Carbon nanotube modified carbon composite monoliths as superior adsorbents for carbon dioxide capture

Carbon composite monoliths were prepared from a commercial phenolic resin mixed with just 1 wt% of carbon nanotubes (CNTs) followed by carbonization and physical activation with CO. The products possess a hierarchical macroporous-microporous structure and superior CO adsorption properties. In particular, they show the top-ranked CO capacity (52 mg CO per g adsorbent at 25 °C and 114 mmHg) under low CO partial pressures, which is of more relevance for flue gas applications. This matches or exceeds those of carbons produced by complex chemical activation and functionalization. Our study demonstrates an effective way to create narrow micropores through structural modification of carbon composites by CNTs. © 2013 The Royal Society of Chemistry.

Habitat Isolation Reduces the Temporal Stability of Island Ecosystems in the Face of Flood Disturbance

Natural ecosystems are increasingly exposed to multiple anthropogenic stressors, including land-use change, deforestation, agricultural intensification, and urbanisation, all of which have led to widespread habitat fragmentation, which is also likely to be amplified further by predicted climate change. The potential interactive effects of these different stressors cannot be determined by studying each in isolation, although such synergies have been largely ignored in ecological field studies to date. Here, we use a model system of naturally fragmented islands in a braided river network, which is exposed to periodic inundation, to investigate the interactive effects of habitat isolation and flood disturbance. Food web structure was similar across the islands during periods of hydrological stability, but several key properties were altered in the aftermath of flood disturbance, based on distance of the islands from the regional source pool of species: taxon richness and mean food chain length declined with habitat isolation after flooding, while the proportion of basal species increased. Greater species turnover through time reflected the slower process of re-colonisation on the more distant islands following disturbance. Increased variability of several food web properties over a 1-year period highlighted the reduced temporal stability of isolated habitat fragments. Many of these effects reflected the differential successes of predator and prey species at re-colonising the islands: even though larger, more mobile consumers may reach the more distant islands first, they cannot establish populations until the lower trophic levels have successfully reassembled. These results highlight the susceptibility of fragmented ecosystems to environmental perturbations. © 2013 Elsevier Ltd.

Real-Time Face Recognition from Surveillance Video

This chapter describes an experimental system for the recognition of human faces from surveillance video. In surveillance applications, the system must be robust to changes in illumination, scale, pose and expression. The system must also be able to perform detection and recognition rapidly in real time. Our system detects faces using the Viola-Jones face detector, then extracts local features to build a shape-based feature vector. The feature vector is constructed from ratios of lengths and differences in tangents of angles, so as to be robust to changes in scale and rotations in-plane and out-of-plane. Consideration was given to improving the performance and accuracy of both the detection and recognition steps.

A systematic review evaluating the impact of online or blended learning vs. face-to-face learning of clinical skills in undergraduate nurse education.

Aim: To determine whether the use of an online or blended learning paradigm has the potential to enhance the teaching of clinical skills in undergraduate nursing.

Background: The need to adequately support and develop students in clinical skills is now arguably more important than previously considered due to reductions in practice opportunities. Online and blended teaching methods are being developed to try and meet this requirement, but knowledge about their effectiveness in teaching clinical skills is limited.

Design: Mixed methods systematic review, which follows the Joanna Briggs Institute User guide version 5.

Data Sources: Computerized searches of five databases were undertaken for the period 1995-August 2013.

Review Methods: Critical appraisal and data extraction were undertaken using Joanna Briggs Institute tools for experimental/observational studies and interpretative and critical research. A narrative synthesis was used to report results.

Results: Nineteen published papers were identified. Seventeen papers reported on online approaches and only two papers reported on a blended approach. The synthesis of findings focused on the following four areas: performance/clinical skill, knowledge, self-efficacy/clinical confidence and user experience/satisfaction. The e-learning interventions used varied throughout all the studies.

