Implementation and evaluation of a new model of nursing practice in radiation oncology

Patients undergoing radiation therapy for cancer face a series of challenges that require support from a multidisciplinary team which includes radiation oncology nurses. However, the specific contribution of nursing, and the models of care that best support the delivery of nursing interventions in the radiotherapy setting, is not well described. In this case study, the Interaction Model of Client Health Behaviour and the associated principles of person-centred care were incorporated into a new model of care that was implemented in one radiation oncology setting in Brisbane, Australia. The new model of care was operationalised through a Primary Nursing/Collaborative Practice framework. To evaluate the impact of the new model for patients and health professionals, multiple sources of data were collected from patients and clinical staff prior to, during, and 18 months following introduction of the practice redesign. One cohort of patients and clinical staff completed surveys incorporating measures of key outcomes immediately prior to implementation of the model, while a second cohort of patients and clinical staff completed these same surveys 18 months following introduction of the model. In-depth interviews were also conducted with nursing, medical and allied health staff throughout the implementation phase to obtain a more comprehensive account of the processes and outcomes associated with implementing such a model. From the patients’ perspectives, this study demonstrated that, although adverse effects of radiotherapy continue to affect patient well-being, patients continue to be satisfied with nursing care in this specialty, and that they generally reported high levels of functioning despite undergoing a curative course of radiotherapy. From the health professionals’ perspective, there was evidence of attitudinal change by nursing staff within the radiotherapy department which reflected a greater understanding and appreciation of a more person-centred approach to care. Importantly, this case study has also confirmed that a range of factors need to be considered when redesigning nursing practice in the radiotherapy setting, as the challenges associated with changing traditional practices, ensuring multidisciplinary approaches to care, and resourcing a new model were experienced. The findings from this study suggest that the move from a relatively functional approach to a person-centred approach in the radiotherapy setting has contributed to some improvements in the provision of individualised and coordinated patient care. However, this study has also highlighted that primary nursing may be limited in its approach as a framework for patient care unless it is supported by a whole team approach, an appropriate supportive governance model, and sufficient resourcing. Introducing such a model thus requires effective education, preparation and ongoing support for the whole team. The challenges of providing care in the context of complex interdisciplinary relationships have been highlighted by this study. Aspects of this study may assist in planning further nursing interventions for patients undergoing radiotherapy for cancer, and continue to enhance the contribution of the radiation oncology nurse to improved patient outcomes.

Didiman: Australian agricultural extension officers in the territory of Papua and New Guinea, 1945-1975

Historically, the development philosophy for the two Territories of Papua and New Guinea (known as TPNG, formerly two territories, Papua and New Guinea) was equated with economic development, with a focus on agricultural development. To achieve the modification or complete change in indigenous farming systems the Australian Government’s Department of External Territories adopted and utilised a programme based on agricultural extension. Prior to World War II, under Australian administration, the economic development of these two territories, as in many colonies of the time, was based on the institution of the plantation. Little was initiated in agriculture development for indigenous people. This changed after World War II to a rationale based on the promotion and advancement of primary industry, but also came to include indigenous farmers. To develop agriculture within a colony it was thought that a modification to, or in some cases the complete transformation of, existing farming systems was necessary to improve the material welfare of the population. It was also seen to be a guarantee for the future national interest of the sovereign state after independence was granted. The Didiman and Didimisis became the frontline, field operatives of this theoretical model of development. This thesis examines the Didiman’s field operations, the structural organisation of agricultural administration and the application of policy in the two territories.

A new family of Marx generator based on resonant converter

This paper presents a novel topology to generate high voltage with utilization of slow and fast power switches. New concepts used in this topology include numbers of diode-capacitor units in parallel with resonant circuits which are connected to a positive buck-boost converter. The resonant circuit reverses the voltage polarity of the capacitors. This configuration has capability of generating a flexible high voltage with certain number of capacitors. The advantage of this topology is to use slow switches, less number of diodes and capacitors compare to Marx generator. Simulations have been performed to verify the proposed topology.

Key competitiveness indicators for new real estate developers

Purpose – The paper aims to explore the key competitiveness indicators (KCIs) that provide the guidelines for helping new real estate developers (REDs) achieve competitiveness during their inception stage in which the organisations start their business. Design/methodology/approach – The research was conducted using a combination of various methods. A literature review was undertaken to provide a proper theoretical understanding of organisational competitiveness within RED's activities and developed a framework of competitiveness indicators (CIs) for REDs. The Delphi forecasting method is employed to investigate a group of 20 experts' perception on the relative importance between CIs. Findings – The results show that the KCIs of new REDs are capital operation capability, entrepreneurship, land reserve capability, high sales revenue from the first real estate development project, and innovation capability. Originality/value – The five KCIs of new REDs are new. In practical terms, the examination of these KCIs would help the business managers of new REDs to effectively plan their business by focusing their efforts on these key indicators. The KCIs can also help REDs provide theoretical constructs of the knowledge base on organisational competitiveness from a dynamic perspective, and assist in providing valuable experiences and in formulating feasible strategies for survival and growth.

A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

A new generation of high voltage pulsed power converters

Improving efficiency and flexibility in pulsed power supply technologies are the most substantial concerns of pulsed power systems specifically for plasma generation. Recently, the improvement of pulsed power supply becomes of greater concern due to extension of pulsed power applications to environmental and industrial areas. A current source based topology is proposed in this paper which gives the possibility of power flow control. The main contribution in this configuration is utilization of low-medium voltage semiconductor switches for high voltage generation. A number of switch-diode-capacitor units are designated at the output of topology to exchange the current source energy into voltage form and generate a pulsed power with sufficient voltage magnitude and stress. Simulations have been carried out in Matlab/SIMULINK platform to verify the capability of this topology in performing desired duties. Being efficient and flexible are the main advantages of this topology.

