Effects of Interface Treatment on the Fatigue Behavior of Shape Memory Alloy Reinforced Polymer Composites

Interfacial properties of Shape Memory Alloy (SMA) reinforced polymer matrix composites can be enhanced by improving the interfacial bonding. This paper focuses on studying the interfacial stresses developed in the SMA-epoxy interface due to various laser shot penning conditions. Fiber-pull test-setup is designed to understand the role of mechanical bias stress cycling and thermal actuation cycling. Phase transformation is tracked over mechanical and thermal fatigue cycles. A micromechanics based model developed earlier based on shear lag in SMA and energy based consistent homogenization is extended here to incorporate the stress-temperature phase diagram parameters for modeling fatigue.

Human Action Recognition in Compressed Domain using PBL-McRBFN Approach

Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.

Bioengineering of AAV2 Capsid at Specific Serine, Threonine, or Lysine Residues Improves Its Transduction Efficiency in Vitro and in Vivo

We hypothesized that the AAV2 vector is targeted for destruction in the cytoplasm by the host cellular kinase/ubiquitination/proteasomal machinery and that modification of their targets on AAV2 capsid may improve its transduction efficiency. In vitro analysis with pharmacological inhibitors of cellular serine/threonine kinases (protein kinase A, protein kinase C, casein kinase II) showed an increase (20-90%) on AAV2-mediated gene expression. The three-dimensional structure of AAV2 capsid was then analyzed to predict the sites of ubiquitination and phosphorylation. Three phosphodegrons, which are the phosphorylation sites recognized as degradation signals by ubiquitin ligases, were identified. Mutation targets comprising eight serine (S) or seven threonine (T) or nine lysine (K) residues were selected in and around phosphodegrons on the basis of their solvent accessibility, overlap with the receptor binding regions, overlap with interaction interfaces of capsid proteins, and their evolutionary conservation across AAV serotypes. AAV2-EGFP vectors with the wild-type (WT) capsid or mutant capsids (15 S/T -> alanine A] or 9 K -> arginine R] single mutant or 2 double K -> R mutants) were then evaluated in vitro. The transduction efficiencies of 11 S/T -> A and 7 K -> R vectors were significantly higher (similar to 63-90%) than the AAV2-WT vectors (similar to 30-40%). Further, hepatic gene transfer of these mutant vectors in vivo resulted in higher vector copy numbers (up to 4.9-fold) and transgene expression (up to 14-fold) than observed from the AAV2-WT vector. One of the mutant vectors, S489A, generated similar to 8-fold fewer antibodies that could be cross-neutralized by AAV2-WT. This study thus demonstrates the feasibility of the use of these novel AAV2 capsid mutant vectors in hepatic gene therapy.

Targeted Modifications in Adeno-Associated Virus Serotype 8 Capsid Improves Its Hepatic Gene Transfer Efficiency In Vivo

