Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

Detection of recently discovered human polyomaviruses in a longitudinal kidney transplant cohort

A large number of human polyomaviruses have been discovered in the last 7 years. However, little is known about the clinical impact on vulnerable immunosuppressed patient populations. Blood, urine, and respiratory swabs collected from a prospective, longitudinal adult kidney transplant cohort (n = 167) generally pre-operatively, at day 4, months 1, 3, and 6 posttransplant, and at BK viremic episodes within the first year were screened for 12 human polyomaviruses using real-time polymerase chain reaction. Newly discovered polyomaviruses were most commonly detected in the respiratory tract, with persistent shedding seen for up to 6 months posttransplant. Merkel cell polyomavirus was the most common detection, but was not associated with clinical symptoms or subsequent development of skin cancer or other skin abnormalities. In contrast, KI polyomavirus was associated with respiratory disease in a subset of patients. Human polyomavirus 9, Malawi polyomavirus, and human polyomavirus 12 were not detected in any patient samples.

If dung beetles (Scarabaeidae: Scarabaeinae) arose in association with dinosaurs, did they also suffer a mass co-extinction at the K-Pg boundary?

The evolutionary success of beetles and numerous other terrestrial insects is generally attributed to co-radiation with flowering plants but most studies have focused on herbivorous or pollinating insects. Non-herbivores represent a significant proportion of beetle diversity yet potential factors that influence their diversification have been largely unexamined. In the present study, we examine the factors driving diversification within the Scarabaeidae, a speciose beetle family with a range of both herbivorous and non-herbivorous ecologies. In particular, it has been long debated whether the key event in the evolution of dung beetles (Scarabaeidae: Scarabaeinae) was an adaptation to feeding on dinosaur or mammalian dung. Here we present molecular evidence to show that the origin of dung beetles occurred in the middle of the Cretaceous, likely in association with dinosaur dung, but more surprisingly the timing is consistent with the rise of the angiosperms. We hypothesize that the switch in dinosaur diet to incorporate more nutritious and less fibrous angiosperm foliage provided a palatable dung source that ultimately created a new niche for diversification. Given the well-accepted mass extinction of non-avian dinosaurs at the Cretaceous-Paleogene boundary, we examine a potential co-extinction of dung beetles due to the loss of an important evolutionary resource, i.e., dinosaur dung. The biogeography of dung beetles is also examined to explore the previously proposed "out of Africa" hypothesis. Given the inferred age of Scarabaeinae as originating in the Lower Cretaceous, the major radiation of dung feeders prior to the Cenomanian, and the early divergence of both African and Gondwanan lineages, we hypothesise that that faunal exchange between Africa and Gondwanaland occurred during the earliest evolution of the Scarabaeinae. Therefore we propose that both Gondwanan vicariance and dispersal of African lineages is responsible for present day distribution of scarabaeine dung beetles and provide examples.