Providing nursing support within residential care homes

This study examines a joint NHS-Local Authority initiative providing a dedicated nursing and physiotherapy team to three residential care homes in Bath and North East Somerset. The initiative aims to meet the nursing needs of residents where they live and to train care home staff in basic nursing. * Hospital admissions and nursing home transfers were prevented. Care home staff and managers preferred residents to be able to stay in their home when they were ill, as did residents themselves. * Enhancing health-orientated education and training of care home staff was challenging at first but relationships improved, and the confidence and professionalism of care staff grew. * Residents’ nursing needs cannot simply be equated with their level of dependency. For example, a resident with dementia can be functionally independent yet have major, often un-communicated health needs. * The early detection of illness and resulting opportunity for early intervention was a major part of the team’s work. Residents were likely to benefit from improved quality of life. * Overall, estimates of costs and savings ranged from a 'worst case' scenario of £2.70 extra to a more likely scenario of £36.90 saved per resident per week. Savings were mainly in reduced use of NHS services, while the Primary Care Trust and Adult Social Services both funded the intervention, highlighting the need for partnership working to sustain funding. * The researchers conclude that any increase in cost should be measured against the benefits of promoting long-term quality of life, quality of care and providing a firm foundation for future workforce development

Accurate, rapid identification of dislocation lines in coherent diffractive imaging via a min-max optimization formulation

Defects such as dislocations impact materials properties and their response during external stimuli. Defect engineering has emerged as a possible route to improving the performance of materials over a wide range of applications, including batteries, solar cells, and semiconductors. Imaging these defects in their native operating conditions to establish the structure-function relationship and, ultimately, to improve performance has remained a considerable challenge for both electron-based and x-ray-based imaging techniques. However, the advent of Bragg coherent x-ray diffractive imaging (BCDI) has made possible the 3D imaging of multiple dislocations in nanoparticles ranging in size from 100 nm to1000 nm. While the imaging process succeeds in many cases, nuances in identifying the dislocations has left manual identification as the preferred method. Derivative-based methods are also used, but they can be inaccurate and are computationally inefficient. Here we demonstrate a derivative-free method that is both more accurate and more computationally efficient than either derivative- or human-based methods for identifying 3D dislocation lines in nanocrystal images produced by BCDI. We formulate the problem as a min-max optimization problem and show exceptional accuracy for experimental images. We demonstrate a 260x speedup for a typical experimental dataset with higher accuracy over current methods. We discuss the possibility of using this algorithm as part of a sparsity-based phase retrieval process. We also provide the MATLAB code for use by other researchers

Reliable Eigenspectra for New Generation Surveys

We present a novel technique to overcome the limitations of the applicability of Principal Component Analysis to typical real-life data sets, especially astronomical spectra. Our new approach addresses the issues of outliers, missing information, large number of dimensions and the vast amount of data by combining elements of robust statistics and recursive algorithms that provide improved eigensystem estimates step-by-step. We develop a generic mechanism for deriving reliable eigenspectra without manual data censoring, while utilising all the information contained in the observations. We demonstrate the power of the methodology on the attractive collection of the VIMOS VLT Deep Survey spectra that manifest most of the challenges today, and highlight the improvements over previous workarounds, as well as the scalability of our approach to collections with sizes of the Sloan Digital Sky Survey and beyond.Comment: 7 pages, 3 figures, accepted to MNRA

N=4 SYM on S^3 with Near Critical Chemical Potentials

We study the N = 4 theory at weak coupling, on a three sphere in the grand canonical ensemble with R symmetry chemical potentials. We focus attention on near critical values for the chemical potentials, above which the classical theory has no ground state. By computing a one loop effective potential for the light degrees of freedom in this regime, we show the existence of flat directions of complex dimension N, 2N and 3N for one, two and three critical chemical potentials respectively; these correspond to one half, one quarter and one-eighth BPS states becoming light respectively at the critical values. At small finite temperature we show that the chemical potentials can be continued beyond their classical limiting values to yield a deconfined metastable phase with lifetime diverging in the large N limit. Our low temperaure analysis complements the high temperature metastability found by Yamada and Yaffe. The resulting phase diagram at weak coupling bears a striking resemblance to the strong coupling phase diagram for charged AdS black holes. Our analysis also reveals subtle qualitative differences between the two regimes.Comment: 34 pages, 4 figure

Integrating Case-Based Reasoning with Adaptive Process Management

The need for more flexiblity of process-aware information systems (PAIS) has been discussed for several years and different approaches for adaptive process management have emerged. Only few of them provide support for both changes of individual process instances and the propagation of process type changes to a collection of related process instances. The knowledge about changes has not yet been exploited by any of these systems. To overcome this practical limitation, PAIS must capture the whole process life cycle and all kinds of changes in an integrated way. They must allow users to deviate from the predefined process in exceptional situations, and assist them in retrieving and reusing knowledge about previously performed changes. In this report we present a proof-of concept implementation of a learning adaptive PAIS. The prototype combines the ADEPT2 framework for dynamic process changes with concepts and methods provided by case-based reasoning(CBR) technology

Seasonal cycles of ozone and oxidized nitrogen species in northeast Asia - 2:A model analysis of the roles of chemistry and transport

[1] The dominant factors controlling the seasonal variations of ozone (O-3) and three major oxidized nitrogen species, peroxyacetyl nitrate (PAN), nitrogen oxides (NOx), and nitric acid (HNO3), in northeast Asia are investigated by using a three-dimensional global chemical transport model to analyze surface observations made at Rishiri Island, a remote island in northern Japan. The model was evaluated by comparing with observed seasonal variations, and with the relationships between O-3, CO, and PAN. We show that the model reproduces the chemical environment at Rishiri Island reasonably well, and that the seasonal cycles of O-3, CO, NOy species, and VOCs are well predicted. The impact of local emissions on some of these constituents is significant, but is not the dominant factor affecting the seasonal cycles. The seasonal roles of chemistry and transport in controlling O-3 and PAN are revealed by examining production/ destruction and import/ export/deposition fluxes in the boundary layer over the Rishiri region. For O-3, transport plays a key role throughout the year, and the regional photochemical contribution is at most 10% in summer. For PAN, in contrast, transport dominates in winter, while in-situ chemistry contributes as much as 75% in summer. It is suggested that the relative contribution of transport and in-situ chemistry is significantly different for O-3 and PAN, but that the wintertime dominance of transport due to the long chemical lifetimes of these species is sufficient to drive the seasonal cycles of springtime maximum and summertime minimum characteristic of remote sites

Adiabatic Quantum Search in Open Systems

Adiabatic quantum algorithms represent a promising approach to universal quantum computation. Whilst in a closed system these algorithms are limited by avoided level crossings, where the gap becomes exponentially small in the system size, their robustness in open systems remains unresolved. We study the dynamics in the proximity of such an avoided level crossing associated with the adiabatic quantum search algorithm in a quantum system that is coupled to a generic environment. At zero temperature, we find that the algorithm remains scalable provided the noise spectral density of the environment decays sufficiently fast at low frequencies. At finite temperature, however, scattering processes render the algorithm inefficient and no quantum speedup can be achieved. Owing to the generic nature of our model, we expect our results to be widely applicable to other adiabatic quantum algorithms.Comment: Accepted version. 6 pages, 2 figures, 10 pages supplemental material