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The research reported in this article focuses on a comparison of two different approaches to setting error bounds, or prediction intervals, on short-term forecasting of solar irradiation as well as solar and wind farm output. Short term in this instance relates to the time scales applicable in the Australian National Electricity Market (NEM), which operates on a five-minute basis throughout the year. The Australian Energy Market Operator (AEMO) has decided in recent years that, as well as point forecasts of energy, it is advantageous for planning purposes to have error bounds on those forecasts. We use quantile regression as one of the techniques to construct the bounds. This procedure is compared to a method of forecasting the conditional variance by use of either ARCH/GARCH or exponential smoothing, whichever is more appropriate for the specific application. The noise terms for these techniques must undergo a normalising transformation before their application. It seems that, for certain applications, quantile regression performs better, and the other technique for some other applications. [ABSTRACT FROM AUTHOR]

Aim: The island species–area relationship (ISAR) assumes that the area of islands is homogeneous, or scales with environmental heterogeneity across an archipelago, which is not always the case. We compare the performance of models that adjust or substitute for island area with measures of habitat diversity, island age and resource availability for two taxonomic groups. Location: Five hotspot archipelagos (Azores, Galapagos, Hawaii, Cape Verde, Canary Islands). Taxa: Vascular plants, birds. Methods: We used the mathematical framework of the power law to compare relevant models, treating the one containing only area as a null model against which others were compared. Data were collated from databases and the literature. Models were compared using linear regression within archipelagos and via mixed effect models with archipelago as a random effect. Results: Weighting of island area by habitat diversity and resource availability systematically improved statistical significance and model fits versus the area only power law. Models including island age did not show the same systematic improvement in model fits. For vascular plants, weighting islands by resource availability (energy and water) performed better than weighting by habitat diversity, although for birds these weightings performed equally well. Main Conclusions: Given that islands within archipelagos are fairly heterogeneous in climate, topography and geology, it is worth accounting for this in ISARs. Our results suggest that, for islands in volcanic hotspot archipelagos, this is best done by using direct measures of habitat diversity and resource availability rather than using island age as a proxy. We, therefore, recommend using direct measures, rather than proxies, when investigating the drivers of biodiversity patterns on islands. [ABSTRACT FROM AUTHOR]

• Comparison of day-ahead deterministic forecasts of solar irradiation and of production of a large-scale PV plant. • Use of Numerical Weather Predictions, post-processing methods and benchmark models. • Optimization of the operation of an energy storage system associated to a PV farm using the solar forecasts and a receding horizon approach. • Evaluation of the economic gain brought by the forecasts in order to increase the revenue offered by the energy arbitrage of the Australian electricity market. • Highlight of relationships between quality and economic value of solar forecasts. During the last decade, numerous solar forecasting tools have been developed to predict the energy generation of photovoltaic (PV) farms. The quality of solar forecasts is assessed by comparing predictions with measured solar data. However, this methodology does not consider the added value of the forecasts for their applications. As a consequence, what value could be given to the improvement of forecasts considering this evaluation framework? To answer this question, this work compares the value of different operational solar forecasts for a specific application. The aim is to look for relationships between the economic value and the error metrics defined to evaluate the forecast quality. A new generation of large-scale PV plants integrates ESS. The aim is to add flexibility to the injection of the production into the grid and thus to maximize the profit by taking advantage of the possibilities offered by the electricity market, such as energy arbitrage. To optimize the operation of these specific ESS, forecasting of the solar production is of paramount importance. The study case considered in this work is a large-scale PV farm of several megawatts associated with Li-ion batteries in the Australian energy market context. For this specific case study, the results show that the metrics used to evaluate the forecast quality based on the mean absolute error (MAE) have an almost linear relationship with the economic gain brought by applying the forecast. More precisely, an improvement of 1% point in MAE results approximately in an increase of 2% points in economical gain. [ABSTRACT FROM AUTHOR]

The deployment of photovoltaic (PV) systems has increased globally to meet renewable energy targets. Intermittent PV power generated due to cloud-induced variability introduces reliability and grid stability issues at higher penetration levels. Variability in power generation can induce voltage fluctuations within the distribution system and cause adverse effects on power quality. Therefore, it is essential to quantify resource variability to mitigate an intermittent power supply. In this study, we propose a new scheme to classify the sky conditions that are based on two common variability metrices: daily clear-sky index and normalized aggregate ramp rates. The daily clear-sky index estimates the cloudiness in the sky, and ramp rates account for the variability introduced in the system generation due to sudden cloud movements. This classification scheme can identify clear-sky, highly variable, low intermittent, high intermittent and overcast days. By performing a Chi-square test on the training and test sets, we obtain Chi-square statistic values greater than 3 with p-value > 0.05. This indicates that the distribution of the training and test clusters are similar, indicating the robustness of the proposed sky classification scheme. We have demonstrated the applicability of the scheme with diverse datasets to show that the proposed classification scheme can be homogenously applied to any dataset globally despite their temporal resolution. Using various case studies, we demonstrate the potential applications of the scheme for understanding resource allocation, site selection, estimating future intermittency due to climate change, and cloud enhancement effects. The proposed sky classification scheme enhances the precision and reliability of solar energy forecasts, optimizing system performance and maximizing energy production efficiency. This improved accuracy is crucial for variability control and planning, ensuring optimal output from PV plants. [ABSTRACT FROM AUTHOR]

