A Strain-Driven Morphotropic Phase Boundary in BiFeO3

Piezoelectric materials, which convert mechanical to electrical energy and vice versa, are typically characterized by the intimate coexistence of two phases across a morphotropic phase boundary. Electrically switching one to the other yields large electromechanical coupling coefficients. Driven by global environmental concerns, there is currently a strong push to discover practical lead-free piezoelectrics for device engineering. Using a combination of epitaxial growth techniques in conjunction with theoretical approaches, we show the formation of a morphotropic phase boundary through epitaxial constraint in lead-free piezoelectric bismuth ferrite (BiFeO3) films. Electric field-dependent studies show that a tetragonal-like phase can be reversibly converted into a rhombohedral-like phase, accompanied by measurable displacements of the surface, making this new lead-free system of interest for probe-based data storage and actuator applications.

Nanoscale Control of Phase Variants in Strain-Engineered BiFeO3

Development of magnetoelectric, electromechanical, and photovoltaic devices based on mixed-phase rhombohedral-tetragonal (R-T) BiFeO3 (BFO) systems is possible only if the control of the engineered R phase variants is realized. Accordingly, we explore the mechanism of a bias induced phase transformation in this system. Single point spectroscopy demonstrates that the T -> R transition is activated at lower voltages compared to T -> - T polarization switching. With phase field modeling, the transition is shown to be electrically driven. We further demonstrate that symmetry of formed R-phase rosettes can be broken by a proximal probe motion, allowing controlled creation of R variants with defined orientation. This approach opens a pathway to designing next-generation magnetoelectronic and data storage devices in the nanoscale.

Digital Exposure of English Place-names (DEEP)

Place-names are a fundamental concept in all academic collections: everything happens somewhere. Contemporary place-names are comprehensively represented in digital gazetteer and geospatial web services such as GeoNames. However, despite millions of pounds of investment by JISC and other agencies in historical online resources in recent years, there is currently no equivalent for historic place-names. This project will digitize the entire 86 volume corpus of the Survey of English Place-Names (SEPN), the ultimate authority on historic place-names in England, and make its 4 million forms available.

Tuneable magneto-optical metamaterials based on photonic resonances in nickel nanorod arrays

We investigate the magneto-optical properties of a nanostructured metamaterial comprised of arrays of nickel nanorods embedded in an anodized aluminum oxide template. The rods are grown using a self-assembly bottom-up technique that provides a uniform, quasi-hexagonal array over a large area, quickly and at low cost. The tuneability of the magneto-optic response of the material is investigated by varying the nanorod dimensions: diameter, length and inter-rod spacing as well as the overall thickness of the template. It is demonstrated that the system acts as a sub-wavelength light trap with enhanced magneto-optical properties occurring at reflectivity minima corresponding to photonic resonances of the metamaterial. Changes in dimensions of the nickel rods on the order of tens of nanometers cause a spectral blue-shift in the peak magneto-optical response of 270 nm in the visible range. A plasmonic enhancement is also observed at lower wavelengths, which becomes increasingly damped with larger diameters and increased volume fraction of nickel inclusions. This type of structure has potential applications in high density magneto-optical data storage (up to 1011–12 rods per square inch), ultrafast magneto-plasmonic switching and optical components for telecommunications.

Optical and magneto-optical properties of gold core cobalt shell magnetoplasmonic nanowire arrays

In this work we present core–shell nanowire arrays of gold coated with a nanometric layer of cobalt. Despite the extremely small Co volume, these core–shell nanowires display large magneto-optical activity and plasmonic resonance determined by the geometry of the structure. Therefore, we are able to tune both the plasmonic and magneto-optical response in the visible range. Through optical and ellipsometric measurements in transmission, and applying a magnetic field to the sample, it is possible to modulate the value of the phase angle (Del {Δ}) between the S and P polarised components. It was found that the core–shell sample produced an order of magnitude larger variation in Del with changing magnetic field direction, compared with hollow cobalt tubes. The enhancement of magneto optical properties through the plasmonic nature of the gold core is complemented with the ability to induce magnetic influence over optical properties via an externally applied field. Moreover, we demonstrate for the first time the ability to use the remanent magnetisation of the Co, in conjunction with the optical properties defined by the Au, to observe remanent optical states in this uniquely designed structure. This new class of magnetoplasmonic metamaterial has great potential in a wide range of applications, from bio-sensing to data storage due to the tuneable nature of multiple resonance modes and dual functionality.

Software as a Service: Analysing Security Issues

Software-as-a-service (SaaS) is a type of software service delivery model which encompasses a broad range of business opportunities and challenges. Users and service providers are reluctant to integrate their business into SaaS due to its security concerns while at the same time they are attracted by its benefits. This article highlights SaaS utility and applicability in different environments like cloud computing, mobile cloud computing, software defined networking and Internet of things. It then embarks on the analysis of SaaS security challenges spanning across data security, application security and SaaS deployment security. A detailed review of the existing mainstream solutions to tackle the respective security issues mapping into different SaaS security challenges is presented. Finally, possible solutions or techniques which can be applied in tandem are presented for a secure SaaS platform.

