A feasibility study for long-path multiple detection using a neural network

Least-squares inverse filters have found widespread use in the deconvolution of seismograms and the removal of multiples. The use of least-squares prediction filters with prediction distances greater than unity leads to the method of predictive deconvolution which can be used for the removal of long path multiples. The predictive technique allows one to control the length of the desired output wavelet by control of the predictive distance, and hence to specify the desired degree of resolution. Events which are periodic within given repetition ranges can be attenuated selectively. The method is thus effective in the suppression of rather complex reverberation patterns. A back propagation(BP) neural network is constructed to perform the detection of first arrivals of the multiples and therefore aid in the more accurate determination of the predictive distance of the multiples. The neural detector is applied to synthetic reflection coefficients and synthetic seismic traces. The processing results show that the neural detector is accurate and should lead to an automated fast method for determining predictive distances across vast amounts of data such as seismic field records. The neural network system used in this study was the NASA Software Technology Branch's NETS system

Toward an automated signature recognition toolkit for mission operations

Signature recognition is the problem of identifying an event or events from its time series. The generic problem has numerous applications to science and engineering. At NASA's Johnson Space Center, for example, mission control personnel, using electronic displays and strip chart recorders, monitor telemetry data from three-phase electrical buses on the Space Shuttle and maintain records of device activation and deactivation. Since few electrical devices have sensors to indicate their actual status, changes of state are inferred from characteristic current and voltage fluctuations. Controllers recognize these events both by examining the waveform signatures and by listening to audio channels between ground and crew. Recently the authors have developed a prototype system that identifies major electrical events from the telemetry and displays them on a workstation. Eventually the system will be able to identify accurately the signatures of over fifty distinct events in real time, while contending with noise, intermittent loss of signal, overlapping events, and other complications. This system is just one of many possible signature recognition applications in Mission Control. While much of the technology underlying these applications is the same, each application has unique data characteristics, and every control position has its own interface and performance requirements. There is a need, therefore, for CASE tools that can reduce the time to implement a running signature recognition application from months to weeks or days. This paper describes our work to date and our future plans

Molecular Ecology and Natural History of Simian Foamy Virus Infection in Wild-Living Chimpanzees

Identifying microbial pathogens with zoonotic potential in wild-living primates can be important to human health, as evidenced by human immunodeficiency viruses types 1 and 2 (HIV-1 and HIV-2) and Ebola virus. Simian foamy viruses (SFVs) are ancient retroviruses that infect Old and New World monkeys and apes. Although not known to cause disease, these viruses are of public health interest because they have the potential to infect humans and thus provide a more general indication of zoonotic exposure risks. Surprisingly, no information exists concerning the prevalence, geographic distribution, and genetic diversity of SFVs in wild-living monkeys and apes. Here, we report the first comprehensive survey of SFVcpz infection in free-ranging chimpanzees (Pan troglodytes) using newly developed, fecal-based assays. Chimpanzee fecal samples (n = 724) were collected at 25 field sites throughout equatorial Africa and tested for SFVcpz-specific antibodies (n = 706) or viral nucleic acids (n = 392). SFVcpz infection was documented at all field sites, with prevalence rates ranging from 44% to 100%. In two habituated communities, adult chimpanzees had significantly higher SFVcpz infection rates than infants and juveniles, indicating predominantly horizontal rather than vertical transmission routes. Some chimpanzees were co-infected with simian immunodeficiency virus (SIVcpz); however, there was no evidence that SFVcpz and SIVcpz were epidemiologically linked. SFVcpz nucleic acids were recovered from 177 fecal samples, all of which contained SFVcpz RNA and not DNA. Phylogenetic analysis of partial gag (616 bp), pol-RT (717 bp), and pol-IN (425 bp) sequences identified a diverse group of viruses, which could be subdivided into four distinct SFVcpz lineages according to their chimpanzee subspecies of origin. Within these lineages, there was evidence of frequent superinfection and viral recombination. One chimpanzee was infected by a foamy virus from a Cercopithecus monkey species, indicating cross-species transmission of SFVs in the wild. These data indicate that SFVcpz (i) is widely distributed among all chimpanzee subspecies; (ii) is shed in fecal samples as viral RNA; (iii) is transmitted predominantly by horizontal routes; (iv) is prone to superinfection and recombination; (v) has co-evolved with its natural host; and (vi) represents a sensitive marker of population structure that may be useful for chimpanzee taxonomy and conservation strategies