A quality improvement project using a problem based post take ward round proforma based on the SOAP acronym to improve documentation in acute surgical receiving

Objectives: Ward round documentation provides one of the most important means of communication between healthcare professionals. We aimed to establish if the use of a problem based standardised proforma can improve documentation in acute surgical receiving. Methods: Gold standards were established using the RCSE record keeping guidelines. We audited documentation for seven days using the following headings: patient name/identification number, subjective findings, objective findings, clinical impression/diagnosis, plan, diet status, discharge decision, discharge planning, signature, and grade. After the initial audit cycle, a ward round proforma was introduced using the above headings and re-audited over a seven day period. Results: The pre-intervention arm contained 50 patients and the post intervention arm contained 47. The following headings showed an improvement in documentation compliance to 100%: patient name/identification number vs 96%, subjective findings vs 84%, objective findings vs 48%, plan vs 98%, signature vs 96%, and grade vs 62%. Documentation of the clinical impression/diagnosis improved to 98% vs 30%, diet status rose to 83% vs 16%, discharge decision to 66% vs 16%, and discharge planning to 40% vs 20%. Conclusions: Standardised proformas improve the documentation of post-take ward round notes. This helps to clarify the onward management plan for all aspects of a patient's care and will help avoid adverse events and litigation. This should improve the quality and safety of Patient Care

Feasibility study on conducting overflight measurements of shaped sonic boom signatures using the Firebee BQM-34E RPV

A study was performed to determine the feasibility of establishing if a 'shaped' sonic boom signature, experimentally shown in wind tunnel models out to about 10 body lengths, will persist out to representative flight conditions of 200 to 300 body lengths. The study focuses on the use of a relatively large supersonic remotely-piloted and recoverable vehicle. Other simulation methods that may accomplish the objective are also addressed and include the use of nonrecoverable target drones, missiles, full-scale drones, very large wind tunnels, ballistic facilities, whirling-arm techniques, rocket sled tracks, and airplane nose probes. In addition, this report will also present a background on the origin of the feasibility study including a brief review of the equivalent body concept, a listing of the basic sonic boom signature characteristics and requirements, identification of candidate vehicles in terms of desirable features/availability, and vehicle characteristics including geometries, area distributions, and resulting sonic boom signatures. A program is developed that includes wind tunnel sonic boom and force models and tests for both a basic and modified vehicles and full-scale flight tests

Markers for the identification of late breast cancer recurrence

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited

Gait recognition based on shape and motion analysis of silhouette contours

This paper presents a three-phase gait recognition method that analyses the spatio-temporal shape and dynamic motion (STS-DM) characteristics of a human subject’s silhouettes to identify the subject in the presence of most of the challenging factors that affect existing gait recognition systems. In phase 1, phase-weighted magnitude spectra of the Fourier descriptor of the silhouette contours at ten phases of a gait period are used to analyse the spatio-temporal changes of the subject’s shape. A component-based Fourier descriptor based on anatomical studies of human body is used to achieve robustness against shape variations caused by all common types of small carrying conditions with folded hands, at the subject’s back and in upright position. In phase 2, a full-body shape and motion analysis is performed by fitting ellipses to contour segments of ten phases of a gait period and using a histogram matching with Bhattacharyya distance of parameters of the ellipses as dissimilarity scores. In phase 3, dynamic time warping is used to analyse the angular rotation pattern of the subject’s leading knee with a consideration of arm-swing over a gait period to achieve identification that is invariant to walking speed, limited clothing variations, hair style changes and shadows under feet. The match scores generated in the three phases are fused using weight-based score-level fusion for robust identification in the presence of missing and distorted frames, and occlusion in the scene. Experimental analyses on various publicly available data sets show that STS-DM outperforms several state-of-the-art gait recognition methods

Automatic Detection of Expanding HI Shells Using Artificial Neural Networks

The identification of expanding HI shells is difficult because of their variable morphological characteristics. The detection of HI bubbles on a global scale therefore never has been attempted. In this paper, an automatic detector for expanding HI shells is presented. The detection is based on the more stable dynamical characteristics of expanding shells and is performed in two stages. The first one is the recognition of the dynamical signature of an expanding bubble in the velocity spectra, based on the classification of an artificial neural network. The pixels associated with these recognized spectra are identified on each velocity channel. The second stage consists in looking for concentrations of those pixels that were firstly pointed out, and to decide if they are potential detections by morphological and 21-cm emission variation considerations. Two test bubbles are correctly detected and a potentially new case of shell that is visually very convincing is discovered. About 0.6% of the surveyed pixels are identified as part of a bubble. These may be false detections, but still constitute regions of space with high probability of finding an expanding shell. The subsequent search field is thus significantly reduced. We intend to conduct in the near future a large scale HI shells detection over the Perseus Arm using our detector.Comment: 39 pages, 11 figures, accepted by PAS

Defining signatures of arm-wise copy number change and their associated drivers in kidney cancers

Using pan-cancer data from The Cancer Genome Atlas (TCGA), we investigated how patterns in copy number alterations in cancer cells vary both by tissue type and as a function of genetic alteration. We find that patterns in both chromosomal ploidy and individual arm copy number are dependent on tumour type. We highlight for example, the significant losses in chromosome arm 3p and the gain of ploidy in 5q in kidney clear cell renal cell carcinoma tissue samples. We find that specific gene mutations are associated with genome-wide copy number changes. Using signatures derived from non-negative matrix factorisation (NMF), we also find gene mutations that are associated with particular patterns of ploidy change. Finally, utilising a set of machine learning classifiers, we successfully predicted the presence of mutated genes in a sample using arm-wise copy number patterns as features. This demonstrates that mutations in specific genes are correlated and may lead to specific patterns of ploidy loss and gain across chromosome arms. Using these same classifiers, we highlight which arms are most predictive of commonly mutated genes in kidney renal clear cell carcinoma (KIRC)