Recombinant adeno-associated virus vectors based on serotype 8 (AAV8) have shown significant promise for liver-directed gene therapy. However, to overcome the vector dose dependent immunotoxicity seen with AAV8 vectors, it is important to develop better AAV8 vectors that provide enhanced gene expression at significantly low vector doses. Since it is known that AAV vectors during intracellular trafficking are targeted for destruction in the cytoplasm by the host-cellular kinase/ubiquitination/proteasomal machinery, we modified specific serine/threonine kinase or ubiquitination targets on the AAV8 capsid to augment its transduction efficiency. Point mutations at specific serine (S)/threonine (T)/lysine (K) residues were introduced in the AAV8 capsid at the positions equivalent to that of the effective AAV2 mutants, generated successfully earlier. Extensive structure analysis was carried out subsequently to evaluate the structural equivalence between the two serotypes. scAAV8 vectors with the wild-type (WT) and each one of the S/T -> Alanine (A) or K-Arginine (R) mutant capsids were evaluated for their liver transduction efficiency in C57BL/6 mice in vivo. Two of the AAV8-S -> A mutants (S279A and S671A), and a K137R mutant vector, demonstrated significantly higher enhanced green fluorescent protein (EGFP) transcript levels (similar to 9- to 46-fold) in the liver compared to animals that received WT-AAV8 vectors alone. The best performing AAV8 mutant (K137R) vector also had significantly reduced ubiquitination of the viral capsid, reduced activation of markers of innate immune response, and a concomitant two-fold reduction in the levels of neutralizing antibody formation in comparison to WT-AAV8 vectors. Vector bio-distribution studies revealed that the K137R mutant had a significantly higher and preferential transduction of the liver (106 vs. 7.7 vector copies/mouse diploid genome) when compared to WT-AAV8 vectors. To further study the utility of the K137R-AAV8 mutant in therapeutic gene transfer, we delivered human coagulation factor IX (h. FIX) under the control of liver-specific promoters (LP1 or hAAT) into C57BL/6 mice. The circulating levels of h. FIX: Ag were higher in all the K137R-AAV8 treated groups up to 8 weeks post-hepatic gene transfer. These studies demonstrate the feasibility of the use of this novel AAV8 vectors for potential gene therapy of hemophilia B.

Low-Order Harmonic Suppression for Open-End Winding IM With Dodecagonal Space Vector Using a Single DC-Link Supply

This paper proposes a technique to suppress low-order harmonics for an open-end winding induction motor drive for a full modulation range. One side of the machine is connected to a main inverter with a dc power supply, whereas the other inverter is connected to a capacitor from the other side. Harmonic suppression (with complete elimination of fifth- and seventh-order harmonics) is achieved by realizing dodecagonal space vectors using a combined pulsewidth modulation (PWM) control for the two inverters. The floating capacitor voltage is inherently controlled during the PWM operation. The proposed PWM technique is shown to be valid for the entire modulation range, including overmodulation and six-step mode of operation of the main inverter. Experimental results have been presented to validate the proposed technique.

A carboxy terminal domain of the L protein of rinderpest virus possesses RNA triphosphatase activity - The first enzyme in the viral mRNA capping pathway

The large protein L of negative-sense RNA viruses is a multifunctional protein involved in transcription and replication of genomic RNA. It also possesses enzymatic activities involved in capping and methylation of viral mRNAs. The pathway for mRNA capping followed by the L protein of the viruses in the Morbillivirus genus has not been established, although it has been speculated that these viruses may follow the unconventional capping pathway as has been shown for some viruses of Rhabdoviridae family. We had earlier shown that the large protein L of Rinderpest virus expressed as recombinant L-P complex in insect cells as well as the ribonucleoprotein complex from purified virus possesses RNA triphosphatase (RTPase) and guanylyltransferase activities, in addition to RNA dependent RNA polymerase activity. In the present work, we demonstrate that RTPase as well as nucleoside triphosphatase (NTPase) activities are exhibited by a subdomain of the L protein in the C terminal region (a.a. 1640 1840). The RTPase activity depends absolutely on a divalent cation, either magnesium or manganese. Both the RTPase and NTPase activities of the protein show dual metal specificity. Two mutant proteins having alanine mutations in the glutamic acid residues in motif-A of the RTPase domain did not show RTPase activity, while exhibiting reduced NTPase activity suggesting overlapping active sites for the two enzymatic functions. The RTPase and NTPase activities of the L subdomain resemble those of the Vaccinia capping enzyme D1 and the baculovirus LEF4 proteins. (C) 2015 Elsevier Inc. All rights reserved.

