"5 Days in August" – How London Local Authorities used Twitter during the 2011 riots

© IFIP International Federation for Information Processing 2012This study examines effects of microblogging communications during emergency events based on the case of the summer 2011 riots in London. During five days in August 2011, parts of London and other major cities in England suffered from extensive public disorders, violence and even loss of human lives. We collected and analysed the tweets posted by the official accounts maintained by 28 London local government authorities. Those authorities used Twitter for a variety of purposes such as preventing rumours, providing official information, promoting legal actions against offenders and organising post-riot community engagement activities. The study shows how the immediacy and communicative power of microblogging can have a significant effect at the response and recovery stages of emergency events

Moving lattice kinks and pulses: an inverse method

We develop a general mapping from given kink or pulse shaped travelling-wave solutions including their velocity to the equations of motion on one-dimensional lattices which support these solutions. We apply this mapping - by definition an inverse method - to acoustic solitons in chains with nonlinear intersite interactions, to nonlinear Klein-Gordon chains, to reaction-diffusion equations and to discrete nonlinear Schr\"odinger systems. Potential functions can be found in at least a unique way provided the pulse shape is reflection symmetric and pulse and kink shapes are at least $C^2$ functions. For kinks we discuss the relation of our results to the problem of a Peierls-Nabarro potential and continuous symmetries. We then generalize our method to higher dimensional lattices for reaction-diffusion systems. We find that increasing also the number of components easily allows for moving solutions.Comment: 15 pages, 5 figure

Investigation of the23Na(p, γ)24Mg and 23Na(p, α)20Ne reactions via (3He,d) spectroscopy

States near the 23Na+p threshold in 24Mg were investigated using the 23Na(3He,d)24Mg reaction over the angular range of 5° ≤ θlab ≤ 35° at E(3He)=20 MeV. Spectroscopic factors were extracted for states corresponding to resonances in the 23Na(p, γ) 24Mg and 23Na(p, α)20Ne reactions. We find that one state, corresponding to a previously unobserved resonance at Ec.m.= 138 keV, may make a significant contribution to the rates of both reactions at low temperatures. Another state, corresponding to a possible resonance at Ec.m.=37 keV may make a small contribution to the 23Na(p, α)20Ne reaction. New rates for the 23Na(p, γ)24Mg and 23Na(p, α) 20Ne reactions are presented and the astrophysical implications are discussed

Investigation of the 22Ne(p,y)23Na reaction via a (3He,d) spectroscopy

States near the [Formula Presented] threshold in [Formula Presented] were investigated using the [Formula Presented] reaction over the angular range of [Formula Presented] at [Formula Presented] Spectroscopic factors were extracted for states corresponding to resonances in the [Formula Presented] reaction. Two previously suggested resonances at [Formula Presented] and 100 keV were not observed at any angle. A new rate for the [Formula Presented] reaction has been calculated and its implications are discussed

Magnetic Field Generation in Stars

Enormous progress has been made on observing stellar magnetism in stars from the main sequence through to compact objects. Recent data have thrown into sharper relief the vexed question of the origin of stellar magnetic fields, which remains one of the main unanswered questions in astrophysics. In this chapter we review recent work in this area of research. In particular, we look at the fossil field hypothesis which links magnetism in compact stars to magnetism in main sequence and pre-main sequence stars and we consider why its feasibility has now been questioned particularly in the context of highly magnetic white dwarfs. We also review the fossil versus dynamo debate in the context of neutron stars and the roles played by key physical processes such as buoyancy, helicity, and superfluid turbulence,in the generation and stability of neutron star fields. Independent information on the internal magnetic field of neutron stars will come from future gravitational wave detections. Thus we maybe at the dawn of a new era of exciting discoveries in compact star magnetism driven by the opening of a new, non-electromagnetic observational window. We also review recent advances in the theory and computation of magnetohydrodynamic turbulence as it applies to stellar magnetism and dynamo theory. These advances offer insight into the action of stellar dynamos as well as processes whichcontrol the diffusive magnetic flux transport in stars.Comment: 41 pages, 7 figures. Invited review chapter on on magnetic field generation in stars to appear in Space Science Reviews, Springe

Understanding the ellagitannin extraction process from oak wood

[EN] The extractability of the main oak ellagitannins has been studied in five model solutions containing different types of oak chips (two sizes and different toasting degrees for each size). A new extraction kinetic model has been proposed from the quantitative experimental results obtained by means of HPLCeESI-MS/MS-multiple reaction monitoring method. The model considers an initial extraction (i.e., washing step) followed by a diffusion step, which involves two different processes that follow first-order kinetics at different rates. Differences in the extractability of the ellagitannins in the different model solutions have been observed and explained on the basis of the kinetic model here proposed

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Delivery of antimicrobial stewardship competencies in UK pre-registration nurse education programmes: a national cross-sectional survey

Background: Registered nurses perform numerous functions critical to the success of antimicrobial stewardship but only 63% of pre-registration nursing programmes include any teaching about stewardship. Updated nursing standards highlight nurses require antimicrobial stewardship knowledge and skills. Aim: To explore the delivery of key antimicrobial stewardship competencies within updated pre-registration nursing programmes. Method: A cross-sectional survey design. Data was collected between March and June 2021. Findings: Lecturers from 35 universities responsible for teaching antimicrobial stewardship participated. The provision of antimicrobial stewardship teaching and learning was inconsistent across programmes with competencies in infection prevention and control, patient centred care, and interprofessional collaborative practice taking precedent over those pertaining to the use, management, and monitoring of antimicrobials. On-line learning and teaching surrounding hand hygiene, personal protective equipment, and immunisation theory was reported to have increased during the pandemic. Only a small number of respondents reported that students shared taught learning with other healthcare professional groups. Conclusion: There is a need to ensure consistency in antimicrobial stewardship across programmes, and greater knowledge pertaining to the use, management and monitoring of antimicrobials should be included. Programmes need to adopt teaching strategies and methods that allow nurses to develop interprofessional skill in order to practice collaboratively

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types