Role of the community matron in advance care planning and ‘do not attempt CPR’ decision-making: a qualitative study

The community matron (CM) is often the key worker caring for patients with chronic, life-limiting, long-term conditions, but these patients are not always recognised as palliative cases. This study explored the experiences of CMs with regard to advance care planning (ACP) and ‘do not attempt cardiopulmonary resuscitation’ (DNACPR) decision-making to understand whether or not they felt adequately prepared for this aspect of their role, and why. Qualitative data were generated from six CMs using a broad interpretive phenomenological approach. Face-to-face recorded interviews were analysed using template analysis. The study found that although participants faced complex ethical situations around ACP and DNACPR almost on a daily basis, none had received any formal training despite the emphasis on training in national and local guidelines. Participants often struggled to get their patients accepted on to the Gold Standards Framework. The research found variability and complexity of cases to be the main barriers to clear identification of the palliative phase

Volunteers In Energy Conservation -- Potential and Problems

The social and political implications of the energy crisis, while complex in nature and understanding, seem to urgently proclaim that the time for action is now. This paper is based on the premise that individual responsibility is essential. The people must act. Political decisions must be made. The people must debate what social climates are to be promoted and by what new energy systems. The key to solving the energy crisis is America\u27s people, and particularly with its youth. With people come the potential and of course, the problems. The approach of this paper will be threefold

Fuzzy adaptive resonance theory: Applications and extensions

Adaptive Resonance Theory, ART, is a powerful clustering tool for learning arbitrary patterns in a self-organizing manner. In this research, two papers are presented that examine the extensibility and applications of ART. The first paper examines a means to boost ART performance by assigning each cluster a vigilance value, instead of a single value for the whole ART module. A Particle Swarm Optimization technique is used to search for desirable vigilance values. In the second paper, it is shown how ART, and clustering in general, can be a useful tool in preprocessing time series data. Clustering quantization attempts to meaningfully group data for preprocessing purposes, and improves results over the absence of quantization with statistical significance. --Abstract, page iv

Petiole nutrient concentrations of upland cotton, Gossypium hirsutum L

Experiments were conducted at seven locations in 1969 and 1970 to determine the effects of growth stage, location differences, and cultivars on the Ca, Mg, K, and P concentrations of cotton petioles. In general, nutrient content of cotton petioles was affected more by growth stage and location than by cultivar difference. Calcium and K concentration usually decreased as the cotton plants approached maturity while Mg and P varied with location. Acala 1517D was generally higher in Ca and P concentrations than were any of the other nine cultivars tested. Coker 417 was high in Mg while the Stoneville cultivars were high in K. The high yielding Stoneville 213 was consistently low in Ca and Mg. Acala 1517D was the lowest yielding of all cultivars tested. When using plant analysis to diagnose nutrient levels in cotton, particular consideration should be given to the cultivars sampled. In this experiment more differences were found among cultivars at mid bloom than at any other physiological growth stage investigated

Editor\u27s Preface

introduction of Doug Smith as new editor of SR

Integrated Scenario-Based Methodology for Project Risk Management

Project risk management is currently used in several industries and mandated by government acquisition agencies around the world to manage uncertainty in an effort to improve a project's probability of success. Common practice involves developing a list of risk items scored with probability and consequence ordinal scales by committee usually focusing on cost and schedule issues. A scenario based process modeling construct is introduced using a hybrid Probabilistic Risk Assessment and Decision Analysis framework integrating project development risks with operational system risks. Project management's decisions are explicitly modeled and ranked based on risk importance to the project. Multiple consequence attributes are unified providing a basis for computing total project risk. This study shows that such an approach leads to an analysis system where scenarios tracing risk items to many possible consequences are explicitly understood; the interaction between cost, schedule, and performance models drive the analysis; probabilities for overruns, delays, increased system hazards are determined directly; and state-of-the-art quantification techniques are directly applicable. All these enhance project management's capability to respond with more effective decisions