Ultrathin Au nanowires supported on rGO/TiO2 as an efficient photoelectrocatalyst

We report the synthesis of stable rGO/TiO2/Au nanowire hybrids showing excellent electrocatalytic activity for ethanol oxidation. Phase-pure anatase TiO2 nanoparticles (similar to 3 nm) were grown on GO sheets followed by the growth of ultrathin Au nanowires leading to the formation of a multidimensional ternary structure (0-D TiO2 and 1-D Au on 2-D graphene oxide). The oleylamine used for the synthesis of the Au nanowires not only leads to stable Au nanowires anchored on the GO sheets but also leads to the functionalization and room temperature reduction of GO. Using control experiments, we delineate the role of the three components in the hybrid and show that there is a significant synergy. We show that the catalytic activity for ethanol oxidation primarily stems from the Au nanowires. While TiO2 triggers the formation of oxygenated species on the Au nanowire surface at a lower potential and also imparts photoactivity, rGO provides a conducting support to minimize the charge transfer resistance in addition to stabilizing the Au nanowires. Compared with nanoparticle hybrids, the nanowire hybrids display a much better electrocatalytic performance. In addition to high efficiency, the nanowire hybrids also show a remarkable tolerance towards H2O2. While our study has a direct bearing on fuel cell technology, the insights gained are sufficiently general such that they provide guiding principles for the development of multifunctional ternary hybrids.

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Compressed domain human action recognition in H.264/AVC video streams

This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of the proposed work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can result in reduced hardware utilization and faster recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust to outdoor as well as indoor testing scenarios. We have evaluated the performance of the proposed method on two benchmark action datasets and achieved more than 85 % accuracy. The proposed algorithm classifies actions with speed (> 2,000 fps) approximately 100 times faster than existing state-of-the-art pixel-domain algorithms.

Review on Tin (II) Sulfide (SnS) Material: Synthesis, Properties, and Applications

Tin (II) sulphide (SnS), a direct band gap semiconductor compound, has recently received great attention due to its unique properties. Because of low cost, absence of toxicity, and good abundance in nature, it is becoming a candidate for future multifunctional devices particularly for light conversion applications. Although the current efficiencies are low, the cost-per-Watt is becoming competitive. At room temperature, SnS exhibits stable low-symmetric, double-layered orthorhombic crystal structure, having a = 0.4329, b = 1.1192, and c = 0.3984nm as lattice parameters. These layer-structured materials are of interest in various device applications due to the arrangement of structural lattice with cations and anions. The layers of cations are separated only by van der Waals forces that provide intrinsically chemically inert surface without dangling bonds and surface density of states. As a result, there is no Fermi level pinning at the surface of the semiconductor. This fact leads to considerably high chemical and environmental stability. Further, the electrical and optical properties of SnS can be easily tailored by modifying the growth conditions or doping with suitable dopants without disturbing its crystal structure.In the last few decades, SnS has been synthesized and studied in the form of single-crystals and thin-films. Most of the SnS single-crystals have been synthesized by Bridgeman technique, whereas thin films have been developed using different physical as well as chemical deposition techniques. The synthesis or development of SnS structures in different forms including single-crystals and thin films, and their unique properties are reviewed here. The observed physical and chemical properties of SnS emphasize that this material could has novel applications in optoelectronics including solar cell devices, sensors, batteries, and also in biomedical sciences. These aspects are also discussed.

Flow Cytometry Analysis of Cytotoxicity In Vitro and Long-Term Toxicity of HA-40wt% BaTiO3 Nanoparticles In Vivo

The development of new implantable biomaterials requires bone-mimicking physical properties together with desired biocompatible property. In continuation to our earlier published research to establish compositional dependent multifunctional bone-like properties and cytocompatibility response of hydroxyapatite (HA)-BaTiO3 composites, the toxicological property evaluation, both invitro and invivo, were conducted on HA-40wt% BaTiO3 and reported in this work. In particular, this work reports invitro cytotoxicity of mouse myoblast cells as well as invivo long-term tissue and nanoparticles interaction of intra-articularly injected HA-40wt% BaTiO3 and BaTiO3 up to the concentration of 25mg/mL in physiological saline over 12weeks in mouse model. The careful analysis of flow cytometry results could not reveal any statistically significant difference in terms of early/late apoptotic cells or necrotic cells over 8d in culture. Extensive histological analysis could not record any signature of cellular level toxicity or pronounced inflammatory response in vital organs as well as at knee joints of Balb/c mice after 12weeks. Taken together, this study establishes nontoxic nature of HA-40wt% BaTiO3 and therefore, HA-40wt% BaTiO3 can be used safely for various biomedical applications.