Conclusion: The available evidence suggests that online learning for teaching clinical skills is no less effective than traditional means. Highlighted by this review is the lack of available evidence on the implementation of a blended learning approach to teaching clinical skills in undergraduate nurse education. Further research is required to assess the effectiveness of this teaching methodology.

3D Morphable Model Construction for Robust Ear and Face Recognition

Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online.

Microstructure, properties and application of YAl2 intermetallic compound as particle reinforcements

An yttrium aluminum (YAl2) intermetallic compound ingot was prepared in an induction furnace under vacuum. The microstructure of YAl2 ingot was characterized by optical microscopy, scanning electron microscopy, and X-ray diffraction. The load bearing response of YAl2 intermetallic was investigated and compared with SiC ceramic by indentation combined with optical microscopy and scanning electron microscopy. Additionally, the tensile properties of the Mg–Li matrix composites reinforced with ultrafine YAl2 particles fabricated by planet ball milling were tested. The results show that the intermetallic compound ingot in this experiment is composed of a main face-centered-cubic structure YAl2 phase, a small amount of YAl phase, and minor Y and Al-rich phases. YAl2 intermetallic compound has excellent stability and shows better capability in crack resistance than SiC ceramic. The YAl2 intermetallic compound has better deformation compatibility with the Mg–14Li–3Al matrix than SiC reinforcement with the matrix, which leads to the superior resistance to crack for YAl2p/Mg–14Li–3Al composite compared to SiCp/Mg–14Li–3Al composite.

Turning Indium Oxide into a Superior Electrocatalyst:Deterministic Heteroatoms

The efficient electrocatalysts for many heterogeneous catalytic processes in energy conversion and storage systems must possess necessary surface active sites. Here we identify, from X-ray photoelectron spectroscopy and density functional theory calculations, that controlling charge density redistribution via the atomic-scale incorporation of heteroatoms is paramount to import surface active sites. We engineer the deterministic nitrogen atoms inserting the bulk material to preferentially expose active sites to turn the inactive material into a sufficient electrocatalyst. The excellent electrocatalytic activity of N-In2O3 nanocrystals leads to higher performance of dye-sensitized solar cells (DSCs) than the DSCs fabricated with Pt. The successful strategy provides the rational design of transforming abundant materials into high-efficient electrocatalysts. More importantly, the exciting discovery of turning the commonly used transparent conductive oxide (TCO) in DSCs into counter electrode material means that except for decreasing the cost, the device structure and processing techniques of DSCs can be simplified in future.

Robust bimodal person identification using face and speech with limited training data and corruption of both modalities

This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.

The Muslim Brotherhood: the Arab Spring its Future Face

The Muslim Brotherhood is the most significant and enduring Sunni Islamist organization of the contemporary era. Its roots lie in the Middle East but it has grown into both a local and global movement, with its well-placed branches reacting effectively to take the opportunities for power and electoral competition offered by the Arab Spring.

Regarded by some as a force of moderation among Islamists, and by others as a façade hiding a terrorist fundamentalist threat, the potential influence of the Muslim Brotherhood on Middle Eastern politics remains ambiguous.The Muslim Brotherhood: The Arab Spring and its Future Face provides an essential insight into the organisation, with chapters devoted to specific cases where the Brotherhood has important impacts on society, the state and politics. Key themes associated with the Brotherhood, such as democracy, equality, pan-Islamism, radicalism, reform, the Palestine issue and gender, are assessed to reveal an evolutionary trend within the movement since its founding in Egypt in 1928 to its manifestation as the largest Sunni Islamist movement in the Middle East in the 21st century. The book addresses the possible future of the Muslim Brotherhood; whether it can surprise sceptics and effectively accommodate democracy and secular trends, and how its ascension to power through the ballot box might influence Western policy debates on their engagement with this manifestation of political Islam.

Drawing on a wide range of sources, this book presents a comprehensive study of a newly resurgent movement and is a valuable resource for students, scholars and policy makers focused on Middle Eastern Politics.