42,085 research outputs found
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
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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 BiSb 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 BiSb 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
BiSb, 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
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