The putative role of some conserved water molecules in the structure and function of human transthyretin

Human transthyretin (hTTR) is a multifunctional protein that is involved in several neurodegenerative diseases. Besides the transportation of thyroxin and vitamin A, it is also involved in the proteolysis of apolipoprotein A1 and A beta peptide. Extensive analyses of 32 high-resolution X-ray and neutron diffraction structures of hTTR followed by molecular-dynamics simulation studies using a set of 15 selected structures affirmed the presence of 44 conserved water molecules in its dimeric structure. They are found to play several important roles in the structure and function of the protein. Eight water molecules stabilize the dimeric structure through an extensive hydrogen-bonding network. The absence of some of these water molecules in highly acidic conditions (pH <= 4.0) severely affects the interfacial hydrogen-bond network, which may destabilize the native tetrameric structure, leading to its dissociation. Three pairs of conserved water molecules contribute to maintaining the geometry of the ligand-binding cavities. Some other water molecules control the orientation and dynamics of different structural elements of hTTR. This systematic study of the location, absence, networking and interactions of the conserved water molecules may shed some light on various structural and functional aspects of the protein. The present study may also provide some rational clues about the conserved water-mediated architecture and stability of hTTR.

Sparse Representation based Anomaly Detection using HOMV in H.264 Compressed Videos

In this paper, we have proposed an anomaly detection algorithm based on Histogram of Oriented Motion Vectors (HOMV) 1] in sparse representation framework. Usual behavior is learned at each location by sparsely representing the HOMVs over learnt normal feature bases obtained using an online dictionary learning algorithm. In the end, anomaly is detected based on the likelihood of the occurrence of sparse coefficients at that location. The proposed approach is found to be robust compared to existing methods as demonstrated in the experiments on UCSD Ped1 and UCSD Ped2 datasets.

Anomaly detection in compressed H.264/AVC video

Real time anomaly detection is the need of the hour for any security applications. In this article, we have proposed a real time anomaly detection for H.264 compressed video streams utilizing pre-encoded motion vectors (MVs). The proposed work is principally motivated by the observation that MVs have distinct characteristics during anomaly than usual. Our observation shows that H.264 MV magnitude and orientation contain relevant information which can be used to model the usual behavior (UB) effectively. This is subsequently extended to detect abnormality/anomaly based on the probability of occurrence of a behavior. The performance of the proposed algorithm was evaluated and bench-marked on UMN and Ped anomaly detection video datasets, with a detection rate of 70 frames per sec resulting in 90x and 250x speedup, along with on-par detection accuracy compared to the state-of-the-art algorithms.

Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method

Three-dimensional (3-D) full-wave electromagnetic simulation using method of moments (MoM) under the framework of fast solver algorithms like fast multipole method (FMM) is often bottlenecked by the speed of convergence of the Krylov-subspace-based iterative process. This is primarily because the electric field integral equation (EFIE) matrix, even with cutting-edge preconditioning techniques, often exhibits bad spectral properties arising from frequency or geometry-based ill-conditioning, which render iterative solvers slow to converge or stagnate occasionally. In this communication, a novel technique to expedite the convergence of MoMmatrix solution at a specific frequency is proposed, by extracting and applying Eigen-vectors from a previously solved neighboring frequency in an augmented generalized minimum residual (AGMRES) iterative framework. This technique can be applied in unison with any preconditioner. Numerical results demonstrate up to 40% speed-up in convergence using the proposed Eigen-AGMRES method.