Thermal crystallization behaviour of Ge-Te-Se glasses

Ge10Te90-xSex (50 less than or equal to x less than or equal to 70) and Ge20Te80-xSex (x = 30, 50) glasses have been prepared by melt-quenching The thermal crystallization behaviour of these samples has been studied by Differential Scanning Calorimetry (DSC), in order to characterise these glasses for memory-threshold switching applications. It is found that Ge10Te90-xSex glasses have higher thermal stability and are more stable against devitrification. These samples may be suitable for threshold switching devices. Ge20Te80-xSex glasses, on the other hand, phase separate on heating and exhibit a double stage crystallization. Based on this, it can be expected that Ge20Te80-xSex samples will show memory behaviour. The activation energy for thermal crystallization of a representative Ge10Te40-xSe50 glass belonging to the Ge10Te90-xSex series has been found by the Kissinger's method to be 0.92 eV. The value of the activation energy obtained also indicates that Ge10Te90-xSex samples are less prone to devitrification and more suitable for threshold behaviour.

A comparison of the DNMR behaviour of methyl 5,6-bis(2-methoxyphenyl)-1,4-dimethyl-7-oxobicyclo[2.2.1]hept-5-en-2-endo-carboxylate and its 7-oxa analogue

Methyl 5,6-Bis(2-methoxyphenyt)-1,4-dimethyl-7-oxobicyclo[2.2.1]hept-5-en-2-endo-carboxylate, a moderately crowded norbornenone ester, exhibits complex VT-DNMR behaviour. A similar behaviour is not seen in its 7-oxa analogue, showing that conformational transmission from position 7 has a crucial influence on the distance parameters that govern the dynamic processes involving the substituents on the bicycloheptene framework.

The thermodynamics and phase behaviour of Tb2Pd2O5 and Er2Pd2O5

Isothermal sections of the phase diagrams for the systems Ln-Pd-O (with Ln = Tb or Er) have been established by equilibration of samples at T = 1223 K, and phase identification after quenching by optical and scanning electron microscopy (OM, SEM), energy dispersive spectroscopy (EDS), and X-ray powder diffraction (XRPD). Two oxide phases were stable along the binary Tb-O: Tb2O3+x, a phase of variable composition, and Tb7O12 at T = 1223K. The oxide PdO was not stable at this temperature. Only one ternary oxide Tb2Pd2O5 was identified in the Tb-Pd-O system. No ternary compound was found in the system Er-Pd-O at T = 1223K. However, the compound Er2Pd2O5 could be synthesized at T = 1075 K by the hydrothermal route. In both systems, the alloys and inter-metallic compounds were all found to be in equilibrium with the lanthanide sesquioxide Ln(2)O(3) (where Ln is either Tb or Er). Two solid-state cells, each incorporating a buffer electrode, were designed to measure the Gibbs energy of formation of the ternary oxides, using yttria-stabilized zirconia as the solid electrolyte and pure oxygen gas as the reference electrode. Electromotive force measurements were conducted in the temperature range (900-1275) K for Th-Pd-O system, and at temperatures from (900-1075) K for the system Er-Pd-O. The standard Gibbs energy of formation Delta(f)G(m)degrees,, of the inter-oxide compounds from their component binary oxides Ln(2)O(3) and PdO are represented by equations linear in temperature. Isothermal chemical potential diagrams for the systems Ln-Pd-O (with Ln = Tb or Er) are developed based on the thermodynamic information. (C) 2002 Elsevier Science Ltd. All rights reserved.

Clinical Proteomics of the Neglected Human Malarial Parasite Plasmodium vivax

Recent reports highlight the severity and the morbidity of disease caused by the long neglected malaria parasite Plasmodium vivax. Due to inherent difficulties in the laboratory-propagation of P. vivax, the biology of this parasite has not been adequately explored. While the proteome of P. falciparum, the causative agent of cerebral malaria, has been extensively explored from several sources, there is limited information on the proteome of P. vivax. We have, for the first time, examined the proteome of P. vivax isolated directly from patients without adaptation to laboratory conditions. We have identified 153 proteins from clinical P. vivax, majority of which do not show homology to any previously known gene products. We also report 29 new proteins that were found to be expressed in P. vivax for the first time. In addition, several proteins previously implicated as anti-malarial targets, were also found in our analysis. Most importantly, we found several unique proteins expressed by P. vivax. This study is an important step in providing insight into physiology of the parasite under clinical settings.

