The Aryne Ene Reaction

Intermolecular aryne ene reactions present opportunities to arylate a wide range of unsaturated substrates in a single step, whilst intramolecular reactions provide expedient access to valuable benzofused carbo- and heterocyclic frameworks. This short review will chart the development of the aryne ene reaction from initial reports that rationalise unexpected byproduct formation in competing [4+2] and [2+2] cycloadditions through to its exploitation in contemporary synthetic methodology

Fast Predictive Simple Geodesic Regression

Deformable image registration and regression are important tasks in medical image analysis. However, they are computationally expensive, especially when analyzing large-scale datasets that contain thousands of images. Hence, cluster computing is typically used, making the approaches dependent on such computational infrastructure. Even larger computational resources are required as study sizes increase. This limits the use of deformable image registration and regression for clinical applications and as component algorithms for other image analysis approaches. We therefore propose using a fast predictive approach to perform image registrations. In particular, we employ these fast registration predictions to approximate a simplified geodesic regression model to capture longitudinal brain changes. The resulting method is orders of magnitude faster than the standard optimization-based regression model and hence facilitates large-scale analysis on a single graphics processing unit (GPU). We evaluate our results on 3D brain magnetic resonance images (MRI) from the ADNI datasets.Comment: 19 pages, 10 figures, 13 table

High-Performance, Wearable Thermoelectric Generator Based on a Highly Aligned Carbon Nanotube Sheet

A high-performance, wearable thermoelectric generator (TEG) was fabricated with a highly aligned carbon nanotube (CNT) sheet. The aligned CNT sheet exhibits extraordinary electrical conductivity compared to disordered CNT sheets and also can be directly fabricated as a continuous TEG without metal electrode interconnects. This provides a significant reduction in contact resistance between TE legs and electrodes compared to traditional TEGs, resulting in higher power output. In addition, the continuity of the module without any disconnected parts provides high degrees of mechanical stability and durability. This robust and scalable approach to flexible TEG fabrication paves the way for CNT applications in lightweight, flexible, and wearable electronics

The response of embedded strain sensors in concrete beams subjected to thermal loading

A wide range of commercially available sensors are frequently used to record the response of civil engineering structures that may be subjected to unexpected loading scenarios, changes of environmental conditions or material deterioration. However, a common problem faced when using these sensors is to distinguish strain changes experienced by the structure due to a temperature change from strain changes that occur due to other causes. Temperature effects on strain sensors are usually accommodated by allowing for temperature effects (temperature compensation); however, there is limited research in the literature that investigates the performance of strain sensor measurements when subjected to temperature change. Understanding the temperature effect on strain sensors will greatly enhance the ability of civil engineers to monitor the performance of structural materials. In this paper, different types of commonly used and advanced strain sensors have been installed in a reinforced concrete beam to measure the thermal strain response of concrete under different temperature conditions. The experimental results demonstrated a 25-30% difference in strain measurements from the different sensors. It is shown in this paper that this difference is due to the combined effects of sensor inaccuracy, uncertainties related to the testing conditions and uncertainties associated with the temperature compensation methods.The authors would like to acknowledge Dr. Peter Long, Martin Touhey and the Engineering Structures Laboratory technical staff at University of Cambridge for their assistance through the experimental program. The authors are also grateful to the Cambridge Center for Smart Infrastructure and Construction for supporting this research project.This is the accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S0950061814008642

A topological Dirac insulator in a quantum spin Hall phase : Experimental observation of first strong topological insulator

