Influence of Nd on the magnetic properties of Nd1-xCaxMnO3

The role played by the Nd ions in the magnetic properties of Nd0.5Ca0.5MnO3 and Nd0.7Ca0.3MnO3 is studied using static magnetization, neutron diffraction and high frequency (9.4-475GHz) Electron Spin Resonance. We show that the Nd ions are weakly coupled to the Mn ions via ferromagnetic exchange and are responsible for the peculiar ferromagnetic resonance observed in the FM phase of both compounds (ground state below 120K for x=0.3, high field state for x=0.5). We then use ESR to look for magnetic phase separation in the low field, CO phase of Nd0.5Ca0.5MnO3. We show that there is no trace of the FM phase imbedded in the CO phase, contrary to what is observed in La0.5Ca0.5MnO3 or Pr0.5Sr0.5MnO3.Comment: to be published in phys.Rev.B as a Rapid Com

Team Exploration of Environments Using Stochastic Local Search

We investigate the use of Stochastic Local Search (SLS) technique to explore environments where agents? knowledge and the time to explore such environments are limited. We extend a work that uses evolutionary algorithms to evolve teams in simulated environments. Our work proposes a formalization of the concept of state and neighborhood for SLS and provides evaluation of agents? teams using number of interesting cells. Further, we modify the environments to include goals that are randomly distributed among interesting cells. Agents in this case are then required to search for goals. Experiments using teams of different sizes show the effectiveness of our technique. Teams were able to complete exploration of more than 70% of the environments, while in the best cases, they were able to complete explorations of more than 80% of the environments within limited time steps. These results compare with those of the previous work. It is interesting to note that all teams of agents were able to find on average all the goals in the three environments when the size of the grid is 12. This is a 100% achievement by the agents? teams. However, performance can be seen to degrade as the environments? sizes become larger

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO2 Levels.

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean's primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom's metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and shared metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum's response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. IMPORTANCE Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum's metabolism

An analysis of the July 2006 heatwave extent in Europe compared to the record year of 2003

Summary: Recent analyses have identified summer warming trends in Europe in recent decades, culminating in 2003, when mean summer temperatures were exceptionally hot over much of Europe. Mean monthly temperatures were very high in July 2003 and reached record levels in both June and August. In 2006, the mean monthly temperature for July reached a record high. Our analysis of temperature observations shows that in July 2006, as in summer 2003, maximum temperatures were more abnormal than minimum values. The 2006 heatwave was located more to the north than in 2003, and particularly affected the Netherlands, Belgium, Germany, Poland, France and Switzerland. The July 2006 anomalies were similar in magnitude to those of June and August 2003, but the discrepancy between minimum and maximum temperature anomalies was larger in 2006 compared to both June and August 2003. For maximum temperature, the affected land area by anomalies higher than 4-6 K was largest in July 2006, although the anomalies were higher in June and August 2003 at the most anomalous sites. In the north of Europe, the absolute monthly temperature values were higher in July 2006 compared to both June (also on the Iberian Peninsula) and August 200

Ignition of quantum cascade lasers in a state of oscillating electric field domains

Quantum Cascade Lasers (QCLs) are generally designed to avoid negative differential conductivity (NDC) in the vicinity of the operation point in order to prevent instabilities. We demonstrate, that the threshold condition is possible under an inhomogeneous distribution of the electric field (domains) and leads to lasing at an operation point with a voltage bias normally attributed to the NDC region. For our example, a Terahertz QCL operating up to the current maximum temperature of 199 K, the theoretical findings agree well with the experimental observations. In particular, we experimentally observe self-sustained oscillations with GHz frequency before and after threshold. These are attributed to traveling domains by our simulations. Overcoming the design paradigm to avoid NDC may allow for the further optimization of QCLs with less dissipation due to stabilizing background current.Comment: 22 page

Application of the Hess-Brezowsky classification to the identification of weather patterns causing heavy winter rainfall in Brittany (France)

An accurate knowledge of the weather patterns causing winter rainfall over the Scorff watershed in western Brittany (W. France) was developed prior to studies of the impact of the climate factor on land use management, and of the hydrological reponses to rain-producing weather patterns. These two studies are carried out in the context of the climate change. The identification of rainy air-circulation types was realized using the objective computational version of the 29-type Hess and Brezowsky Grosswetterlagen system of classifying European synoptic regimes, for the cold season (November-March) of the 1958–2005 period at the reference weather station of Lorient, and 13 other stations located in western and southern Brittany, including a more detailed study for the wet 2000–2001 cold season for three reference stations of the Scorff watershed (Lorient, Plouay and Plouray). The precipitation proportion (including the days with rainfall ≥20 mm) was calculated by major air-circulation type (GWT: see Appendix A) and by individual air-circulation subtype (GWL: see Appendix A) for the studied time-period. The most frequently occurrence of rainy days associated with westerly and southerly GWL confirmed well-known observations in western Europe and so justify the use of the Hess-Brezowsky classification in other areas outside Central Europe. The southern or south-western exposure of the watershed with a hilly inland area enhanced the heavy rainfall generated by the SW and S circulation types, and increased the difference between the rainfall amounts of coastal and inland stations during the wettest days

