Fabrication of hybrid proton-exchange membranes using a brandnew high temperature ionic liquid as charge transporting and clay modifier

The search for more compatibility between ionic liquids (ILs) and polymer matrices in proton-exchange membrane fuel cells (PEMFCs) is one of the ways in which IL leaking from proton-exchange membranes could be minimized. In this work, it is presented the synthesis of an aromatic high temperature ionic liquid (HTIL), which, incorporated into an aromatic matrix such as sulfonated polyether ether ketone (sPEEK), is expected to diminish the IL leaking that normally affects PEMFC. Phenylethylammonium trifluoromethane sulfonate (PhetaTfO) was successfully synthesized and characterized. Its melting point of 88°C makes it to classify as a HTIL and it was employed as modifier of natural Montmorillonite, forming the phenylethylammonium intercalated montmorillonite (MmtPheta) and thus, ternary membranes containing PhetaTfO, MmtPheta, and sPEEK were prepared and characterized. Immersion tests demonstrated a higher compatibility of PhetaTfO with matrix when compared to the reference DemaTfO, which was reflected in up to 30% lower IL loss by the synthesized IL than the DemaTfO; X-rays diffraction (XRD) patterns demonstrated that the modified clay was properly dispersed inside the membranes, while dynamic mechanical analyses (DMA) results indicated a strong plasticizer effect along the increase of PhetaTfO content inside the membrane, while at the same time, the conductivity increased in an exponential manner, which permitted to identify an empiric exponential equation to evaluate the effect of concentration on ionic conductivity. The maximum conductivity obtained at IL concentrations of around 38 wt% was 0.2 mS/cm. It could expect high ionic conductivities of 10 mS/cm when the concentration of this IL is 60%; nevertheless, in order to achieve that, crosslinking treatments should be done to give the membranes enough mechanical resistance.     

Tetranorsesquiterpenoids as Attractants of Yucca Moths to Yucca Flowers

Journal of Chemical Ecology - The obligate pollination mutualism between Yucca and yucca moths is a classical example of coevolution. Oviposition and active pollination by female yucca moths occur...     

Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging

Objective

Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation.

Materials and methods

Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader’s subjective confidence to assess the images (not confident, confident, very confident).

Results

Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as ‘perfusion deficit’, 113 vs. 109 as ‘dark rim artifacts’, 9 vs. 7 as ‘uncertain signal loss’, and 817 vs. 824 as ‘normal’. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as ‘good’ or ‘excellent’ (92 vs. 63%), and the diagnostic confidence more often as “very confident” (71 vs. 45%) compared to non-MoCo.

Conclusions

The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader’s subjective confidence to assess the images were rated more favorably for MoCo.

     

Biofilm Responses to Flow Regulation by Dams in Mediterranean Rivers

Dams regulate downstream hydrology and modify water quality, which in turn can impinge on the biota, especially in rivers naturally subject to large hydrological variability, such as those under Mediterranean climate. The effect of dams on biofilms was analysed in three tributaries (Cinca, Siurana and Montsant) of the Ebro River (NE Spain). We hypothesized that flow regulation would lead to lower spatial variability of biofilms on the streambed and to a decrease in their metabolic rate per unit biomass, especially during low flow periods. Biofilm characteristics were studied in five transects evenly spaced along river reaches upstream (control) and downstream (impact) of dams in each river, along with riverbed granulometry, hydraulics and water chemistry. Chlorophyll‐a, respiratory activity, photosynthetic capacity and efficiency, and extracellular enzymatic activities (β‐d ‐glucosidase, alkaline phosphatase and leucine‐amino‐peptidase) of epilithic biofilms were measured in different seasons. Spatial variability of chemical and biological variables was reduced downstream of the dams. Chlorophyll‐a concentration, photosynthetic efficiency and respiration capacity were higher in impact than in control reaches, but generally, low inorganic phosphorus concentrations resulted in comparable phosphatase activities downstream and upstream of dams. On the other hand, β‐d ‐glucosidase and leucine‐amino‐peptidase activities were higher at impact reaches. Biofilms were thicker and metabolically more active at the impact reaches, with higher ability to transform dissolved organic matter. Overall, results from this study provide evidence that dams can largely affect the structure and activity of river biofilms, with foreseeable important consequences for river ecosystem functioning. Copyright © 2014 John Wiley & Sons, Ltd.     