Human action recognition using a fast learning fully complex-valued classifier

In this paper, we use optical flow based complex-valued features extracted from video sequences to recognize human actions. The optical flow features between two image planes can be appropriately represented in the Complex plane. Therefore, we argue that motion information that is used to model the human actions should be represented as complex-valued features and propose a fast learning fully complex-valued neural classifier to solve the action recognition task. The classifier, termed as, ``fast learning fully complex-valued neural (FLFCN) classifier'' is a single hidden layer fully complex-valued neural network. The neurons in the hidden layer employ the fully complex-valued activation function of the type of a hyperbolic secant function. The parameters of the hidden layer are chosen randomly and the output weights are estimated as the minimum norm least square solution to a set of linear equations. The results indicate the superior performance of FLFCN classifier in recognizing the actions compared to real-valued support vector machines and other existing results in the literature. Complex valued representation of 2D motion and orthogonal decision boundaries boost the classification performance of FLFCN classifier. (c) 2012 Elsevier B.V. All rights reserved.

Simulating grasping behavior of people using the relational description scheme

This paper presents an enhanced relational description for the prescription of the grasp requirement and evolution of the posture of a digital human hand towards satisfaction of this requirement. Precise relational description needs anatomical segmentation of the hand geometry into palmar, dorsal and lateral patches using the palm-plane and joint locations information, and operational segmentation of the object geometry into pull,push and lateral patches with due consideration to the effect of friction. Relational description identifies appropriate patches for a desired grasp condition. Satisfaction of this requirement occurs in two discrete stages,namely,contact establishment and post-contact force exertion for object capturing. Contact establishment occurs in four potentially overlapping phases,namely,re-orientation,transfer,pre- shaping,and closing-in. The novel h and re-orientation phase,enables the palm to face the object in a task sequence scenario, transfer takes the wrist to the ball park ; pre-shaping and close-in finally achieves the contact. In this paper, an anatomically pertinent closed-form formulation is presented for the closing-in phase for identification of the point of contact on the patches ,prescribed by the relational description. Since mere contact does not ensure grasp and slip phenomenon at the point of contact on application of force is a common occurrence, the effect of slip in presence of friction has been studied for 2D and 3D object grasping endeavours and a computational generation of the slip locus is presented.A general slip locus is found to be a non-linear curve even on planar faces.Two varieties of slip phenomena,namely,stabilizing and non-stabilizing slips, and their local characteristics have been identified.Study of the evolution of this slip characteristic over the slip locus exhibited diverse grasping behaviour possibilities. Thus, the relational description paradigm not only makes the requirement specification easy and meaningful but also enables high fidelity hand object interaction studies possible.

Information and Efficiency in the Nervous System-A Synthesis

In systems biology, questions concerning the molecular and cellular makeup of an organism are of utmost importance, especially when trying to understand how unreliable components-like genetic circuits, biochemical cascades, and ion channels, among others-enable reliable and adaptive behaviour. The repertoire and speed of biological computations are limited by thermodynamic or metabolic constraints: an example can be found in neurons, where fluctuations in biophysical states limit the information they can encode-with almost 20-60% of the total energy allocated for the brain used for signalling purposes, either via action potentials or by synaptic transmission. Here, we consider the imperatives for neurons to optimise computational and metabolic efficiency, wherein benefits and costs trade-off against each other in the context of self-organised and adaptive behaviour. In particular, we try to link information theoretic (variational) and thermodynamic (Helmholtz) free-energy formulations of neuronal processing and show how they are related in a fundamental way through a complexity minimisation lemma.

Exploration of deleterious single nucleotide polymorphisms in the components of human P bodies: An in silico approach

P bodies are 100-300 nm sized organelles involved in mRNA silencing and degradation. A total of 60 human proteins have been reported to localize to P bodies. Several human SNPs contribute to complex diseases by altering the structure and function of the proteins. Also, SNPs alter various transcription factors binding, splicing and miRNA regulatory sites. Owing to the essential functions of P bodies in mRNA regulation, we explored computationally the functional significance of SNPs in 7 P body components such as XRN1, DCP2, EDC3, CPEB1, GEMIN5, STAU1 and TRIM71. Computational analyses of non-synonymous SNPs of these components was initiated using well utilized publicly available software programs such as the SIFT, followed by PolyPhen, PANTHER, MutPred, I-Mutant-2.0 and PhosSNP 1.0. Functional significance of noncoding SNPs in the regulatory regions were analysed using FastSNP. Utilizing miRSNP database, we explored the role of SNPs in the context that alters the miRNA binding sites in the above mentioned genes. Our in silico studies have identified various deleterious SNPs and this cataloguing is essential and gives first hand information for further analysis by in vitro and in vivo methods for a better understanding of maintenance, assembly and functional aspects of P bodies in both health and disease. (C) 2013 Elsevier B.V. All rights reserved.