Thermographic Inspection of Metallic Honeycomb Sandwich Structures

The X-33/VentureStar has a Thermal Protection System (TPS) consisting mainly of brazed metallic honeycomb sandwich structures. Inspection of these structures is changing as a result of the extremely thin (less than 200 microns) skins, the small critical defect size (less than 2 mm long by 100 microns wide) and the large number (more than 1000) of parts to be inspected. Pulsed Infrared Thermography has been determined to be the most appropriate inspection method for manufacturing inspection based on performance comparison with other methods, cost, schedule and other factors. The results of the assessment of the different methods will be summarized and data on the performance of the final production inspection system will be given. Finite difference thermal methods have been used to model the whole inspection process. Details of correlation between the models and experimental data will be given and data on the use of pulsed infrared thermography on other metallic honeycomb sandwich structures will be given

Achieving commutation control of an MRI-powered robot actuator

Actuators that are powered, imaged, and controlled by magnetic resonance (MR) scanners could inexpensively provide wireless control of MR-guided robots. Similar to traditional electric motors, the MR scanner acts as the stator and generates propulsive torques on an actuator rotor containing one or more ferrous particles. Generating maximum motor torque while avoiding instabilities and slippage requires closed-loop control of the electromagnetic field gradients, i.e., commutation. Accurately estimating the position and velocity of the rotor is essential for high-speed control, which is a challenge due to the low refresh rate and high latency associated with MR signal acquisition. This paper proposes and demonstrates a method for closed-loop commutation based on interleaving pulse sequences for rotor imaging and rotor propulsion. This approach is shown to increase motor torque and velocity, eliminate rotor slip, and enable regulation of rotor angle. Experiments with a closed-loop MR imaging actuator produced a maximum force of 9.4 N

Low frequency sound absorption in a porous material with periodically distributed dead-end pores

A theoretical and numerical study of the sound propagation in air-saturated porous media with straight pores bearing lateral cavities (dead-ends) is proposed. The straight pores can be considered as the main (Biot) pores. The lateral cavities are located at ”nodes” periodically spaced along each ”main pore” axis. The effect of periodicity in the distribution of the lateral cavities is studied and the low frequency limit valid for the closely spaced dead-ends is considered separately. It is shown that the absorption coefficient and transmission loss are influenced by the viscothermal losses in the main pores as well as their perforation rate. The presence of long or short dead-ends significantly alters the acoustical properties of the material. These depend strongly on the geometry (diameter and length) of the dead-ends, on their number per node and on the periodicity along the propagation axis. These effects are primarily due to low sound velocity in the main pores and on thermal losses occurring in the lateral cavities. The model predictions are compared with experimental results and examples of material design featuring periodically distributed dead-end pores are proposed

Evaluating air quality by combining stationary, smart mobile pollution monitoring and data-driven modelling

© 2019 Elsevier Ltd Air pollution impact assessment is a major objective for various community councils in large cities, which have lately redirected their attention towards using more low-cost sensing units supported by citizen involvement. However, there is a lack of research studies investigating real-time mobile air-quality measurement through smart sensing units and even more of any data-driven modelling techniques that could be deployed to predict air quality accurately from the generated data-sets. This paper addresses these challenges by: a) proposing a comparative and detailed investigation of various air quality monitoring devices (both fixed and mobile), tested through field measurements and citizen sensing in an eco-neighbourhood from Lorraine, France, and by b) proposing a machine learning approach to evaluate the accuracy and potential of such mobile generated data for air quality prediction. The air quality evaluation consists of three experimenting protocols: a) first, we installed fixed passive tubes for monitoring the nitrogen dioxide concentrations placed in strategic locations highly affected by traffic circulation in an eco-neighbourhood, b) second, we monitored the nitrogen dioxide registered by citizens using smart and mobile pollution units carried at breathing level; results revealed that mobile-captured concentrations were 3–5 times higher than the ones registered by passive-static monitoring tubes and c) third, we compared different mobile pollution stations working simultaneously, which revealed noticeable differences in terms of result variability and sensitivity. Finally, we applied a machine learning modelling by using decision trees and neural networks on the mobile-generated data and show that humidity and noise are the most important factors influencing the prediction of nitrogen dioxide concentrations of mobile stations