Intermittent electrical power output from grid-connected solar farms causes intermittent and uncertain requirements for dispatchable power to balance power supply and demand. Accurate forecasting of electrical power output from solar farms can improve managing power generators connected to the grid. To forecast the electrical power output, a time series model is developed for two solar farms in Australia. The forecast model consists of a Fourier series that models seasonality and an autoregressive moving-average component that models the difference between the observed electrical power outputs and the Fourier series. Persistence detection is added to the model to improve forecast performance on clear days. Using minutely data, the model forecasts the electrical power output seven minutes ahead at every five-minute interval to comply with the requirements of the Australian Energy Market Operator (AEMO). Based on a 30-day testing period, the normalized mean absolute error (NMAE) skills of the time series model are 10.9% and 13.2% lower than those of the clear sky index persistence (CSIP) model. However, the normalized root mean squared error (NRMSE) skills of the time series model are approximately 3% and 12% higher than those of CSIP and the model currently used by AEMO, respectively. As the NRMSE skills are more indicative than the NMAE skills in reducing large forecast errors that would reduce electricity grid stability, the results suggest that AEMO can improve the management of the electricity grid with an inexpensive tool by adopting the developed model to forecast electrical power output of solar farms. [ABSTRACT FROM AUTHOR]

Grain boundary energies in different elements are correlated. The proportional scaling constants relating the energies of crystallography-equivalent boundaries in any two f.c.c. elements are nearly constant, with the notable exception of aluminum where these constants are known to vary significantly. However, the origins of the exceptional behavior of aluminum are not understood. Previously, we reported that for fcc metals there is a preference for tilt boundaries to shift their tilt axis across the (1 1 ¯ 0) plane towards [112] and to ultimately form low energy [112] core shifted boundaries (CSBs). By comparing grain boundary energies in copper and aluminum with different tilt axes in (1 1 ¯ 0) plane, we now report the existence of a well-defined scaling behavior for the case of low angle boundaries. In contrast, the scaling constant for high angle boundaries is essentially fixed regardless of their tilt axis shift. This results in a gradual change in the scaling constants from low angle to high angle boundaries, which is responsible for the apparent exceptional scaling behavior found in aluminum. An analysis of structure evolution during core shifting points to the significance of boundary-core dissociation, a form of correlated relaxation of individual atoms at boundaries, in controlling the scaling of boundary energies. [Display omitted] [ABSTRACT FROM AUTHOR]

Aim: The General Dynamic Model of island biogeography (GDM) explains patterns of species richness on volcanic hotspot archipelagos with respect to island age (T) and area (A), most commonly employing what we here call semi‐log ATT2 and LogATT2 models. These can be considered direct extensions of semi‐log and power law species‐area relationships (SARs), with a hump‐shaped function of T modelling drivers of biodiversity over and above area per se. We compare these and related models and investigate their conceptual and mathematical connections. Location: The Azores, Galapagos, Hawaii, Marquesas, Society Islands, Cape Verde Islands, Canary Islands and Aeolian archipelagos. Taxa: Vascular plants, birds, bryophytes, arthropods and molluscs. Methods: We gathered species richness data from databases and published sources, resulting in 34 datasets for various taxa. We used the Akaike information criterion corrected for small sample size (AICc) to compare the relative performance of models. We analysed the data at archipelago level and across archipelagos by using mixed effect models. We also calculated the relative time of expected peak diversity (Tpeak) from parameter estimates. Results: In almost three‐fourth of the cases the best model overall was one that contained only A or T rather than both predictors. There was greater variance between taxa than between archipelagos. Better dispersed taxa tended to reach peak diversity earlier. The most generally applicable of the models including T were the LogATT2 and LogTT2 models. These have important, previously unrecognized mathematical properties. Main Conclusions: SARs and species–time relationships should always be considered as potentially more parsimonious options. Considering the LogATT2 model as a modification of the power law S = cAz, where a lognormal function in T replaces the constant, c allows the construction of an extended framework for the GDM with incorporation of additional predictors such as measures of environmental heterogeneity and application beyond hotspot archipelagos. [ABSTRACT FROM AUTHOR]

Outdoor thermal comfort is influenced by people's climate expectations, perceptions and adaptation capacity. Varied individual response to comfortable or stressful thermal environments results in a deviation between actual outdoor thermal activity choices and those predicted by thermal comfort indices. This paper presents a passive activity observation (PAO) method for estimating contextual limits of outdoor thermal adaptation. The PAO method determines which thermal environment result in statistically meaningful changes may occur in outdoor activity patterns, and it estimates thresholds of outdoor thermal neutrality and limits of thermal adaptation in public space based on activity observation and microclimate field measurement. Applications of the PAO method have been demonstrated in Adelaide, Melbourne and Sydney, where outdoor activities were analysed against outdoor thermal comfort indices between 2013 and 2014. Adjusted apparent temperature (aAT), adaptive predicted mean vote (aPMV), outdoor standard effective temperature (OUT_SET), physiological equivalent temperature (PET) and universal thermal comfort index (UTCI) are calculated from the PAO data. Using the PAO method, the high threshold of outdoor thermal neutrality was observed between 24 °C for optional activities and 34 °C for necessary activities (UTCI scale). Meanwhile, the ultimate limit of thermal adaptation in uncontrolled public spaces is estimated to be between 28 °C for social activities and 48 °C for necessary activities. Normalised results indicate that city-wide high thresholds for outdoor thermal neutrality vary from 25 °C in Melbourne to 26 °C in Sydney and 30 °C in Adelaide. The PAO method is a relatively fast and localised method for measuring limits of outdoor thermal adaptation and effectively informs urban design and policy making in the context of climate change. [ABSTRACT FROM AUTHOR]

Highlights • The BEKK and DCC econometric models of VAR-mGARCH type are studied on wind speed data. • These are spatio-temporal models which allow for cross-volatility modeling. • The models are studied in their data generation and forecasting aspects. • Their volatility forecasting ability is used in an energy portfolio control problem. Abstract This paper evaluates the application of a family of VAR-mGARCH (Vector AutoRegressive with multivariate AutoRegressive Conditional Heteroskedasticity) volatility models to the problem of modeling (i.e. generating correct in-sample scenarios) and forecasting in a probabilistic way three univariate but mutually dependent wind speed hourly series. The evaluation starts from the consideration that optimal modeling and optimal forecasting are not necessarily attained by the same models, and that they are assessed in different ways. The proposed VAR-mGARCH family, originated in Finance, consists of the VAR-BEKK (VAR - Baba, Engle, Kraft and Kroner) model and the VAR-DCC (VAR - Dynamic Conditional Correlation) model, the latter seen as the simplified and more scalable version of the former. These models were never used in wind speed studies before. Both models will be used with Gaussian innovations, and the VAR-DCC model will be also used with Student's t innovations. These models, which are able to dynamically couple volatilities, are compared to two benchmark model sets, the first set consisting of three independent univariate AR-GARCH (i.e. non-vector) models, the second set consisting of an individual VAR model without the GARCH sector. These benchmark models cannot dynamically couple volatilities. Both benchmark model sets will be used with Gaussian innovations. The time series used for the evaluation are taken from three North-American wind metering sites located at few tens of kilometers from each other. In order to highlight the usefulness of choosing autoregressive coupled volatility schemes for modeling and forecasting spatially and temporally varying wind speed data, a controlled variance electricity generation portfolio example of Markowitz type, typical of Energy Finance, is also discussed at some length. In all, it is concluded that the VAR-DCC model with Student's t innovations is the most balanced choice for this data set when the three goals of modeling, forecasting and scalability in the number of considered sites are taken into account at once. [ABSTRACT FROM AUTHOR]

Separation models predict diffuse horizontal irradiance from other meteorological parameters such as the global horizontal irradiance or zenith angle. From a mathematical point of view, the separation modeling problem is a regression, where the regressors are observed or computed variables and the regressand is the unobserved diffuse fraction. The most successful minute-resolution separation model prior to 2016 was proposed by Engerer, which is constructed using a trend component (cloud enhancement) and a main effect (logistic function). Subsequently, the Starke model published in 2018 further improved the Engerer model. It is herein shown that the logistic-function type of model, and many other separation models, can be transformed into a (condition-based) multiple linear regression problem. Under this transformation framework, two new models are proposed, which strictly dominate the performance of the Engerer model and the Starke model, at all 7 test sites across the continental United States, making them probably the most accurate separation models to date. The new models are also tested at 5 European sites with unseen data (i.e., not involved during model parameter fitting); their performance again dominates all benchmarking models. The new separation models leverage half-hourly satellite-derived diffuse fraction. Since satellite data are available globally, the satellite-augmented separation models have universal applicability. However, despite their good performance, empirical separation models suffer from a series of issues. Hence, models driven by atmospheric physics are the "true gems" that one should pursue. [ABSTRACT FROM AUTHOR]

Presents a study which investigated the thermal decomposition of the Kodak thin-film resist (KTFR) used in the fabrication of integrated thermionic emission devices. Factor which affects the degree of residue formation in KTFR; Characteristics of the KTFR residue; Ramifications of the presence of a carbon residue at cathode operating temperatures.

Presents information on a study which demonstrated that in the absence of recombination, the decomposition from the carbonates to the corresponding oxides occurs in a single step. Preparation of the samples; Decomposition behavior reported; Observations on the structure of the x-ray amorphous decomposition product.

Due its intermittency, the large-scale integration of solar energy into electricity grids is an issue and more specifically in an insular context. Thus, forecasting the output of solar energy is a key feature to efficiently manage the supply-demand balance. In this paper, three short term forecasting procedures are applied to island locations in order to see how they perform in situations that are potentially more volatile than continental locations. Two continental locations, one coastal and one inland are chosen for comparison. At the two time scales studied, ten minute and hourly, the island locations prove to be more difficult to forecast, as shown by larger forecast errors. It is found that the three methods, one purely statistical combining Fourier series plus linear ARMA models, one combining clear sky index models plus neural net models, and a third using a clear sky index plus ARMA, give similar forecasting results. It is also suggested that there is great potential of merging modelling approaches on different horizons. [ABSTRACT FROM AUTHOR]

Dust aerosol particle size plays a crucial role in determining dust cycle in the atmosphere and the extent of its impact on the other atmospheric parameters. The in-situ measurements of dust particle size are very costly, spatially sparse and time-consuming. This paper presents an algorithm to retrieve effective dust diameter using infrared band brightness temperature from SEVIRI (the Spinning Enhanced Visible and InfaRed Imager) on the Meteosat satellite. An empirical model was constructed that directly relates differences in brightness temperatures of 8.7, 10.8 and 12.0 μm bands to effective dust diameter using the Mie extinction efficiency factor. Three case studies are used to test the model. The results showed consistency between the model and in-situ aircraft measurements. A severe dust storm over the Middle-East is presented to demonstrate the use of the model. This algorithm is expected to contribute to filling the gap created by the discrepancies between the current size distributions retrieval techniques and aircraft measurements. Potential applications include enhancing the accuracy of atmospheric modelling and forecasting horizontal visibility and solar energy system performance over regions affected by dust storms. [ABSTRACT FROM AUTHOR]

Background: Technological advancements in newer-generation catheterisation laboratories may reduce patient and occupational radiation exposure.Methods: We compared fluoroscopy time and dose-area product (DAP) between a Philips Allura X-PER FD20 and Siemens Artis Zeego Hybrid systems for 47 single-vessel percutaneous coronary interventions (PCI) and 35 transcatheter aortic valve implantations (21 Corevalve, 14 Edwards Sapien TAVI) using the FD20, versus 30 PCI and 28 TAVI (15 Corevalve, 13 Sapien) with the Zeego over a 24-month period.Results: Multivariate analysis revealed that, adjusting for patient weight and fluoroscopy time, DAP (median, interquartile range) was 26% lower for PCI with the Zeego than the FD20 [55.6 (27.0-91.5) vs 77.6 (51.2-129.1) Gy.cm(2), P=0.03)] and using tomographic imaging with the Zeego did not increase DAP for TAVI procedures [98.1 (65.9-136.6) vs 112.4 (64.9-156.2) Gy.cm(2) (P=NS). Although fluoroscopy times were longer for TAVI procedures than PCI with both systems (23.5-24.4 vs 7.3-9.2mins, p<0.0001), there was a significant difference in DAP between PCI and combined TAVI with the Zeego (55.6 vs 112.4Gy.cm(2), P<0.006) but not with the FD20 (77.6 vs 98.1Gy.cm(2), P=NS).Conclusion: Specific dose-reducing features of the new-generation system reduced DAP more for PCI than TAVI, as valve replacement procedures use additional cine-acquisition not necessary for PCI. [ABSTRACT FROM AUTHOR]

We apply the CARDS solar forecasting tool, developed at the University of South Australia, to forecasting of solar radiation series at three sites in Guadeloupe in the Caribbean. After performing the model estimates at each individual site, forecast errors were tested for cross correlation. It was found that on an hourly time scale, there was small but significant correlation between sites, and this was taken into account in refining the forecast. Cross correlation was found to be insignificant at the ten minute time scale so this effect was not included in the forecasting. Also, the final error series in each case was tested for an ARCH effect, finding that to construct prediction intervals for the forecast a conditional heteroscedastic model had to be constructed for the variance. Note that cross correlation between sites has to be included for this procedure as well as in the forecasting of the radiation. [ABSTRACT FROM AUTHOR]

As the frequency and intensity of heatwaves are growing in Australia, strategies to combat heat are becoming more vital. Cities are exposed to urban heat islands (UHIs) due to excess urbanisation. In this study, a definition of urban heatwave (UHW) is conceptualised to investigate the combined impacts of heatwaves and UHIs. To quantify the negative impacts of UHW, indicators--such as excess morbidity, electricity and water consumption--are considered. The intensity of UHWs is calculated using the unit of excess heat factor (EHF), developed by the Australian Bureau of Meteorology. EHF enables the comparability of UHWs in different geographical locations. Using the indicators and the intensity of UHWs, a calculation method to quantify heatwave resilience at a precincts scale is proposed. The study summarises the assumed influential factors of precinct heatwave resilience based on the existing literature and propose a "cool retrofitting toolkit" (CRT). CRT creates the framework to assess the adaptation to and mitigation of UHWs available to retrofit existing precincts, and to evaluate potential retrofitting strategies in terms of energy and carbon efficiency, financial affordability and perceived acceptability by population. This study illuminates the importance of climate, function, built environment and population characteristics-conscious retrofitting. [ABSTRACT FROM AUTHOR]

Background With the increased application of structural heart intervention techniques, there is concern over increasing radiation dose, especially during lengthy procedures. Methods We compared data from 91 consecutive single-vessel percutaneous coronary interventions, 69 patent foramen ovale closures, 25 atrial septal defect closures, 49 percutaneous transluminal mitral valvuloplasties, 57 balloon aortic valvuloplasties, 53 trans-catheter aortic valve implantations (TAVI), 21 left atrial appendage occlusions and 7 MitraClip ® procedures. Results The following fluoroscopy times and dose-area product (median, interquartile range) were recorded: patent foramen ovale closure (7.8, 5.3-10.9 minutes; 16.9, 7.5-30.6 Gycm 2 ), atrial septal defect closure (10.1, 7.3-13 minutes; 15.5, 11.6-30.5 Gycm 2 ), percutaneous transluminal mitral valvuloplasty (14.3, 11.4-24.2 minutes; 37.4, 19.8-87.0 Gycm 2 ), balloon aortic valvuloplasty (8.4, 5.2-13.2 minutes; 19.8, 10.2-30.0 Gycm 2 ), Edwards Sapien™ TAVI (24.0, 19.3-34.4 minutes; 86.4, 64.0-111.4 Gycm 2 ), Medtronic CoreValve ® TAVI (19.4, 15.0-26.0 minutes; 101.9, 52.6-143.2 Gycm 2 ), left atrial appendage occlusion (18.5, 15.7-29.1 minutes; 84.1, 36.4-140.0 Gycm 2 ), Mitraclip ® procedures (37.2, 14.2-59.9 minutes; 89.1, 26.2-118.7 Gycm 2 ), coronary angiography and single vessel percutaneous coronary intervention (6.6, 5.1-11.0 minutes; 62.5, 37.0-95.8 Gycm 2 ). Conclusion For structural heart interventions, dose-area product was not significantly greater than for coronary angiography with single-vessel percutaneous coronary artery intervention. This should be reassuring to patients and staff attending prolonged structural heart interventions. [ABSTRACT FROM AUTHOR]

People's views of landscape can have significant impact on their land use choices. This in turn can have climate implications. In the literature, there is significant attention paid to the effect of climate on landscape, but as well, there are more examples than one might expect of the effects of landscape change on climate. I present evidence of this from Western Australia and Africa, and some conjectured negative and positive effects in two locations in South Australia. I argue that the land use change affecting the landscape and thus affecting the climate emanates from one's view of landscape. There are also some personal reflections of perceptions of landscape from someone who started life in a climate and landscape far removed from the South Australian environment within which he has chosen to live. [ABSTRACT FROM AUTHOR]

Calculating the age of trees is often desirable in vegetation studies, but is sometimes difficult. In arid areas in particular, tree rings may not be annual, and growth may be related more to rainfall than annual cycles. A relationship between age and trunk circumference was developed for two species, Acacia aneura and Myoporum platycarpum, based on measurements of trees of known age (<80 years) growing on permanent quadrats on the Koonamore Reserve, in semi-arid South Australia. Extrapolation beyond the known ages was made by finding the maximum girth of mature trees in a larger population and using this to estimate an asymptote to which the curve is constrained to approach. We envisage that the techniques developed here could be applied to other species of a similar nature, those for which there is no relationship between number of tree rings and age. [ABSTRACT FROM AUTHOR]

Abstract: To assess the viability of proposed solar installations, knowledge of global solar radiation is not sufficient. For stationary photovoltaic plant, we require global radiation series, but also the contemporaneous diffuse radiation series. Alternatively, for concentrated solar thermal, we need global and direct normal solar radiation. In this paper, we investigate whether one can simply use a model for predicting diffuse radiation using multiple predictions derived by our research team, the Boland–Ridley–Lauret (BRL) model, to give delineations of both diffuse and direct or if we need to use another model for direct or develop a new direct normal statistical model. [Copyright &y& Elsevier]

We demonstrate how the local density of electronic states evolves as the size and dimensionality of surface dangling bond nanowires are modified. These wires were fabricated using the probe of a scanning tunneling microscope on a hydrogen passivated n-type Si(100)-(2 × 1) surface. We demonstrate that by varying the number and arrangement of dangling bonds on the surface it is possible to arbitrarily engineer the electronic characteristic of a surface nanowire from that of a semiconductor with a controllable band gap to that of a metal. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes to use a rather new statistical approach in the realm of solar radiation modelling namely Bayesian inference. In this work, the theory of Bayesian inference will be presented at length. The Bayesian analysis consists in two levels. The first one is related to the parameter estimation while the second one concerns the model selection problem. As an illustration, a Bayesian parameter estimation method is used to derive a logistic hourly solar diffuse fraction model. A major difference between Bayesian and frequentist (or classical) methods is that the Bayesian inference offers a framework (through the use of prior information) to continuously update our posterior beliefs. In other words, all previous work is not wasted as the preceding model’s parameters can be used as prior information for the derivation of the parameters estimates of the next (new) model. For this particular application, it is also shown that the use of Bayesian methods instead of classical statistical techniques lead to a less biased model. [Copyright &y& Elsevier]

Equity in resource allocation is central to the tenet of social justice in health care. The management of surgical waiting lists is of critical importance to clinicians, patients and regulators. In most hospital environments, the basic process has remained unchanged for decades. Patients are assigned to one of three urgency-related categories. Clinicians consequently administer three competing patient pools. The basis by which patients are selected for treatment may be difficult to define. The specific clinical circumstances of each patient are often unreported and may be unknown to those administering the list. Waiting list bias is also recognised. This may reflect clinician advocacy, pressure to meet category timeframe restrictions or perceived training requirements. In this environment, it is difficult to demonstrate propriety in care. We report the implementation of a pilot program to redesign waiting list management within a South Australian public hospital unit. This allows assemblage of patients into a single list. Overall priority is determined by balancing clinical acuity and waiting time. The determination of acuity takes into account both the primary category and the specific characteristics of each patient that are relevant to their intended procedure. Uniquely, the process is applicable to lists containing patients with dissimilar conditions. This paper reviews the limitations of current approaches in meeting reasonable community expectations. The principles and social justification underpinning this reform are introduced. Finally, the benefits offered by the program are discussed and interim results are reported. What is known about this topic? Current models for the management of hospital waiting lists have remained largely unchanged for several decades. Typically patients are allocated to urgent, semi-urgent and non-urgent categories of care. No methodology exists to systematically integrate these groups, or to account for specific patient factors. In this void, propriety in management is difficult to establish or defend. What does this paper add? A program is reported that unifies all categories of patients into a single prioritised waiting list. The order of patients is dynamic, and transparently reflects waiting time, category assignment and relevant individual patient factors. Uniquely, the program is applicable to lists containing patients with diverse clinical conditions. What are the implications for clinicians? Adoption of new technology is essential if reasonable community expectations in waiting list management are to be met. The current program provides unambiguous, defensible prioritisation of all patients awaiting care. The present reliance on individual managers is reduced, and the unique circumstances of each patient are recognised. We believe this approach affords significant benefit to patients, practitioners and regulators. [ABSTRACT FROM AUTHOR]

Abstract: For some locations both global and diffuse solar radiation are measured. However, for many locations, only global radiation is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from direct on some other plane using trigonometry, we need to have diffuse radiation on the horizontal plane available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia . Boland et al. developed a validated model for Australian conditions. Boland et al. detailed our recent advances in developing the theoretical framework for the use of the logistic function instead of piecewise linear or simple nonlinear functions and was the first step in identifying the means for developing a generic model for estimating diffuse from global and other predictors. We have developed a multiple predictor model, which is much simpler than previous models, and uses hourly clearness index, daily clearness index, solar altitude, apparent solar time and a measure of persistence of global radiation level as predictors. This model performs marginally better than currently used models for locations in the Northern Hemisphere and substantially better for Southern Hemisphere locations. We suggest it can be used as a universal model. [Copyright &y& Elsevier]

Accurately forecasting the output of grid connected wind and solar systems is critical to increasing the overall penetration of renewables on the electrical network. This is especially the case in Australia, where there has been a massive increase in solar and wind farms in the last 15 years, as well as in roof top solar, both domestic and commercial. For example, in 2020, 27% of the electricity in Australia was from renewable sources, and in South Australia almost 60% was from wind and solar. In the literature, there has been extensive research reported on solar and wind resource, entailing both point and interval forecasts, but there has been much less focus on the forecasting of output from wind and solar systems. In this review, we canvass both what has been reported and also what gaps remain. In the case of the latter topic, there are numerous aspects that are not well dealt with in the literature. We have added discussion on the value of forecasts, rather than just focusing on forecast skill. Further, we present a section on how to deal with conditionally changing variance, a topic that has little focus in the literature. One other topic may be particularly important in Australia at the moment, but may become more widespread. This is how to deal with the concept of a clear sky output from a solar farm when the field is oversized compared to the inverter capacity, resulting in a plateau for the output. [ABSTRACT FROM AUTHOR]

Abstract: For some locations both global and diffuse solar radiation are measured. However, for many locations, only global is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from trigonometry, we need to have diffuse on the horizontal available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse radiation on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia [Spencer JW. A comparison of methods for estimating hourly diffuse solar radiation from global solar radiation. Sol Energy 1982; 29(1): 19–32]. Boland et al. [Modelling the diffuse fraction of global solar radiation on a horizontal surface. Environmetrics 2001; 12: 103–16] developed a validated model for Australian conditions. We detail our recent advances in developing the theoretical framework for the approach reported therein, particularly the use of the logistic function instead of piecewise linear or simple nonlinear functions. Additionally, we have also constructed a method, using quadratic programming, for identifying values that are likely to be erroneous. This allows us to eliminate outliers in diffuse radiation values, the data most prone to errors in measurement. [Copyright &y& Elsevier]

Objective. Considerable controversy persists regarding the use of human antibiotics to promote growth in animals raised for food. The authors examined the economic effect of removing antibiotics used for growth promotion in commercial broiler chickens. Methods. The authors utilized data published by the Perdue company, the fourth largest poultry producer in the United States, in which a non-randomized controlled trial of growth-promoting antibiotic (GPA) use was conducted with seven million broiler chickens to evaluate the impact of removing GPAs on production. Results. Positive production changes were associated with GPA use, but were insufficient to offset the cost of the antibiotics. The net effect of using GPAs was a lost value of $0.0093 per chicken (about 0.45% of total cost). Based upon these data, the authors found no basis for the claim that the use of GPAs lowers the cost of production. Note that this study does not include veterinary cost changes or changes in performance variability associated with the removal of GPAs. Conclusions. This economic analysis is the first study to the authors' knowledge utilizing large-scale empirical data collected by U.S. industry, in which it is demonstrated that the use of GPAs in poultry production is associated with economic losses to the producers. These data are of considerable importance in the ongoing national debate concerning the continued use of antibiotics for growth promotion of food animals. Based on the industry study and the resulting economic impact, the use of GPAs in U.S. poultry production should be reconsidered. [ABSTRACT FROM AUTHOR]

Abstract: We report the assembly properties of high density and high aspect ratio metal nanowire arrays (Au, Cu and Ag with diameters ranging from 40 to 250 nm) after release from the anodic alumina oxide (AAO) templates. Individual Ag and Cu nanowires were observed following release from the template, however, in the case of gold nanowires, the dispersion was dependent on size and aspect ratio. 40–100 nm gold wires aggregated to form bundles or disordered mats. We show that a simple cyanide-mediated release from the AAO template, results in isolated dispersion of wires even for the smallest wire diameters. Possible stabilising mechanisms for observed tendency of nanowires dispersion are discussed. [Copyright &y& Elsevier]

Abstract: The valuation of seagrass habitats, and indeed many natural resources, has been the focus of many researchers with differing approaches. This study presents an estimate of the value of seagrass habitats in terms of the contribution to secondary production of some important South Australian fish species in a broad scale domain. The approach we take considers the relationship between primary production estimates for seagrass habitats in temperate and subtropical coastal waters and estimates of commercial, recreational and discarded catch figures. The paper briefly describes models which link expected harvest of different species to seagrass area and the consequent expected reduction in catch given seagrass decline. We estimate that the economic contribution of seagrass habitats to secondary production in the gulf waters of South Australia is of the order of $ A114 million per year. Furthermore, we estimate in a particular example that the economic cost of a 16% decline of seagrass in one small area was $ 235,000 per year in lost production. [Copyright &y& Elsevier]

Abstract: We report the co-existence and growth of two different types of GdSi2 nanowires (NWs) following Gd deposition on the Si(100) surface. The first NW type is hexagonal and similar in appearance and orientation to that previously reported in the literature. The structure of the second NW type is unknown, but its orientation, thermodynamic stability and surface appearance are consistent with an orthorhombic structure. Real-time high-temperature STM studies show that these new NWs are thermodynamically preferred and in regions where both wires co-exist, they grow at the expense of their hexagonal counterparts. The implications of these observations for nanoscale interconnects is discussed. [Copyright &y& Elsevier]

The reaction of 1,3-cyclohexadiene (1,3-CHD) with Si dimers on the Si(100)-2×1 surface was studied via scanning tunnelling microscopy (STM) and density functional theory (DFT). Both intra- and interdimer [2+2] and [4+2] products are observed on the surface under empty-state bias conditions. Comparison of the observed products and their respective distribution on the surface with preliminary DFT calculations suggest a kinetically controlled reaction mechanism. [Copyright &y& Elsevier]

Focuses on a study that showed that on an hour-to-hour basis the stochastic components of climate variables may be disregarded in building thermal, solar process heat and photovoltaic system performance without significantly affecting the result. Deterministic and stochastic components of the climatic variables; Construction of the weather data sets; Results.

A chemically induced dimer configuration was prepared on the silicon (Si) (100) surface and was characterized by scanning tunneling microscopy (STM) and spectroscopy (STS). These prepared dimers, which are essentially untilted and differ both electronically and structurally from the dynamically tilting dimers normally found on this surface, are more reactive than normal dimers. For molecular hydrogen (H[sub 2]) adsorption, the enhancement is about 10[sup 9] at room temperature. There is no appreciable barrier for the H[sub 2] reaction at prepared sites, indicating the prepared configuration closely approximates the actual dimer structure in the transition state. This previously unknown ability to prepare specific surface configurations has important implications for understanding and controlling reaction dynamics on semiconductor surfaces. [ABSTRACT FROM AUTHOR]

Solar energy is an economic and clean power source subject to natural variability, while energy storage might attenuate it, ultimately, effective and operationally feasible forecasting techniques for energy management are needed for better grid integration. This work presents a novel deterministic forecast method considering: irradiance pattern classification, Markov chains, fuzzy logic and an operational approach. The method developed was applied in a rolling manner for six years to a target location with no prior data to assess performance and its changes as new local data becomes available. Clearness index, diffuse fraction and irradiance hourly forecasts are analyzed on a yearly basis but also for 20 day types, and compared against smart persistence. Results show the proposed method outperforms smart persistence by ~10% for clearness index and diffuse fraction on the base case, but there are significant differences across the 20 day types analyzed, reaching up to +60% for clear days. Forecast lead time has the greatest impact in forecasting performance, which is important for any practical implementation. Seasonality in data gaps or rejected data can have a definite effect in performance assessment. A novel, comprehensive and detailed analysis framework was shown to present a better assessment of forecasters' performance. [ABSTRACT FROM AUTHOR]

Accurately forecasting the output of grid connected wind and solar systems is critical to increasing the overall penetration of renewables on the electrical network. This includes not only forecasting the expected level, but also putting error bounds on the forecast. The National Electricity Market (NEM) in Australia operates on a five minute basis. We used statistical forecasting tools to generate forecasts with prediction intervals, trialing them on one wind and one solar farm. In classical time series forecasting, construction of prediction intervals is rudimentary if the error variance is constant—Termed homoscedastic. However, if the variance changes—Either conditionally as with wind farms, or systematically because of diurnal effects as with solar farms—The task is much more complicated. The tools were trained on segments of historical data and then tested on data not used in the training. Results from the testing set showed good performance using metrics, including Coverage and Interval Score. The methods used can be adapted to various time scales for short term forecasting. [ABSTRACT FROM AUTHOR]

We prove an extended Granger–Johansen representation theorem (GJRT) for finite‐ or infinite‐order integrated autoregressive time series on Banach space. We assume only that the resolvent of the autoregressive polynomial for the series is analytic on and inside the unit circle except for an isolated singularity at unity. If the singularity is a pole of finite order the time series is integrated of the same order. If the singularity is an essential singularity the time series is integrated of order infinity. When there is no deterministic forcing the value of the series at each time is the sum of an almost surely convergent stochastic trend, a deterministic term depending on the initial conditions and a finite sum of embedded white noise terms in the prior observations. This is the extended GJRT. In each case the original series is the sum of two separate autoregressive time series on complementary subspaces – a singular component which is integrated of the same order as the original series and a regular component which is not integrated. The extended GJRT applies to all integrated autoregressive processes irrespective of the spatial dimension, the number of stochastic trends and cointegrating relations in the system and the order of integration. [ABSTRACT FROM AUTHOR]

The purpose of this review was to provide an account of the interaction of hydrogen with silicon surface in light of recent STM studies. The results of numerous earlier studies and more recent STM studies have been compared and in the event of conflicting data an attempt was made to explain the origin of the discrepancy. [ABSTRACT FROM AUTHOR]

Describes the use of the scanning tunneling microscope (STM) in the observation of chlorine atoms on the Si(100)-(2x1) surface. Interactions of the STM probe tip with surface adsorbates; Facilitation of chlorine atom migration by the presence of a chlorine bridge-bonded minimum; Dangling bond sites.

Presents an examination of the chemical etching process. Details on the early methods of chemical etching; Description of the development of the etching process; Use of chemical etching in the United States microelectronics industry; Schematic views of the etching process; Details on the etching of a silicon surface. INSET: Silicon's (100) and (111) surfaces.

The article offers information on the emulation of touch by electronic means. It states that high spatial-resolution and pressure-sensitive artifical skins need to be developed for touch emulation. It also mentions several benefits of using artificial skin including development of precision tools with advanced skills, and amalgamation of touch capacity into flexible and scrollable display technologies.

Here we report on a technique for anisotropic etching of silicon similar to the well established vapor-liquid-solid technique for the growth of semiconductor nanowires. By annealing a patterned gold line on a H terminated silicon surface, Si atoms diffuse into the Au to form a eutectic phase. Upon exposure to etchant gases the dissolved silicon reacts and desorbs from the eutectic phase causing additional silicon to diffuse from the substrate to re-establish the equilibrium eutectic composition. In this manner the patterned eutectic material becomes anisotropically etched into the silicon substrate, in a process we call solid liquid vapor etching. [ABSTRACT FROM AUTHOR]

The article discusses controversies faced by public services, urban water supply and wastewater utilities in the U.S. It discusses the state of the industry in the country. It stresses the role played by the private sector in the water industry. It cites the issues involved in the proposals for public/private partnership.

With the recent rapid increase in the use of roof top photovoltaic solar systems worldwide, and also, more recently, the dramatic escalation in building grid connected solar farms, especially in Australia, the need for more accurate methods of very short-term forecasting has become a focus of research. The International Energy Agency Tasks 46 and 16 have brought together groups of experts to further this research. In Australia, the Australian Renewable Energy Agency is funding consortia to improve the five minute forecasting of solar farm output, as this is the time scale of the electricity market. The first step in forecasting of either solar radiation or output from solar farms requires the representation of the inherent seasonality. One can characterise the seasonality in climate variables by using either a multiplicative or additive modelling approach. The multiplicative approach with respect to solar radiation can be done by calculating the clearness index, or alternatively estimating the clear sky index. The clearness index is defined as the division of the global solar radiation by the extraterrestrial radiation, a quantity determined only via astronomical formulae. To form the clear sky index one divides the global radiation by a clear sky model. For additive de-seasoning, one subtracts some form of a mean function from the solar radiation. That function could be simply the long term average at the time steps involved, or more formally the addition of terms involving a basis of the function space. An appropriate way to perform this operation is by using a Fourier series set of basis functions. This article will show that for various reasons the additive approach is superior. Also, the differences between the representation for solar energy versus solar farm output will be demonstrated. Finally, there is a short description of the subsequent steps in short-term forecasting. [ABSTRACT FROM AUTHOR]

The article presents a study which revealed the impact of the surface effects in thin silicon films on the transport of charge carriers and on device performance. The result was considered as a new opportunity for device physics. Researchers added that the position of the Fermi energy is still controlled during silicon doping. Thus, a need to develop a high-resolution technique for the implantation of dopant ions on semiconductor materials is needed.

The levitation of a permanent magnet over a type-II superconductor may be modified and controlled by the addition of a variable magnetic field to the magnet-superconductor system. Using this scheme, levitation of a magnet of significantly larger mass was established by the direct interaction of the additonal field with the levitating magnet. [ABSTRACT FROM AUTHOR]

Observations are presented on levitation and suspension of a permanent magnet by combination of a variable magnetic field and a type II superconductor (YBa2Cu3Ox). It has been found that a continuous range of distances exists where stable levitation and suspension may be obtained, and that the orientation of magnetic moment of the levitated or suspended magnet is also adjustable over a range of angles. In addition, the incorporation of the magnetic element makes it possible to suspend much higher mass than observed previously. [ABSTRACT FROM AUTHOR]