Local conductance: A means to extract polarization and depolarizing fields near domain walls in ferroelectrics

Conducting atomic force microscopy images of bulk semiconducting BaTiO3 surfaces show clear stripe domain contrast. High local conductance correlates with strong out-of-plane polarization (mapped independently using piezoresponse force microscopy), and current- voltage characteristics are consistent with dipole-induced alterations in Schottky barriers at the metallic tip-ferroelectric interface. Indeed, analyzing current-voltage data in terms of established Schottky barrier models allows relative variations in the surface polarization, and hence the local domain structure, to be determined. Fitting also reveals the signature of surface-related depolarizing fields concentrated near domain walls. Domain information obtained from mapping local conductance appears to be more surface-sensitive than that from piezoresponse force microscopy. In the right materials systems, local current mapping could therefore represent a useful complementary technique for evaluating polarization and local electric fields with nanoscale resolution.

Investigation of tanpura string vibrations using a two-dimensional time-domain model incorporating coupling and bridge friction

Tanpura string vibrations have been investigated previously using numerical models based on energy conserving schemes derived from a Hamiltonian description in one-dimensional form. Such time-domain models have the property that, for the lossless case, the numerical Hamiltonian (representing total energy of the system) can be proven to be constant from one time step
to the next, irrespective of any of the system parameters; in practice the Hamiltonian can be shown to be conserved within machine precision. Models of this kind can reproduce a jvari effect, which results from the bridge-string interaction. However the one-dimensional formulation has recently been shown to fail to replicate the jvaris strong dependence on the thread placement. As a first step towards simulations which accurately emulate this sensitivity to the thread placement, a twodimensional model is proposed, incorporating coupling of controllable level between the two string polarisations at the string termination opposite from the barrier. In addition, a friction force acting when the string slides across the bridge in horizontal direction is introduced, thus effecting a further damping mechanism. In this preliminary study, the string is terminated at the position of the thread. As in the one-dimensional model, an implicit scheme has to be used to solve the system, employing Newton's method to calculate the updated positions and momentums of each string segment. The two-dimensional model is proven to be energy conserving when the loss parameters are set to zero, irrespective of the coupling constant. Both frequency-dependent and independent losses are then added to the string, so that the model can be compared to analogous instruments. The influence of coupling and the bridge friction are investigated.

DED or alive: assembly and regulation of the death effector domain complexes.

Death effector domains (DEDs) are protein-protein interaction domains initially identified in proteins such as FADD, FLIP and caspase-8 involved in regulating apoptosis. Subsequently, these proteins have been shown to have important roles in regulating other forms of cell death, including necroptosis, and in regulating other important cellular processes, including autophagy and inflammation. Moreover, these proteins also have prominent roles in innate and adaptive immunity and during embryonic development. In this article, we review the various roles of DED-containing proteins and discuss recent developments in our understanding of DED complex formation and regulation. We also briefly discuss opportunities to therapeutically target DED complex formation in diseases such as cancer.

Contextual Intrusion Alerts for SCADA Networks

The complexity of modern SCADA networks and their associated cyber-attacks requires an expressive but flexible manner for representing both domain knowledge and collected intrusion alerts with the ability to integrate them for enhanced analytical capabilities and better understanding of attacks. This paper proposes an ontology-based approach for contextualized intrusion alerts in SCADA networks. In this approach, three security ontologies were developed to represent and store information on intrusion alerts, Modbus communications, and Modbus attack descriptions. This information is correlated into enriched intrusion alerts using simple ontology logic rules written in Semantic Query-Enhanced Web Rules (SQWRL). The contextualized alerts give analysts the means to better understand evolving attacks and to uncover the semantic relationships between sequences of individual attack events. The proposed system is illustrated by two use case scenarios.