3D Surface Reconstruction of Noisy Point Clouds Using Growing Neural Gas: 3D Object/Scene Reconstruction

With the advent of low-cost 3D sensors and 3D printers, scene and object 3D surface reconstruction has become an important research topic in the last years. In this work, we propose an automatic (unsupervised) method for 3D surface reconstruction from raw unorganized point clouds acquired using low-cost 3D sensors. We have modified the growing neural gas network, which is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation, to perform 3D surface reconstruction of different real-world objects and scenes. Some improvements have been made on the original algorithm considering colour and surface normal information of input data during the learning stage and creating complete triangular meshes instead of basic wire-frame representations. The proposed method is able to successfully create 3D faces online, whereas existing 3D reconstruction methods based on self-organizing maps required post-processing steps to close gaps and holes produced during the 3D reconstruction process. A set of quantitative and qualitative experiments were carried out to validate the proposed method. The method has been implemented and tested on real data, and has been found to be effective at reconstructing noisy point clouds obtained using low-cost 3D sensors.     

IaaSMon: Monitoring Architecture for Public Cloud Computing Data Centers

Monitoring of cloud computing infrastructures is an imperative necessity for cloud providers and administrators to analyze, optimize and discover what is happening in their own infrastructures. Current monitoring solutions do not fit well for this purpose mainly due to the incredible set of new requirements imposed by the particular requirements associated to cloud infrastructures. This paper describes in detail the main reasons why current monitoring solutions do not work well. Also, it provides an innovative monitoring architecture that enables the monitoring of the physical and virtual machines available within a cloud infrastructure in a non-invasive and transparent way making it suitable not only for private cloud computing but also for public cloud computing infrastructures. This architecture has been validated by means of a prototype integrating an existing enterprise-class monitoring solution, Nagios, with the control and data planes of OpenStack, a well-known stack for cloud infrastructures. As a result, our new monitoring architecture is able to extend the exiting Nagios functionalities to fit in the monitoring of cloud infrastructures. The proposed architecture has been designed, implemented and released as open source to the scientific community. The proposal has also been empirically validated in a production-level cloud computing infrastructure running a test bed with up to 128 VMs where overhead and responsiveness has been carefully analyzed.     

Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.     

COACH: COllaborative certificate stAtus CHecking mechanism for VANETs

Vehicular Ad Hoc Networks (VANETs) require mechanisms to authenticate messages, identify valid vehicles, and remove misbehaving vehicles. A public key infrastructure (PKI) can be used to provide these functionalities using digital certificates. However, if a vehicle is no longer trusted, its certificates have to be revoked and this status information has to be made available to other vehicles as soon as possible. In this paper, we propose a collaborative certificate status checking mechanism called COACH to efficiently distribute certificate revocation information in VANETs. In COACH, we embed a hash tree in each standard Certificate Revocation List (CRL). This dual structure is called extended-CRL. A node possessing an extended-CRL can respond to certificate status requests without having to send the complete CRL. Instead, the node can send a short response (less than 1 kB) that fits in a single UDP message. Obviously, the substructures included in the short responses are authenticated. This means that any node possessing an extended-CRL can produce short responses that can be authenticated (including Road Side Units or intermediate vehicles). We also propose an extension to the COACH mechanism called EvCOACH that is more efficient than COACH in scenarios with relatively low revocation rates per CRL validity period. To build EvCOACH, we embed an additional hash chain in the extended-CRL. Finally, by conducting a detailed performance evaluation, COACH and EvCOACH are proved to be reliable, efficient, and scalable.     

An improved formalism for quantum computation based on geometric algebra—case study: Grover’s search algorithm

The Grover search algorithm is one of the two key algorithms in the field of quantum computing, and hence it is desirable to represent it in the simplest and most intuitive formalism possible. We show firstly, that Clifford’s geometric algebra, provides a significantly simpler representation than the conventional bra-ket notation, and secondly, that the basis defined by the states of maximum and minimum weight in the Grover search space, allows a simple visualization of the Grover search analogous to the precession of a spin- ${\frac{1}{2}}$ particle. Using this formalism we efficiently solve the exact search problem, as well as easily representing more general search situations. We do not claim the development of an improved algorithm, but show in a tutorial paper that geometric algebra provides extremely compact and elegant expressions with improved clarity for the Grover search algorithm. Being a key algorithm in quantum computing and one of the most studied, it forms an ideal basis for a tutorial on how to elucidate quantum operations in terms of geometric algebra—this is then of interest in extending the applicability of geometric algebra to more complicated problems in fields of quantum computing, quantum decision theory, and quantum information.