A new pulsed power supply topology based on positive buck-boost converters concept

Improving efficiency and flexibility in pulsed power supply technologies is the most substantial concern of pulsed power systems specifically with regard to plasma generation. Recently, the improvement of pulsed power supply has become of greater concern due to the extension of pulsed power applications to environmental and industrial areas. With this respect, a current source based topology is proposed in this paper as a pulsed power supply which gives the possibility of power flow control during load supplying mode. The main contribution in this configuration is utilization of low-medium voltage semiconductor switches for high voltage generation. A number of switch-diode-capacitor units are designated at the output of topology to exchange the current source energy into voltage form and generate a pulsed power with sufficient voltage magnitude and stress. Simulations carried out in Matlab/SIMULINK platform as well as experimental tests on a prototype setup have verified the capability of this topology in performing desired duties. Being efficient and flexible are the main advantages of this topology.

Coal Seam Gas Water from Maramarua, New Zealand: Characterisation and Comparison to United States Analogues

Groundwater from Maramarua has been identified as coal seam gas (CSG) water by studying its composition, and comparing it against the geochemical signature from other CSG basins. CSG is natural gas that has been produced through thermogenic and biogenic processes in underground coal seams; CSG extraction requires the abstraction of significant amounts of CSG water. To date, no international literature has described coal seam gas water in New Zealand, however recent CSG exploration work has resulted in CSG water quality data from a coal seam in Maramarua, New Zealand. Water quality from this site closely follows the geochemical signature associated with United States CSG waters, and this has helped to characterise the type of water being abstracted. CSG water from this part of Maramarua has low calcium, magnesium, and sulphate concentrations but high sodium (334 mg/l), chloride (146 mg/l) and bicarbonate (435 mg/l) concentrations. In addition, this water has high pH (7.8) and alkalinity (360 mg/l as CaCO3), which is a direct consequence of carbonate dissolution and biogenic processes. Different analyte ratios ('source-rock deduction' method) have helped to identify the different formation processes responsible in shaping Maramarua CSG water

Australia and New Zealand CBNG development and environmental implications

Following the success of Coalbed Natural Gas (CBNG) operations in the United States, companies in Australia and New Zealand have been actively exploring and developing this technology for the last two decades. In particular, the Bowen and Surat basins in Queensland, Australia, have undergone extensive CBNG development. Unfortunately, awareness of potential environmental problems associated with CBNG abstraction has not been widespread and legislation has at times struggled to keep up with rapid development. In Australia, the combined CBNG resource for both the Bowen and Surat basins has been estimated at approximately 10,500 PJ with gas content as high as 10 m3/tonne of coal. There are no official estimates for the magnitude of the CBNG resource in New Zealand but initial estimates suggest this could be up to 1,300 PJ with gas content ranging from 1 to 5 m3/tonne of coal. In Queensland, depressurization of the Walloon Coal Measures to recover CBNG has the potential to induce drawdown in adjacent deep aquifer systems through intraformational groundwater flow. In addition, CBNG operators have been disposing their co-produced water by using large unlined ponds, which is not the best practice for managing co-produced water. CBNG waters in Queensland have the typical geochemical signature associated with CBNG waters (Van Voast, 2003) and thus have the potential to impair soils and plant growth where land disposal is considered. Water quality from exploration wells in New Zealand exhibit the same characteristics although full scale production has not yet begun. In general, the environmental impacts that could arise from CBNG water extraction depend on the aquifer system, the quantity and quality of produced water, and on the method of treatment and disposal being used. Understanding these impacts is necessary to adequately manage CBNG waters so that environmental effects are minimized; if properly managed, CBNG waters can be used for beneficial applications and can become a valuable resource to stakeholders.

Characterisation of Coal Seam Gas Waters in New Zealand

Coal seam gas (CSG) exploration and development requires the abstraction of significant amounts of water. This is so because gas desorbtion in coal seams takes place only after aquifer pressure has been reduced by prolonged pumping of aquifer water. CSG waters have a specific geochemical signature which is a product of their formation process. These waters have high bicarbonate, high sodium, low calcium, low magnesium, and very low sulphate concentrations. Additionally, chloride concentrations may be high depending on the coal depositional environment. This particular signature is not only useful for exploration purposes, but it also highlights potential environmental issues that can arise as a consequence of CSG water disposal. Since 2002 L&M Coal Seam Gas Ltd and CRL Energy Ltd, have been involved in exploration and development of CSG in New Zealand. Anticipating disposal of CSG waters as a key issue in CSG development, they have been assessing CSG water quality along with exploration work. Coal seam gas water samples from an exploration well in Maramarua closely follow the geochemical signature associated with CSG waters. This has helped to identify CSG potential, while at the same time assessing the chemical characteristics and water generation processes in the aquifer. Neutral pH and high alkalinity suggest that these waters could be easily managed once the sodium and chloride concentrations are reduced to acceptable levels.

New criteria for evaluating methods of identifying hot spots

Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

Statistical and Econometric Methods for Transportation Data Analysis, 2nd edition

Now in its second edition, this book describes tools that are commonly used in transportation data analysis. The first part of the text provides statistical fundamentals while the second part presents continuous dependent variable models. With a focus on count and discrete dependent variable models, the third part features new chapters on mixed logit models, logistic regression, and ordered probability models. The last section provides additional coverage of Bayesian statistical modeling, including Bayesian inference and Markov chain Monte Carlo methods. Data sets are available online to use with the modeling techniques discussed.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.