A landscape-level assessment of Asian elephant habitat, its population and elephant-human conflict in the Anamalai hill ranges of southern Western Ghats, India

Spatial information at the landscape scale is extremely important for conservation planning, especially in the case of long-ranging vertebrates. The biodiversity-rich Anamalai hill ranges in the Western Ghats of southern India hold a viable population for the long-term conservation of the Asian elephant. Through rapid but extensive field surveys we mapped elephant habitat, corridors, vegetation and land-use patterns, estimated the elephant population density and structure, and assessed elephant-human conflict across this landscape. GIS and remote sensing analyses indicate that elephants are distributed among three blocks over a total area of about 4600 km(2). Approximately 92% remains contiguous because of four corridors; however, under 4000 km2 of this area may be effectively used by elephants. Nine landscape elements were identified, including five natural vegetation types, of which tropical moist deciduous forest is dominant. Population density assessed through the dung count method using line transects covering 275 km of walk across the effective elephant habitat of the landscape yielded a mean density of 1.1 (95% Cl = 0.99-1.2) elephant/km(2). Population structure from direct sighting of elephants showed that adult male elephants constitute just 2.9% and adult females 42.3% of the population with the rest being subadults (27.4%), juveniles (16%) and calves (11.4%). Sex ratios show an increasing skew toward females from juvenile (1:1.8) to sub-adult (1:2.4) and adult (1:14.7) indicating higher mortality of sub-adult and adult males that is most likely due to historical poaching for ivory. A rapid questionnaire survey and secondary data on elephant-human conflict from forest department records reveals that villages in and around the forest divisions on the eastern side of landscape experience higher levels of elephant-human conflict than those on the western side; this seems to relate to a greater degree of habitat fragmentation and percentage farmers cultivating annual crops in the east. We provide several recommendations that could help maintain population viability and reduce elephant-human conflict of the Anamalai elephant landscape. (C) 2013 Deutsche Gesellschaft far Saugetierkunde. Published by Elsevier GmbH. All rights reserved.

Viscoelastic Behavior of Human Lamin A Proteins in the Context of Dilated Cardiomyopathy

Lamins are intermediate filament proteins of type V constituting a nuclear lamina or filamentous meshwork which lines the nucleoplasmic side of the inner nuclear membrane. This protein mesh provides a supporting scaffold for the nuclear envelope and tethers interphase chromosome to the nuclear periphery. Mutations of mainly A-type lamins are found to be causative for at least 11 human diseases collectively termed as laminopathies majority of which are characterised by aberrant nuclei with altered structural rigidity, deformability and poor mechanotransduction behaviour. But the investigation of viscoelastic behavior of lamin A continues to elude the field. In order to address this problem, we hereby present the very first report on viscoelastic properties of wild type human lamin A and some of its mutants linked with Dilated cardiomyopathy (DCM) using quantitative rheological measurements. We observed a dramatic strain-softening effect on lamin A network as an outcome of the strain amplitude sweep measurements which could arise from the large compliance of the quasi-cross-links in the network or that of the lamin A rods. In addition, the drastic stiffening of the differential elastic moduli on superposition of rotational and oscillatory shear stress reflect the increase in the stiffness of the laterally associated lamin A rods. These findings present a preliminary insight into distinct biomechanical properties of wild type lamin A protein and its mutants which in turn revealed interesting differences.

RAPID HUMAN ACTION RECOGNITION IN H.264/AVC COMPRESSED DOMAIN FOR VIDEO SURVEILLANCE

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 our 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 effect in reduced hardware utilization and fast recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust in outdoor as well as indoor testing scenarios. We have tested our method on two benchmark action datasets and achieved more than 85% accuracy. The proposed algorithm classifies actions with speed (>2000 fps) approximately 100 times more than existing state-of-the-art pixel-domain algorithms.

Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the `feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony.

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.

An Optical How Feature and McFIS Based Approach for 3-Dimensional Human Action Recognition

We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.