8 research outputs found
The global oscillation network group site survey. II. Results
The Global Oscillation Network Group (GONG) Project will place a network of instruments around the world to observe solar oscillations as continuously as possible for three years. The Project has now chosen the six network sites based on analysis of survey data from fifteen sites around the world. The chosen sites are: Big Bear Solar Observatory, California; Mauna Loa Solar Observatory, Hawaii; Learmonth Solar Observatory, Australia; Udaipur Solar Observatory, India; Observatorio del Teide, Tenerife; and Cerro Tololo Interamerican Observatory, Chile.
Total solar intensity at each site yields information on local cloud cover, extinction coefficient, and transparency fluctuations. In addition, the performance of 192 reasonable components analysis. An accompanying paper describes the analysis methods in detail; here we present the results of both the network and individual site analyses.
The selected network has a duty cycle of 93.3%, in good agreement with numerical simulations. The power spectrum of the network observing window shows a first diurnal sidelobe height of 3 × 10⁻⁴ with respect to the central component, an improvement of a factor of 1300 over a single site. The background level of the network spectrum is lower by a factor of 50 compared to a single-site spectrum
The global oscillation network group site survey. II. Results
The Global Oscillation Network Group (GONG) Project will place a network of instruments around the world to observe solar oscillations as continuously as possible for three years. The Project has now chosen the six network sites based on analysis of survey data from fifteen sites around the world. The chosen sites are: Big Bear Solar Observatory, California; Mauna Loa Solar Observatory, Hawaii; Learmonth Solar Observatory, Australia; Udaipur Solar Observatory, India; Observatorio del Teide, Tenerife; and Cerro Tololo Interamerican Observatory, Chile.
Total solar intensity at each site yields information on local cloud cover, extinction coefficient, and transparency fluctuations. In addition, the performance of 192 reasonable components analysis. An accompanying paper describes the analysis methods in detail; here we present the results of both the network and individual site analyses.
The selected network has a duty cycle of 93.3%, in good agreement with numerical simulations. The power spectrum of the network observing window shows a first diurnal sidelobe height of 3 × 10⁻⁴ with respect to the central component, an improvement of a factor of 1300 over a single site. The background level of the network spectrum is lower by a factor of 50 compared to a single-site spectrum
Pregnancy stage and number of fetuses may influence maternal plasma leptin in ewes
Maternal plasma leptin is elevated in ewes during pregnancy. The authors studied whether there was any relation between maternal plasma leptin and insulin concentrations, the number of fetuses and the circulating and faecal levels of gestagens. At the end of the breeding season in January the ovarian activity of Prolific Merino ewes was induced/synchronised with gestagen + eCG treatment. Ewes were inseminated artificially (AI) by laparoscopy. Blood and faecal samples were collected before AI (day 0) and again 41, 81 and 101 days later. The plasma levels of leptin (pL), insulin and progesterone (pP4), and the faecal P4 metabolite (P4-met) content were determined. The day 0 level of pL was significantly higher in pregnant (n = 24) than in non-pregnant ewes (n = 32). By day 41 the pL of pregnant animals had doubled, it showed a further moderate increase on day 81, and decreased slightly thereafter. During pregnancy pP4 and faecal P4-met rose continuously and were positively correlated at all stages. The mean levels of pL and pP4 and the faecal content of P4-met were lower in ewes bearing single (n = 12) than in those with 2 (n = 6) or 3-5 fetuses (n = 6). Analysis of variance demonstrated significant differences according to the number of fetuses in the pL and pP4, but not in P4-met (p = 0.042, 0.044, and 0.051, respectively). Leptin showed positive correlation with insulin before the AI but not during pregnancy. On days 41 and 81 pL showed a slight positive correlation with P4 and P4-met, which decreased slightly by day 101. This study shows that although leptinaemia is affected by the number of fetuses and the level of P4, pregnancy stage is a more important regulator than these additional factors
Metagenomic Detection of Viral Pathogens in Spanish Honeybees: Co- Infection by Aphid Lethal Paralysis, Israel Acute Paralysis and Lake Sinai Viruses
The situation in Europe concerning honeybees has in recent years become increasingly aggravated with steady decline in populations and/or catastrophic winter losses. This has largely been attributed to the occurrence of a variety of known and "unknown", emerging novel diseases. Previous studies have demonstrated that colonies often can harbour more than one pathogen, making identification of etiological agents with classical methods difficult. By employing an unbiased metagenomic approach, which allows the detection of both unexpected and previously unknown infectious agents, the detection of three viruses, Aphid Lethal Paralysis Virus (ALPV), Israel Acute Paralysis Virus (IAPV), and Lake Sinai Virus (LSV), in honeybees from Spain is reported in this article. The existence of a subgroup of ALPV with the ability to infect bees was only recently reported and this is the first identification of such a strain in Europe. Similarly, LSV appear to be a still unclassified group of viruses with unclear impact on colony health and these viruses have not previously been identified outside of the United States. Furthermore, our study also reveals that these bees carried a plant virus, Turnip Ringspot Virus (TuRSV), potentially serving as important vector organisms. Taken together, these results demonstrate the new possibilities opened up by high-throughput sequencing and metagenomic analysis to study emerging new diseases in domestic and wild animal populations, including honeybees