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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.
This paper describes the modeling of a high-temperature storage system for an existing solar tower power plant with open volumetric receiver technology, which uses air as heat transfer medium (HTF). The storage system model has been developed in the simulation environment Matlab/Simulink®. The storage type under investigation is a packed bed thermal energy storage system which has the characteristics of a regenerator. Thermal energy can be stored and discharged as required via the HTF air. The air mass flow distribution is controlled by valves, and the mass flow by two blowers. The thermal storage operation strategy has a direct and significant impact on the energetic and economic efficiency of the solar tower power plants.
Bacillus pumilus reveals a remarkably high resistance to hydrogen peroxide provoked oxidative stress
(2014)
Bacillus pumilus is characterized by a higher oxidative stress resistance than other comparable industrially relevant Bacilli such as B. subtilis or B. licheniformis. In this study the response of B. pumilus to oxidative stress was investigated during a treatment with high concentrations of hydrogen peroxide at the proteome, transcriptome and metabolome level. Genes/proteins belonging to regulons, which are known to have important functions in the oxidative stress response of other organisms, were found to be upregulated, such as the Fur, Spx, SOS or CtsR regulon. Strikingly, parts of the fundamental PerR regulon responding to peroxide stress in B. subtilis are not encoded in the B. pumilus genome. Thus, B. pumilus misses the catalase KatA, the DNA-protection protein MrgA or the alkyl hydroperoxide reductase AhpCF. Data of this study suggests that the catalase KatX2 takes over the function of the missing KatA in the oxidative stress response of B. pumilus. The genome-wide expression analysis revealed an induction of bacillithiol (Cys-GlcN-malate, BSH) relevant genes. An analysis of the intracellular metabolites detected high intracellular levels of this protective metabolite, which indicates the importance of bacillithiol in the peroxide stress resistance of B. pumilus.
Two single-incision mini-slings used for treating urinary incontinence in women are compared with respect to the stresses they produce in their surrounding tissue. In an earlier paper we experimentally observed that these implants produce considerably different stress distributions in a muscle tissue equivalent. Here we perform 2D finite element analyses to compare the shear stresses and normal stresses in the tissue equivalent for the two meshes and to investigate their failure behavior. The results clearly show that the Gynecare TVT fails for increasing loads in a zipper-like manner because it gradually debonds from the surrounding tissue. Contrary to that, the tissue at the ends of the DynaMesh-SIS direct may rupture but only at higher loads. The simulation results are in good agreement with the experimental observations thus the computational model helps to interpret the experimental results and provides a tool for qualitative evaluation of mesh implants.
There is significant interest in sampling subglacial environments for geobiological studies, but they are difficult to access. Existing ice-drilling technologies make it cumbersome to maintain microbiologically clean access for sample acquisition and environmental stewardship of potentially fragile subglacial aquatic ecosystems. The IceMole is a maneuverable subsurface ice probe for clean in situ analysis and sampling of glacial ice and subglacial materials. The design is based on the novel concept of combining melting and mechanical propulsion. It can change melting direction by differential heating of the melting head and optional side-wall heaters. The first two prototypes were successfully tested between 2010 and 2012 on glaciers in Switzerland and Iceland. They demonstrated downward, horizontal and upward melting, as well as curve driving and dirt layer penetration. A more advanced probe is currently under development as part of the Enceladus Explorer (EnEx) project. It offers systems for obstacle avoidance, target detection, and navigation in ice. For the EnEx-IceMole, we will pay particular attention to clean protocols for the sampling of subglacial materials for biogeochemical analysis. We plan to use this probe for clean access into a unique subglacial aquatic environment at Blood Falls, Antarctica, with return of a subglacial brine sample.
Developing a new production host from a blueprint: Bacillus pumilus as an industrial enzyme producer
(2014)
This paper develops a new finite element method (FEM)-based upper bound algorithm for limit and shakedown analysis of hardening structures by a direct plasticity method. The hardening model is a simple two-surface model of plasticity with a fixed bounding surface. The initial yield surface can translate inside the bounding surface, and it is bounded by one of the two equivalent conditions: (1) it always stays inside the bounding surface or (2) its centre cannot move outside the back-stress surface. The algorithm gives an effective tool to analyze the problems with a very high number of degree of freedom. Our numerical results are very close to the analytical solutions and numerical solutions in literature.
Today, the assembly of laser systems requires a large share of manual operations due to its complexity regarding the optimal alignment of optics. Although the feasibility of automated alignment of laser optics has been shown in research labs, the development effort for the automation of assembly does not meet economic requirements – especially for low-volume laser production. This paper presents a model-based and sensor-integrated assembly execution approach for flexible assembly cells consisting of a macro-positioner covering a large workspace and a compact micromanipulator with camera attached to the positioner. In order to make full use of available models from computer-aided design (CAD) and optical simulation, sensor systems at different levels of accuracy are used for matching perceived information with model data. This approach is named "chain of refined perception", and it allows for automated planning of complex assembly tasks along all major phases of assembly such as collision-free path planning, part feeding, and active and passive alignment. The focus of the paper is put on the in-process image-based metrology and information extraction used for identifying and calibrating local coordinate systems as well as the exploitation of that information for a part feeding process for micro-optics. Results will be presented regarding the processes of automated calibration of the robot camera as well as the local coordinate systems of part feeding area and robot base.