MAST flight system dynamic performance

The MAST Flight System as a test bed for large space structure control algorithms is discussed. An overview is given of the control system architecture. The actuators, the sensors, the control computer, and the baseline damping algorithm are discussed

Transparent soil for imaging the rhizosphere

Understanding of soil processes is essential for addressing the global issues of food security, disease transmission and climate change. However, techniques for observing soil biology are lacking. We present a heterogeneous, porous, transparent substrate for in situ 3D imaging of living plants and root-associated microorganisms using particles of the transparent polymer, Nafion, and a solution with matching optical properties. Minerals and fluorescent dyes were adsorbed onto the Nafion particles for nutrient supply and imaging of pore size and geometry. Plant growth in transparent soil was similar to that in soil. We imaged colonization of lettuce roots by the human bacterial pathogen Escherichia coli O157:H7 showing micro-colony development. Micro-colonies may contribute to bacterial survival in soil. Transparent soil has applications in root biology, crop genetics and soil microbiology

Scalable Parallel Numerical Constraint Solver Using Global Load Balancing

We present a scalable parallel solver for numerical constraint satisfaction problems (NCSPs). Our parallelization scheme consists of homogeneous worker solvers, each of which runs on an available core and communicates with others via the global load balancing (GLB) method. The parallel solver is implemented with X10 that provides an implementation of GLB as a library. In experiments, several NCSPs from the literature were solved and attained up to 516-fold speedup using 600 cores of the TSUBAME2.5 supercomputer.Comment: To be presented at X10'15 Worksho

Electromechanical tuning of vertically-coupled photonic crystal nanobeams

We present the design, the fabrication and the characterization of a tunable one-dimensional (1D) photonic crystal cavity (PCC) etched on two vertically-coupled GaAs nanobeams. A novel fabrication method which prevents their adhesion under capillary forces is introduced. We discuss a design to increase the flexibility of the structure and we demonstrate a large reversible and controllable electromechanical wavelength tuning (> 15 nm) of the cavity modes.Comment: 11 pages, 4 figure

Prominent effect of soil network heterogeneity on microbial invasion

Using a network representation for real soil samples and mathematical models for microbial spread, we show that the structural heterogeneity of the soil habitat may have a very significant influence on the size of microbial invasions of the soil pore space. In particular, neglecting the soil structural heterogeneity may lead to a substantial underestimation of microbial invasion. Such effects are explained in terms of a crucial interplay between heterogeneity in microbial spread and heterogeneity in the topology of soil networks. The main influence of network topology on invasion is linked to the existence of long channels in soil networks that may act as bridges for transmission of microorganisms between distant parts of soil

The KATRIN Experiment

The KArlsruhe TRitium Neutrino mass experiment, KATRIN, aims to search for the mass of the electron neutrino with a sensitivity of 0.2 eV/c^2 (90% C.L.) and a detection limit of 0.35 eV/c^2 (5 sigma). Both a positive or a negative result will have far reaching implications for cosmology and the standard model of particle physics and will give new input for astroparticle physics and cosmology. The major components of KATRIN are being set up at the Karlsruhe Institut of Technology in Karlsruhe, Germany, and test measurements of the individual components have started. Data taking with tritium is scheduled to start in 2012.Comment: 3 pages, 1 figure, proceedings of the TAUP 2009 International Conference on Topics in Astroparticle and Underground Physics, to be published in Journal of Physics, Conference Serie

Explaining Deep Learning Models for Age-related Gait Classification based on time series acceleration

Gait analysis holds significant importance in monitoring daily health, particularly among older adults. Advancements in sensor technology enable the capture of movement in real-life environments and generate big data. Machine learning, notably deep learning (DL), shows promise to use these big data in gait analysis. However, the inherent black-box nature of these models poses challenges for their clinical application. This study aims to enhance transparency in DL-based gait classification for aged-related gait patterns using Explainable Artificial Intelligence, such as SHAP. A total of 244 subjects, comprising 129 adults and 115 older adults (age>65), were included. They performed a 3-minute walking task while accelerometers were affixed to the lumbar segment L3. DL models, convolutional neural network (CNN) and gated recurrent unit (GRU), were trained using 1-stride and 8-stride accelerations, respectively, to classify adult and older adult groups. SHAP was employed to explain the models' predictions. CNN achieved a satisfactory performance with an accuracy of 81.4% and an AUC of 0.89, and GRU demonstrated promising results with an accuracy of 84.5% and an AUC of 0.94. SHAP analysis revealed that both CNN and GRU assigned higher SHAP values to the data from vertical and walking directions, particularly emphasizing data around heel contact, spanning from the terminal swing to loading response phases. Furthermore, SHAP values indicated that GRU did not treat every stride equally. CNN accurately distinguished between adults and older adults based on the characteristics of a single stride's data. GRU achieved accurate classification by considering the relationships and subtle differences between strides. In both models, data around heel contact emerged as most critical, suggesting differences in acceleration and deceleration patterns during walking between different age groups

Amplification of different marker sequences for identification of Agrobacterium vitis strains

Research Not

Applying Model Based Techniques for Early Safety Evaluation of an Automotive Architecture in Compliance with the ISO 26262 Standard

International audienceIn 2011, the automotive industry introduced the application of a standardized process for functional safety-related development of automotive electronic products. The related international standard, ISO 26262 functional safety for road vehicles, has high demands on process documentation and analysis. Within an engineering context this challenges the tremendous increase of complexity for modern automotive systems and high productivity demands for industrial competiveness purpose. Model based development techniques based on an Architecture Description Language (ADL) has been identified as the best candidate to manage the system complexity and the related safety analysis with the benefit of formal description and capabilities for test automation. The proposed concept relies on the definition of a compositional error modeling approach tightly coupled with the system architecture model, capable to analyze the software and hardware architectures and implementations. This paper explains the results of the language extension based on the EAST-ADL and AUTOSAR domain model in terms of early safety evaluation of an automotive architecture, automating the qualitative and quantitative assessment of road vehicle products as claimed by the application of the ISO 26262