Studies of Adsorption Characteristics of Activated Carbons Down to 4.5 K for the Development of Cryosorption Pumps for Fusion Systems

Cryosorption pump is the only possible device to pump helium, hydrogen and its isotopes in fusion environment, such as high magnetic field and high plasma temperatures. Activated carbons are known to be the most suitable adsorbent in the development of cryosorption pumps. For this purpose, the data of adsorption characteristics of activated carbons in the temperature range 4.5 K to 77 K are needed, but are not available in the literature. For obtaining the above data, a commercial micro pore analyzer operating at 77 K has been integrated with a two stage GM cryocooler, which enables the cooling of the sample temperature down to 4.5 K. A heat switch mounted between the second stage cold head and the sample chamber helps to raise the sample chamber temperature to 77 K without affecting the performance of the cryocooler. The detailed description of this system is presented elsewhere. This paper presents the results of experimental studies of adsorption isotherms measured on different types of activated carbons in the form of granules, globules, flake knitted and non-woven types in the temperature range 4.5 K to 10 K using Helium gas as the adsorbate. The above results are analyzed to obtain the pore size distributions and surface areas of the activated carbons. The effect of adhesive used for bonding the activated carbons to the panels is also studied. These results will be useful to arrive at the right choice of activated carbon to be used for the development of cryosorption pumps.

OPTICAL FLOW ESTIMATION USING APPROXIMATE NEAREST NEIGHBOR FIELD FUSION

This paper proposes an optical flow algorithm by adapting Approximate Nearest Neighbor Fields (ANNF) to obtain a pixel level optical flow between image sequence. Patch similarity based coherency is performed to refine the ANNF maps. Further improvement in mapping between the two images are obtained by fusing bidirectional ANNF maps between pair of images. Thus a highly accurate pixel level flow is obtained between the pair of images. Using pyramidal cost optimization, the pixel level optical flow is further optimized to a sub-pixel level. The proposed approach is evaluated on the middlebury dataset and the performance obtained is comparable with the state of the art approaches. Furthermore, the proposed approach can be used to compute large displacement optical flow as evaluated using MPI Sintel dataset.

Correlation of microstructure and creep behaviour of MRI230D Mg alloy developed by two different casting technologies

The relationship between the as-cast microstructure and creep behaviour of the heat-resistant MRI230D Mg alloy produced by two different casting technologies is investigated. The alloy in both ingot-casting (IC) and high pressure die-casting (HPDC) conditions consists of alpha-Mg, 06 ((Mg,AI)(2)Ca), Al-Mn and Sn-Mg-Ca rich phases. However, the HPDC alloy resulted in relatively finer grain size and higher volume fraction of finer, denser network of eutectic C36 phase in the as-cast microstructure as compared to that of the IC alloy. The superior creep resistance exhibited by the HPDC alloy at all the stress levels and temperatures employed in the present investigation was attributed to the more effective dispersion strengthening effect caused by the presence of finer and denser network of the C36 phase. The increased amount of the eutectic C36 phase was the only change observed in the microstructures of both alloys following creep tests. (C) 2015 Elsevier B.V. All rights reserved.

Physical Layer Data Fusion Via Distributed Co-Phasing With General Signal Constellations

This paper studies a pilot-assisted physical layer data fusion technique known as Distributed Co-Phasing (DCP). In this two-phase scheme, the sensors first estimate the channel to the fusion center (FC) using pilots sent by the latter; and then they simultaneously transmit their common data by pre-rotating them by the estimated channel phase, thereby achieving physical layer data fusion. First, by analyzing the symmetric mutual information of the system, it is shown that the use of higher order constellations (HOC) can improve the throughput of DCP compared to the binary signaling considered heretofore. Using an HOC in the DCP setting requires the estimation of the composite DCP channel at the FC for data decoding. To this end, two blind algorithms are proposed: 1) power method, and 2) modified K-means algorithm. The latter algorithm is shown to be computationally efficient and converges significantly faster than the conventional K-means algorithm. Analytical expressions for the probability of error are derived, and it is found that even at moderate to low SNRs, the modified K-means algorithm achieves a probability of error comparable to that achievable with a perfect channel estimate at the FC, while requiring no pilot symbols to be transmitted from the sensor nodes. Also, the problem of signal corruption due to imperfect DCP is investigated, and constellation shaping to minimize the probability of signal corruption is proposed and analyzed. The analysis is validated, and the promising performance of DCP for energy-efficient physical layer data fusion is illustrated, using Monte Carlo simulations.

Speaker verification based on the fusion of speech acoustics and inverted articulatory signals

We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.

Stalking influenza by vaccination with pre-fusion headless HA mini-stem

Inaccuracies in prediction of circulating viral strain genotypes and the possibility of novel reassortants causing a pandemic outbreak necessitate the development of an anti-influenza vaccine with increased breadth of protection and potential for rapid production and deployment. The hemagglutinin (HA) stem is a promising target for universal influenza vaccine as stem-specific antibodies have the potential to be broadly cross-reactive towards different HA subtypes. Here, we report the design of a bacterially expressed polypeptide that mimics a H5 HA stem by protein minimization to focus the antibody response towards the HA stem. The HA mini-stem folds as a trimer mimicking the HA prefusion conformation. It is resistant to thermal/chemical stress, and it binds to conformation-specific, HA stem-directed broadly neutralizing antibodies with high affinity. Mice vaccinated with the group 1 HA mini-stems are protected from morbidity and mortality against lethal challenge by both group 1 (H5 and H1) and group 2 (H3) influenza viruses, the first report of cross-group protection. Passive transfer of immune serum demonstrates the protection is mediated by stem-specific antibodies. Furthermore, antibodies indudced by these HA stems have broad HA reactivity, yet they do not have antibody-dependent enhancement activity.