separated by gel-filtration chromatography and apparent molecular masses of 310 kDa for NI-NOR and 200 kDa for PM-NR were estimated. The PM-associated NI-NOR may reduce the apoplastic nitrite produced by PM-NR in vivo and may play a role in nitrate signalling via NO formation.

Carbohydrates as organic raw materials.

Abstract: In view of the impending transition of chemical industry from depleting fossil raw materials to renewable feedstocks — the end of cheap oil is predicted around 2040 — this account gives an overview on chemically and enzymatically transforming carbohydrates, by far the major part of the annually regrowing biomass, into products with versatile industrial application profiles and the potential to eventually replace those presently derived from petrochemical sources. The article contains sections titled: 1. Introduction 2. Availability of Carbohydrates 3. Current Nonfood Industrial Products from Sugars 3.1. Ethanol 3.2. Furfural 3.3 d-Sorbitol 3.4 Lactic Acid and Polylactic Acid (PLA) 3.5. Sugar-Based Surfactants 3.5.1. ‘Sorbitan’ Esters 3.5.2. N-Methyl-N-acyl-glucamides (NMCA) 3.5.3. Alkylpolyglucosides (APG) 3.5.4. Sucrose Fatty Acid Monoesters 3.6. Pharmaceuticals and Vitamins 4. Toward Further Sugar-based Chemicals: Potential Development Lines 4.1. Furan Compounds 4.1.1. 5-Hydroxymethylfurfural (HMF) 4.1.2. 2,5-Dimethylfuran (DMF) 4.1.3. Furans with a Tetrahydroxybutyl Side Chain 4.2. Dihydropyrones 4.3. Sugar-Derived Unsaturated Nitrogen Heterocycles 4.3.1. Pyrroles 4.3.2. Pyrazoles 4.3.3. Imidazoles 4.3.4. 3-Pyridinols 4.4. Toward Sugar-Based Aromatic Chemicals 4.5. Microbial Conversion of Six-Carbon-Sugars into Simple Carboxylic Acids and Alcohols 4.5.1. Carboxylic Acids 4.5.2. Potential Sugar-Based Alcohol Commodities by Microbial Conversions 4.6. Chemical Conversion of Sugars into Carboxylic Acids 4.7. Biopolymers from Polymerizable Sugar Derivatives 4.7.1. Synthetic Biopolyesters 4.7.2. Microbial Polyesters 4.7.3. Polyamides 5. Outlook 6. References

Airborne observations of the Eyjafjalla volcano ash cloud over Europe during air space closure in April and May 2010

Abstract: . Airborne lidar and in-situ measurements of aerosols and trace gases were performed in volcanic ash plumes over Europe between Southern Germany and Iceland with the Falcon aircraft during the eruption period of the Eyjafjalla volcano between 19 April and 18 May 2010. Flight planning and measurement analyses were supported by a refined Meteosat ash product and trajectory model analysis. The volcanic ash plume was observed with lidar directly over the volcano and up to a distance of 2700 km downwind, and up to 120 h plume ages. Aged ash layers were between a few 100 m to 3 km deep, occurred between 1 and 7 km altitude, and were typically 100 to 300 km wide. Particles collected by impactors had diameters up to 20 μm diameter, with size and age dependent composition. Ash mass concentrations were derived from optical particle spectrometers for a particle density of 2.6 g cm−3 and various values of the refractive index (RI, real part: 1.59; 3 values for the imaginary part: 0, 0.004 and 0.008). The mass concentrations, effective diameters and related optical properties were compared with ground-based lidar observations. Theoretical considerations of particle sedimentation constrain the particle diameters to those obtained for the lower RI values. The ash mass concentration results have an uncertainty of a factor of two. The maximum ash mass concentration encountered during the 17 flights with 34 ash plume penetrations was below 1 mg m−3. The Falcon flew in ash clouds up to about 0.8 mg m−3 for a few minutes and in an ash cloud with approximately 0.2 mg m−3 mean-concentration for about one hour without engine damage. The ash plumes were rather dry and correlated with considerable CO and SO2 increases and O3 decreases. To first order, ash concentration and SO2 mixing ratio in the plumes decreased by a factor of two within less than a day. In fresh plumes, the SO2 and CO concentration increases were correlated with the ash mass concentration. The ash plumes were often visible slantwise as faint dark layers, even for concentrations below 0.1 mg m−3. The large abundance of volatile Aitken mode particles suggests previous nucleation of sulfuric acid droplets. The effective diameters range between 0.2 and 3 μm with considerable surface and volume contributions from the Aitken and coarse mode aerosol, respectively. The distal ash mass flux on 2 May was of the order of 500 (240–1600) kg s−1. The volcano induced about 10 (2.5–50) Tg of distal ash mass and about 3 (0.6–23) Tg of SO2 during the whole eruption period. The results of the Falcon flights were used to support the responsible agencies in their decisions concerning air traffic in the presence of volcanic ash.

Bayesian optimization for learning gaits under uncertainty

Abstract: Designing gaits and corresponding control policies is a key challenge in robot locomotion. Even with a viable controller parametrization, finding near-optimal parameters can be daunting. Typically, this kind of parameter optimization requires specific expert knowledge and extensive robot experiments. Automatic black-box gait optimization methods greatly reduce the need for human expertise and time-consuming design processes. Many different approaches for automatic gait optimization have been suggested to date. However, no extensive comparison among them has yet been performed. In this article, we thoroughly discuss multiple automatic optimization methods in the context of gait optimization. We extensively evaluate Bayesian optimization, a model-based approach to black-box optimization under uncertainty, on both simulated problems and real robots. This evaluation demonstrates that Bayesian optimization is particularly suited for robotic applications, where it is crucial to find a good set of gait parameters in a small number of experiments.

Parsing Argumentation Structures in Persuasive Essays

Abstract: In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecti...