Characteristics of Beet Soilborne Mosaic Virus, a Furo-like Virus Infecting Sugar Beet

Beet soilborne mosaic virus (BSBMV) is a rigid rod-shaped virus transmitted by Polymyxa betae. Particles were 19 nm wide and ranged from 50 to over 400 nm, but no consistent modal lengths could be determined. Nucleic acids extracted from virions were polyadenylated and typically separated into three or four discrete bands of variable size by agarose-formaldehyde gel electrophoresis. RNA 1 and 2, the largest of the RNAs, consistently averaged 6.7 and 4.6 kb, respectively. The sizes and number of smaller RNA species were variable. The molecular mass of the capsid protein of BSBMV was estimated to be 22.5 kDa. In Northern blots, probes specific to the 3´ end of individual beet necrotic yellow vein virus (BNYVV) RNAs 1–4 hybridized strongly with the corresponding BNYVV RNA species and weakly with BSBMV RNAs 1, 2, and 4. Probes specific to the 5´ end of BNYVV RNAs 1–4 hybridized with BNYVV but not with BSBMV. No cross-reaction between BNYVV and BSBMV was detected in Western blots. In greenhouse studies, root weights of BSBMV-infected plants were significantly lower than mock-inoculated controls but greater than root weights from plants infected with BNYVV. Results of serological, hybridization, and virulence experiments indicate that BSBMV is distinct from BNYVV. However, host range, capsid size, and the number, size, and polyadenylation of its RNAs indicate that BSBMV more closely resembles BNYVV than it does other members of the genus Furovirus

Fourier Analysis of Gapped Time Series: Improved Estimates of Solar and Stellar Oscillation Parameters

Quantitative helio- and asteroseismology require very precise measurements of the frequencies, amplitudes, and lifetimes of the global modes of stellar oscillation. It is common knowledge that the precision of these measurements depends on the total length (T), quality, and completeness of the observations. Except in a few simple cases, the effect of gaps in the data on measurement precision is poorly understood, in particular in Fourier space where the convolution of the observable with the observation window introduces correlations between different frequencies. Here we describe and implement a rather general method to retrieve maximum likelihood estimates of the oscillation parameters, taking into account the proper statistics of the observations. Our fitting method applies in complex Fourier space and exploits the phase information. We consider both solar-like stochastic oscillations and long-lived harmonic oscillations, plus random noise. Using numerical simulations, we demonstrate the existence of cases for which our improved fitting method is less biased and has a greater precision than when the frequency correlations are ignored. This is especially true of low signal-to-noise solar-like oscillations. For example, we discuss a case where the precision on the mode frequency estimate is increased by a factor of five, for a duty cycle of 15%. In the case of long-lived sinusoidal oscillations, a proper treatment of the frequency correlations does not provide any significant improvement; nevertheless we confirm that the mode frequency can be measured from gapped data at a much better precision than the 1/T Rayleigh resolution.Comment: Accepted for publication in Solar Physics Topical Issue "Helioseismology, Asteroseismology, and MHD Connections

Network structure of vertebrate scavenger assemblages at the global scale: drivers and ecosystem functioning implications

publishedVersio

Stochastic thermodynamics of holonomic systems

International audienc

Survey of remote data monitoring systems

A self-contained data-logger device called an SDAS (Site Data Acquisition Subsystem) was built for the National Solar Data Network (NSDN) which could collect analog data from 96 channels, store the data for up to three days, and then transmit the stored data on request to a central facility by voice-grade telephone lines. This system has worked fairly well for the eight years that it has been in service. However, the design and components are getting old and newer dataloggers may be more reliable and accurate and less expensive. This report discusses the results of an extensive search for an SDAS replacement. The survey covered 62 models from 36 manufacturers. These numbers are not indicative of all the dataloggers or manufacturers available, but only those which appeared to have some qualifications for the NSDN datalogger replacement. This report views the datalogger as a system which is made up of sensors, a data acquisition and storage unit, a telecommunications subsystem, and a data processing subsystem. Therefore, there is a section on sensors used in the NSDN, telecommunications technology, and data processing requirements. These four components or subsystems are all necessary in order to have an integrated, successful remote data monitoring network