Study of rapid ionisation for simulation of soft X-ray lasers with the 2D hydro-radiative code ARWEN

We present our fast ionisation routine used to study transient softX-raylasers with ARWEN, a two-dimensional hydrodynamic code incorporating adaptative mesh refinement (AMR) and radiative transport. We compute global rates between ion stages assuming an effective temperature between singly-excited levels of each ion. A two-step method is used to obtain in a straightforward manner the variation of ion populations over long hydrodynamic time steps. We compare our model with existing theoretical results both stationary and transient, finding that the discrepancies are moderate except for large densities. We simulate an existing Molybdenum Ni-like transient softX-raylaser with ARWEN. Use of the fast ionisation routine leads to a larger increase in temperature and a larger gain zone than when LTE datatables are used.

Depth dependent lattice disorder and strain in Mn-implanted and post-annealed InAs thin films

The lattice order degree and the strain in as-grown, Mn-implanted and post-implantedannealedInAsthinfilms were investigated with depth resolution by means of Rutherford backscattering spectrometry in channeling conditions (RBS/C). Three main crystallographic axes were analyzed for both In and As sublattices. The behaviour of the induced defects was evaluated in two regions with different native defects: the interface and the surface. The results show that Mn implantation and post-implantation annealing are anisotropic processes, affecting in a different way the In and As sublattices. The mechanisms influencing the enhancement and deterioration of the crystal quality during the implantation are discussed in relation to the as-grown defects and the segregation of the elements

High quality InAlN single layers lattice-matched to GaN grown by molecular beam epitaxy

We report on properties of high quality ~60 nm thick InAlN layers nearly in-plane lattice-matched to GaN, grown on c-plane GaN-on-sapphire templates by plasma-assisted molecular beam epitaxy. Excellent crystalline quality and low surface roughness are confirmed by X-ray diffraction, transmission electron microscopy, and atomic force microscopy. High annular dark field observations reveal a periodic in-plane indium content variation (8 nm period), whereas optical measurements evidence certain residual absorption below the band-gap. The indium fluctuation is estimated to be +/- 1.2% around the nominal 17% indium content via plasmon energy oscillations assessed by electron energy loss spectroscopy with sub-nanometric spatial resolution.

2D-Tasks for Cognitive Rehabilitation

Neuropsychological Rehabilitation is a complex clinic process which tries to restore or compensate cognitive and behavioral disorders in people suffering from a central nervous system injury. Information and Communication Technologies (ICTs) in Biomedical Engineering play an essential role in this field, allowing improvement and expansion of present rehabilitation programs. This paper presents a set of cognitive rehabilitation 2D-Tasks for patients with Acquired Brain Injury (ABI). These tasks allow a high degree of personalization and individualization in therapies, based on the opportunities offered by new technologies.

A Fast Reconfigurable 2D HW Core Architecture on FPGAs for Evolvable Self- Adaptive Systems

Modern FPGAs with Dynamic and Partial Reconfiguration (DPR) feature allow the implementation of complex, yet flexible, hardware systems. Combining this flexibility with evolvable hardware techniques, real adaptive systems, able to reconfigure themselves according to environmental changes, can be envisaged. In this paper, a highly regular and modular architecture combined with a fast reconfiguration mechanism is proposed, allowing the introduction of dynamic and partial reconfiguration in the evolvable hardware loop. Results and use case show that, following this approach, evolvable processing IP Cores can be built, providing intensive data processing capabilities, improving data and delay overheads with respect to previous proposals. Results also show that, in the worst case (maximum mutation rate), average reconfiguration time is 5 times lower than evaluation time.

Analysis and 2D Simulation of a Hexapod Robot Leg for Remote Exploration

A walking machine is a wheeled rover alternative, well suited for work in an unstructured environment and specially in abrupt terrain. They have some drawback like speed and power consumption, but they can achieve complex movements and protrude very little the environment they are working on. The locomotion system is determined by the terrain conditions and, in our case, this legged design has been chosen based in a working area like Rio Tinto in the South of Spain, which is a river area with abrupt terrain. A walking robot with so many degrees of freedom can be a challenge when dealing with the analysis and simulations of the legs. This paper shows how to deal with the kinematical analysis of the equations of a hexapod robot based on a design developed by the Center of Astrobiology INTA-CSIC following the classical formulation of equations

Optimization of the irrigation time and irrigation frequency by using Hydrus-2D and a capacitance FDR sensor

The evolution of water content on a sandy soil during the sprinkler irrigation campaign, in the summer of 2010, of a field of sugar beet crop located at Valladolid (Spain) is assessed by a capacitive FDR (Frequency Domain Reflectometry) EnviroScan. This field is one of the experimental sites of the Spanish research center for the sugar beet development (AIMCRA). The objective of the work focus on monitoring the soil water content evolution of consecutive irrigations during the second two weeks of July (from the 12th to the 28th). These measurements will be used to simulate water movement by means of Hydrus-2D. The water probe logged water content readings (m3/m3) at 10, 20, 40 and 60 cm depth every 30 minutes. The probe was placed between two rows in one of the typical 12 x 15 m sprinkler irrigation framework. Furthermore, a texture analysis at the soil profile was also conducted. The irrigation frequency in this farm was set by the own personal farmer 0 s criteria that aiming to minimizing electricity pumping costs, used to irrigate at night and during the weekend i.e. longer irrigation frequency than expected. However, the high evapotranspiration rates and the weekly sugar beet water consumption—up to 50mm/week—clearly determined the need for lower this frequency. Moreover, farmer used to irrigate for six or five hours whilst results from the EnviroScan probe showed the soil profile reaching saturation point after the first three hours. It must be noted that AIMCRA provides to his members with a SMS service regarding weekly sugar beet water requirement; from the use of different meteorological stations and evapotranspiration pans, farmers have an idea of the weekly irrigation needs. Nevertheless, it is the farmer 0 s decision to decide how to irrigate. Thus, in order to minimize water stress and pumping costs, a suitable irrigation time and irrigation frequency was modeled with Hydrus-2D. Results for the period above mentioned showed values of water content ranging from 35 and 30 (m3/m3) for the first 10 and 20cm profile depth (two hours after irrigation) to the minimum 14 and 13 (m3/m3) ( two hours before irrigation). For the 40 and 60 cm profile depth, water content moves steadily across the dates: The greater the root activity the greater the water content variation. According to the results in the EnviroScan probe and the modeling in Hydrus-2D, shorter frequencies and irrigation times are suggested.

Image sub-segmentation by PFCM and Artificial Neural Networks to detect pore space in 2D and 3D CT soil images

The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.