Tumor suppressor Ras-association domain family 1 isoform A is a novel regulator of cardiac hypertrophy

BACKGROUND: Ras signaling regulates a number of important processes in the heart, including cell growth and hypertrophy. Although it is known that defective Ras signaling is associated with Noonan, Costello, and other syndromes that are characterized by tumor formation and cardiac hypertrophy, little is known about factors that may control it. Here we investigate the role of Ras effector Ras-association domain family 1 isoform A (RASSF1A) in regulating myocardial hypertrophy.

METHODS AND RESULTS: A significant downregulation of RASSF1A expression was observed in hypertrophic mouse hearts, as well as in failing human hearts. To further investigate the role of RASSF1A in cardiac (patho)physiology, we used RASSF1A knock-out (RASSF1A(-)(/)(-)) mice and neonatal rat cardiomyocytes with adenoviral overexpression of RASSF1A. Ablation of RASSF1A in mice significantly enhanced the hypertrophic response to transverse aortic constriction (64.2% increase in heart weight/body weight ratio in RASSF1A(-)(/)(-) mice compared with 32.4% in wild type). Consistent with the in vivo data, overexpression of RASSF1A in cardiomyocytes markedly reduced the cellular hypertrophic response to phenylephrine stimulation. Analysis of molecular signaling events in isolated cardiomyocytes indicated that RASSF1A inhibited extracellular regulated kinase 1/2 activation, likely by blocking the binding of Raf1 to active Ras.

CONCLUSIONS: Our data establish RASSF1A as a novel inhibitor of cardiac hypertrophy by modulating the extracellular regulated kinase 1/2 pathway.

On the Ontological Quality and Logical Quality of Conceptual-Modeling Grammars: The Need for a Dual Perspective

A core activity in information systems development involves building a conceptual model of the domain that an information system is intended to support. Such models are created using a conceptual-modeling (CM) grammar. Just as high-quality conceptual models facilitate high-quality systems development, high-quality CM grammars facilitate high-quality conceptual modeling. This paper provides a new perspective on ways to improve the quality of the semantics of CM grammars. For many years, the leading approach to this topic has relied on ontological theory. We show, however, that the ontological approach captures only half the story. It needs to be coupled with a logical approach. We explain how the ontological quality and logical quality of CM grammars interrelate. Furthermore, we outline three contributions that a logical approach can make to evaluating the quality of CM grammars: a means of seeing some familiar conceptual-modeling problems in simpler ways; the illumination of new problems; and the ability to prove the benefit of modifying existing CM grammars in particular ways. We demonstrate these benefits in the context of the Entity-Relationship grammar. More generally, our paper opens up a new area of research with many opportunities for future research and practice.

An empirical polarization domain channel availability model for cognitive radio

In dynamic spectrum access networks, cognitive radio terminals monitor their spectral environment in order to detect and opportunistically access unoccupied frequency channels. The overall performance of such networks depends on the spectrum occupancy or availability patterns. Accurate knowledge on the channel availability enables optimum performance of such networks in terms of spectrum and energy efficiency. This work proposes a novel probabilistic channel availability model that can describe the channel availability in different polarizations for mobile cognitive radio terminals that are likely to change their orientation during their operation. A Gaussian approximation is used to model the empirical occupancy data that was obtained through a measurement campaign in the cellular frequency bands within a realistic operational scenario.

A statistical framework for channel availability modelling in the polarisation domain

Cognitive radio has been proposed as a means of improving the spectrum utilisation and increasing spectrum efficiency of wireless systems. This can be achieved by allowing cognitive radio terminals to monitor their spectral environment and opportunistically access the unoccupied frequency channels. Due to the opportunistic nature of cognitive radio, the overall performance of such networks depends on the spectrum occupancy or availability patterns. Appropriate knowledge on channel availability can optimise the sensing performance in terms of spectrum and energy efficiency. This work proposes a statistical framework for the channel availability in the polarization domain. A Gaussian Normal approximation is used to model real-world occupancy data obtained through a measurement campaign in the cellular frequency bands within a realistic scenario.

Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.