When electrons are subject to a large external magnetic field, the conventional charge quantum Hall effect \cite{Klitzing,Tsui} dictates that an electronic excitation gap is generated in the sample bulk, but metallic conduction is permitted at the boundary. Recent theoretical models suggest that certain bulk insulators with large spin-orbit interactions may also naturally support conducting topological boundary states in the extreme quantum limit, which opens up the possibility for studying unusual quantum Hall-like phenomena in zero external magnetic field. Bulk Bi$_{1-x}$Sb$_x$ single crystals are expected to be prime candidates for one such unusual Hall phase of matter known as the topological insulator. The hallmark of a topological insulator is the existence of metallic surface states that are higher dimensional analogues of the edge states that characterize a spin Hall insulator. In addition to its interesting boundary states, the bulk of Bi$_{1-x}$Sb$_x$ is predicted to exhibit three-dimensional Dirac particles, another topic of heightened current interest. Here, using incident-photon-energy-modulated (IPEM-ARPES), we report the first direct observation of massive Dirac particles in the bulk of Bi$_{0.9}$Sb$_{0.1}$, locate the Kramers' points at the sample's boundary and provide a comprehensive mapping of the topological Dirac insulator's gapless surface modes. These findings taken together suggest that the observed surface state on the boundary of the bulk insulator is a realization of the much sought exotic "topological metal". They also suggest that this material has potential application in developing next-generation quantum computing devices.Comment: 16 pages, 3 Figures. Submitted to NATURE on 25th November(2007

Spontaneous Synchrony Breaking

Research on synchronization of coupled oscillators has helped explain how uniform behavior emerges in populations of non-uniform systems. But explaining how uniform populations engage in sustainable non-uniform synchronization may prove to be just as fascinating

One-loop SYM-supergravity relation for five-point amplitudes

We derive a linear relation between the one-loop five-point amplitude of N=8 supergravity and the one-loop five-point subleading-color amplitudes of N=4 supersymmetric Yang-Mills theory.Comment: 17 pages, 2 figures; v2: very minor correction

Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease

The joint analysis of biomedical data in Alzheimer's Disease (AD) is important for better clinical diagnosis and to understand the relationship between biomarkers. However, jointly accounting for heterogeneous measures poses important challenges related to the modeling of the variability and the interpretability of the results. These issues are here addressed by proposing a novel multi-channel stochastic generative model. We assume that a latent variable generates the data observed through different channels (e.g., clinical scores, imaging, ...) and describe an efficient way to estimate jointly the distribution of both latent variable and data generative process. Experiments on synthetic data show that the multi-channel formulation allows superior data reconstruction as opposed to the single channel one. Moreover, the derived lower bound of the model evidence represents a promising model selection criterion. Experiments on AD data show that the model parameters can be used for unsupervised patient stratification and for the joint interpretation of the heterogeneous observations. Because of its general and flexible formulation, we believe that the proposed method can find important applications as a general data fusion technique.Comment: accepted for presentation at MLCN 2018 workshop, in Conjunction with MICCAI 2018, September 20, Granada, Spai

Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction

Estimating uncertainty of camera parameters computed in Structure from Motion (SfM) is an important tool for evaluating the quality of the reconstruction and guiding the reconstruction process. Yet, the quality of the estimated parameters of large reconstructions has been rarely evaluated due to the computational challenges. We present a new algorithm which employs the sparsity of the uncertainty propagation and speeds the computation up about ten times \wrt previous approaches. Our computation is accurate and does not use any approximations. We can compute uncertainties of thousands of cameras in tens of seconds on a standard PC. We also demonstrate that our approach can be effectively used for reconstructions of any size by applying it to smaller sub-reconstructions.Comment: ECCV 201

Self-Assembling Hydrogels Based on a Complementary Host-Guest Peptide Amphiphile Pair

Supramolecular polymer-based biomaterials play a significant role in current biomedical research. In particular, peptide amphiphiles (PAs) represent a promising material platform for biomedical applications given their modular assembly, tunability, and capacity to render materials with structural and molecular precision. However, the possibility to provide dynamic cues within PA-based materials would increase the capacity to modulate their mechanical and physical properties and, consequently, enhance their functionality and broader use. In this study, we report on the synthesis of a cationic PA pair bearing complementary adamantane and β-cyclodextrin host–guest cues and their capacity to be further incorporated into self-assembled nanostructures. We demonstrate the possibility of these recognition motifs to selectively bind, enabling noncovalent cross-linking between PA nanofibers and endowing the resulting supramolecular hydrogels with enhanced mechanical properties, including stiffness and resistance to degradation, while retaining in vitro biocompatibility. The incorporation of the host–guest PA pairs in the resulting hydrogels allowed not only for macroscopic mechanical control from the molecular scale, but also for the possibility to engineer further spatiotemporal dynamic properties, opening opportunities for broader potential applications of PA-based materials