Assessing pain in preterm infants in the neonatal intensive care unit:moving to a 'brain-oriented' approach

Preterm infants in the neonatal intensive care unit undergo repeated exposure to procedural and ongoing pain. Early and long-term changes in pain processing, stress-response systems and development may result from cumulative early pain exposure. So that appropriate treatment can be given, accurate assessment of pain is vital, but is also complex because these infants' responses may differ from those of full-term infants. A variety of uni- and multidimensional assessment tools are available; however, many have incomplete psychometric testing and may not incorporate developmentally important cues. Near-infrared spectroscopy and/or EEG techniques that measure neonatal pain responses at a cortical level offer new opportunities to validate neonatal pain assessment tools.

Moving to evidence-based practice in long-term care:the role of a Best Practise Resource Centre in two long-term care settings.

In this article, the authors provide an overview on the development of a Long-Term Care Best Practise Resource Centre. The results of both a feasibility study and the outcomes of a 1-year demonstration project are presented. The demonstration project involved a hospital as the information service provider and two demonstration sites, a home care service agency and a nursing home that used the services of the Centre. The goals of the Centre were threefold: provide access to literature for staff in long-term care (LTC) settings; improve the information management skills of health care providers; and support research and the integration of best practices in LTC organizations. The results of the pilot study contributed to the development of a collaborative information access system for LTC clinicians and managers that provides timely, up-to-date information contributing to improving the quality of care for adults receiving LTC. Based on this demonstration project, strategies for successful innovation in LTC are identified.

Trading Energy ETFs with an Improved Moving Average Strategy

In this paper we employ the recently introduced improved moving average methodology of Papailias and Thomakos (2011) and we apply it in two energy ETFs. We compare it to the standard moving average methodology and the buy and hold strategy. Investors who are interested in energy-related sectors and trade using averages, could benefit by forming their strategies based on this improved moving average methodology as it returns higher profits accompanied by decreased risk (measured in terms of drawdown).

An investigation into the acceleration response of a damaged beam-type structure to a moving force

In recent years there have been a growing number of publications on procedures for damage detection in beams from analysing their dynamic response to the passage of a moving force. Most of this research demonstrates their effectiveness by showing that a singularity that did not appear in the healthy structure is present in the response of the damaged structure. This paper elucidates from first principles how the acceleration response can be assumed to consist of ‘static’ and ‘dynamic’ components, and where the beam has experienced a localised loss in stiffness, an additional ‘damage’ component. The combination of these components establishes how the damage singularity will appear in the total response. For a given damage severity, the amplitude of the ‘damage’ component will depend on how close the damage location is to the sensor, and its frequency content will increase with higher velocities of the moving force. The latter has implications for damage detection because if the frequency content of the ‘damage’ component includes bridge and/or vehicle frequencies, it becomes more difficult to identify damage. The paper illustrates how a thorough understanding of the relationship between the ‘static‘ and ‘damage’ components contributes to establish if damage has occurred and to provide an estimation of its location and severity. The findings are corroborated using accelerations from a planar finite element simulation model where the effects of force velocity and bridge span are examined.

Moving Beyond the Administrative: Supervisors' Perspectives on Clinical Supervision in Child Welfare

This study contributes to the emerging knowledge base of child welfare supervision. An exploratory study examined the beliefs, practices, and experiences of 51 child welfare supervisors in Ontario, Canada. Eight focus groups were held with supervisors from a range of settings cross the province. The study identified a number of interwoven factors at the organizational, supervisory, and practice level that affect the nature of supervision offered. Implications are drawn for child welfare practice, models of supervision which integrate administrative, clinical and educational features, organizational culture, and training new supervisors.

Report on Urban Settlement Upgrading in Iraq: Kurani Ainkawa, Erbil: Moving Forward, Lessons Learned

In 2009 UN-HABITAT engaged in assisting the Kurdistan Regional Government (KRG) with the design and implementation of a ‘Improving the Housing Delivery System Project in Erbil’. This initiative built upon Iraq’s National Slum Upgrading Strategy (2005) and upon Phase II of UN-HABITAT’s 'Strengthening the Capacity of the Housing Sector in Iraq' project. Key to its initiative within the KRG has been a pilot project to upgrade an informal settlement in Erbil - Kurani Ainkawa. This report reflects on the pilot project’s achievements and lessons learned from pioneering a decentralized housing strategy.

Modal Extraction for Wind Turbines using Moving Window Subspace Identification

This paper proposes a method for wind turbine mode identification using the multivariable output error statespace (MOESP) identification algorithm. The paper incorporates a fast moving window QR decomposition and propagator method from array signal processing, yielding a moving window subspace identification algorithm. The algorithm assumes that the system order is known as a priori and remains constant during identification. For the purpose of extracting modal information for turbines modelled as a linear parameter varying (LPV) system, the algorithm is applicable since a nonlinear system can be approximated as a piecewise time invariant system in consecutive data windows. The algorithm is exemplified using numerical simulations which show that the moving window algorithm can track the modal information. The paper also demonstrates that the low computational burden of the algorithm, compared to conventional batch subspace identification, has significant implications for online implementation.

Fast Moving Window Algorithm for QR and Cholesky Decompositions

This paper proposes a fast moving window algorithm for QR and Cholesky decompositions by simultaneously applying data updating and downdating. The developed procedure is based on inner products and entails a similar downdating to that of the Chambers’ approach. For adding and deleting one row of data from the original matrix, a detailed analysis shows that the proposed algorithm outperforms existing ones in terms or computational efficiency, if the number of columns exceeds 7. For a large number of columns, the proposed algorithm is numerically superior compared to the traditional sequential technique.