Reynolds and Mach number simulation of Apollo and Gemini re-entry and comparison with flight

Reynolds and Mach numbers simulation of Apollo and Gemini reentry compared with flight dat

Forecast horizon aggregation in integer autoregressive moving average (INARMA) models

This paper addresses aggregation in integer autoregressive moving average (INARMA) models. Although aggregation in continuous-valued time series has been widely discussed, the same is not true for integer-valued time series. Forecast horizon aggregation is addressed in this paper. It is shown that the overlapping forecast horizon aggregation of an INARMA process results in an INARMA process. The conditional expected value of the aggregated process is also derived for use in forecasting. A simulation experiment is conducted to assess the accuracy of the forecasts produced by the aggregation method and to compare it to the accuracy of cumulative h-step ahead forecasts over the forecasting horizon. The results of an empirical analysis are also provided

CCM2 Molecular Signaling Pathway

Cerebral cavernous malformations (CCM) are a central nervous system vascular malformation often responsible for hemorrhagic strokes. Molecular genetic studies have identified three genes (CCMl KRITI, CCM2 Malcavernin, and CCM3 PDCDIO) and four possible loci responsible for the pathogenesis of these lesions. CCMl functions through integrin signaling and regulation of RACl activity and may be involved in the MAPK and JNK signaling cascades. We hypothesized that CCM2 likely functioned through the same pathways and that CCM3 expression is regulated by these stress-induced signaling cascades. We showed that CCM2 likely functions through the MAPK pathway as the mouse homolog, osmosensing scaffold protein for MEKK3 (OSM), has been shown to interact in the p38 mitogen activated protein kinase (p38 MAPK) signaling pathway regulated by RAC1. We confirmed that CCMl and CCM2 signal as a complex since co-immunoprecipitation indicates joint expression. We also characterized the role of CCM3 in the MAPK pathway by identifying interacting serine threonine kinases (STK) and KIAA0826 based on yeast two-hybrid data. This was further examined through immunohistochemical analysis showing CCM3 is expressed in a variety of human organs especially arterial vascular endothelium in a similar pattern to CCM2. The yeast two-hybrid data supports current theories that there is a link between CCM pathogenesis and the ERK-MAPK cascade. These findings correlate with previous studies and further elucidate the signaling pathways involved in CCM pathogenesis which may in turn be helpful in future therapeutic advances

Milk production in Finnsheep and Romanov breeds

The Finn, Romanov and several U.S. sheep breeds were machine milked to obtain information on several measures of milk production and milk composition. Data were obtained over at wo year to four year period utilizing 146 purebred ewe records and 165 crossbred ewe records. The level of milk production for a 130 day lactation period for the breeds evaluated was generally low compared to traditional European dairy breeds. The least-squares overall mean for milk yield was 68.8 liters. The Suffolk (80.5 liters) and the Rambouillet (75.3 liters) were superior. The Targhee, Dorset and Lincoln breeds followed in order for milk yield. The Finn (64.0 liters) and Romanov (39.1 liters) were lowest. Finn sired crossbred ewes had the highest level of milk production (84.4 liters) in a four breed diallel mating design of Finn, Dorset, Lincoln and Rambouillet breeds. A value of 15.4 % was found for heterosis in milk production

Formation of seasonal groups and application of seasonal indices

Estimating seasonal variations in demand is a challenging task faced by many organisations. There may be many stock-keeping units (SKUs) to forecast, but often data histories are short, with very few complete seasonal cycles. It has been suggested in the literature that group seasonal indices (GSI) methods should be used to take advantage of information on similar SKUs. This paper addresses two research questions: (1) how should groups be formed in order to use the GSI methods? and (2) when should the GSI methods and the individual seasonal indices (ISI) method be used? Theoretical results are presented, showing that seasonal grouping and forecasting may be unified, based on a Mean Square Error criterion, and K-means clustering. A heuristic K-means method is presented, which is competitive with the Average Linkage method. It offers a viable alternative to a company’s own grouping method or may be used with confidence if a company lacks a grouping method. The paper gives empirical findings that confirm earlier theoretical results that greater accuracy may be obtained by employing a rule that assigns the GSI method to some SKUs and the ISI method to the remainder

Reproducibility in forecasting research

The importance of replication has been recognised across many scientific disciplines. Reproducibility is a necessary condition for replicability, because an inability to reproduce results implies that the methods have not been specified sufficiently, thus precluding replication. This paper describes how two independent teams of researchers attempted to reproduce the empirical findings of an important paper, ‘‘Shrinkage estimators of time series seasonal factors and their effect on forecasting accuracy’’ (Miller & Williams, 2003). The two teams proceeded systematically, reporting results both before and after receiving clarifications from the authors of the original study. The teams were able to approximately reproduce each other’s results, but not those of Miller and Williams. These discrepancies led to differences in the conclusions as to the conditions under which seasonal damping outperforms classical decomposition. The paper specifies the forecasting methods employed using a flowchart. It is argued that this approach to method documentation is complementary to the provision of computer code, as it is accessible to a broader audience of forecasting practitioners and researchers. The significance of this research lies not only in its lessons for seasonal forecasting but also, more generally, in its approach to the reproduction of forecasting research