Brillouin light scattering by spin waves in magnetic metamaterials based on Co nanorods

We report on the investigations of spin wave modes in arrays of densely packed Co nanorods using Brillouin light scattering. We have observed a significant role of spin wave modes along the nanorod axis in contrast to infinite magnetic nanowires. Unusual optical properties featuring an inverted Stokes/anti-Stokes asymmetry of the Brillouin scattering spectra have been observed. The spectrum of spin wave modes in the nanorod array has been calculated and compared with the experiment. Experimental observations are explained in terms of a combined numerical-analytical approach taking into account both the low aspect ratio of individual magnetic nanorods and dipolar magnetic coupling between the nanorods in the array. The optical studies of spin-wave modes in the metamaterials with low aspect ratio nanorods have revealed new magnetic and magneto-optical properties compared to continuous magnetic films or infinite magnetic nanowires. Such magnetic metamaterials are important class of active metamaterials needed for prospective data storage and signal processing applications. (c) 2012 Optical Society of America

Brillouin scattering of light by spin waves in ferromagnetic nanorods

We report the investigations of spin wave modes of arrays of Ni and Co nanorods using Brillouin light scattering. We have revealed the significant influence of spin wave modes along the nanorod axis in contrast to infinite magnetic nanowires. Unusual optical properties featuring an inverted Stokes/anti-Stokes asymmetry of the Brillouin scattering spectra have been observed. The spectrum of spin wave modes in the nanorod array has been calculated and compared with the experiment. Experimental observations are explained in terms of a combined numerical-analytical approach taking into account both the low aspect ratio of individual magnetic nanorods and dipolar magnetic coupling between the nanorods in the array. The optical studies of spin-wave modes in nanorod metamaterials with low aspect ratio nanorods have revealed new magnetic and magneto-optical properties compared to continuous magnetic films or infinite magnetic nanowires. Such magnetic artificial materials are important class of active metamaterials needed for prospective data storage and signal processing applications. © 2012 Elsevier B.V.

Computational cancer biology: education is a natural key to many locks

Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.

The impact of next generation sequencing technologies on haematological research - A review

Next-generation sequencing (NGS) technologies have begun to revolutionize the field of haematological malignancies through the assessment of a patient's genetic makeup with a minimal cost. Significant discoveries have already provided a unique insight into disease initiation, risk stratification and therapeutic intervention. Sequencing analysis will likely form part of the routine diagnostic testing in the future. However, a number of important issues need to be addressed for that to become a reality with regard to result interpretation, laboratory workflow, data storage and ethical issues. In this review we summarize the contribution that NGS has already made to the field of haematological malignancies. Finally, we discuss the challenges that NGS technologies will bring in relation to data storage, ethical and legal issues and laboratory validation. Despite these challenges, we predict that high-throughput DNA sequencing will redefine haematological malignancies based on individualized genomic analysis.

CSFinder: A Cold-Start Friend Finder in Large-Scale Social Networks

Recommending users for a new social network user to follow is a topic of interest at present. The existing approaches rely on using various types of information about the new user to determine recommended users who have similar interests to the new user. However, this presents a problem when a new user joins a social network, who is yet to have any interaction on the social network. In this paper we present a particular type of conversational recommendation approach, critiquing-based recommendation, to solve the cold start problem. We present a critiquing-based recommendation system, called CSFinder, to recommend users for a new user to follow. A traditional critiquing-based recommendation system allows a user to critique a feature of a recommended item at a time and gradually leads the user to the target recommendation. However this may require a lengthy recommendation session. CSFinder aims to reduce the session length by taking a case-based reasoning approach. It selects relevant recommendation sessions of past users that match the recommendation session of the current user to shortcut the current recommendation session. It selects relevant recommendation sessions from a case base that contains the successful recommendation sessions of past users. A past recommendation session can be selected if it contains recommended items and critiques that sufficiently overlap with the ones in the current session. Our experimental results show that CSFinder has significantly shorter sessions than the ones of an Incremental Critiquing system, which is a baseline critiquing-based recommendation system.

Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments

Abstract
Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.
This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.

Leveraging Stratification in Twitter Sampling

With Tweet volumes reaching 500 million a day, sampling is inevitable for any application using Twitter data. Realizing this, data providers such as Twitter, Gnip and Boardreader license sampled data streams priced in accordance with the sample size. Big Data applications working with sampled data would be interested in working with a large enough sample that is representative of the universal dataset. Previous work focusing on the representativeness issue has considered ensuring the global occurrence rates of key terms, be reliably estimated from the sample. Present technology allows sample size estimation in accordance with probabilistic bounds on occurrence rates for the case of uniform random sampling. In this paper, we consider the problem of further improving sample size estimates by leveraging stratification in Twitter data. We analyze our estimates through an extensive study using simulations and real-world data, establishing the superiority of our method over uniform random sampling. Our work provides the technical know-how for data providers to expand their portfolio to include stratified sampled datasets, whereas applications are benefited by being able to monitor more topics/events at the same data and computing cost.