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Low-pathogenic avian influenza viruses (LPAIVs) of the H5 subtype can mutate to highly pathogenic forms, potentially destabilizing the poultry industry. Wild migratory birds are considered a natural reservoir of LPAIVs capable of dispersing both high- and low-pathogenic forms of the virus. Therefore, surveillance and characterization of AIV in wild birds are essential. Here, we report on the isolation and genetic characterization of 10 AIVs of the H5N2 subtype obtained through surveillance in Hokkaido, Japan, during 2009 and 2011. Full-genome sequencing revealed that the H5 and N2 genes of these isolates are all closely related to each other, belonging to the Eurasian avian-like lineage, but they are unrelated to H5 highly pathogenic strains of clade 2.3.4.4. The internal genes of the isolates were found to be diverse, consistent with our hypothesis that these H5N2 strains have undergone multiple reassortment events. Even though all of the H5N2 isolates were characterized as LPAIV based on the amino acid sequences at the HA cleavage site, this analysis demonstrates a diverse pool of precursors that may seed future outbreaks in poultry and possible human transmissions, suggesting the need for high-quality surveillance., Japan Society for the Promotion of Science. Grant-in-Aid for the Bilateral Joint Projects, Heiwa Nakajima Foundation, National Institute of Allergy and Infectious Diseases (U.S.) (contracts HHSN266200700009C and HHSN266200700007C)

This study reports on the genetic characterization of an avian influenza virus, subtype H12N3, isolated from an Eurasian green-winged teal (Anas crecca) in Japan in 2009. The entire genome sequence of the isolate was analyzed, and phylogenetic analyses were conducted to characterize the evolutionary history of the isolate. Phylogenetic analysis of the hemagglutinin and neuraminidase genes indicated that the virus belonged to the Eurasian-like avian lineage. Molecular dating indicated that this H12 virus is likely a multiple reassortant influenza A virus. This is the first reported characterization of influenza A virus subtype H12N3 isolated in Japan and these data contribute to the accumulation of knowledge on the genetic diversity and generation of novel influenza A viruses., National Institute of Allergy and Infectious Diseases (U.S.) (Contracts HHSN266200700009C and HHSN266200700007), Japan Society for the Promotion of Science. Grant-in-Aid for the Bilateral Joint Projects, Heiwa Nakajima Foundation

There are three types of data association problems. The first is the observation-to-track association (OTTA) problem, where given an observation with some known measurement statistics and a set of existing candidate (uncertain) resident space object (RSO) tracks the analyst seeks to associate each observation with a unique track (or none). The second association problem is where we have multiple tracks at different time instances and wish to determine whether any of the tracks belong to the same RSO. This is the track-to-track association (TTTA) problem. The final association problem is where we are given a set of observations at different time instances and wish to determine which of these observations were generated by the same RSO. This is the observation-to-observation association (OTOA) problem. The focus of our paper is the OTOA problem. In this paper, we tackle the OTOA problem by using an appropriate initial orbit determination (IOD) method as well as criteria from information theory. The two main criteria we use in this paper are mutual information and information divergence. We demonstrate how these two criteria can be used within an unscented transform framework as well as with a particle-based approach. The information theoretic solutions described in this paper can be adjusted to address the other (OTTA and TTTA) association problems, which will be the focus of future research. We will demonstrate the main result in simulation., In the Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, 9-12 Sep 2014, Maui, HI.

The admissible region is defined as the set of physically acceptable orbits (i.e., orbits with negative energies). Given additional constraints on orbital semi-major axis, eccentricity, etc, the admissible region is further constrained, resulting in the constrained admissible region (CAR). Based on known statistics of the measurement process, in this paper we replace hard constraints with a probabilistic representation of the admissible region. This results in the probabilistic admissible region (PAR) that can be used for orbit initiation in Bayesian tracking. While this is a general concept that is applicable to any measurement scenario, we will illustrate the idea using a short-arc, angles-only observation scenario., In the Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, 9-12 Sep 2014, Maui, HI.

Continuing outbreaks of pathogenic (H5N1) and pandemic (SOIVH1N1) influenza have underscored the need to understand the origin, characteristics, and evolution of novel influenza A virus (IAV) variants that pose a threat to human health. In the last 4–5 years, focus has been placed on the organization of large-scale surveillance programs to examine the phylogenetics of avian influenza virus (AIV) and host–virus relationships in domestic and wild animals. Here we review the current gaps in wild animal and environmental surveillance and the current understanding of genetic signatures in potentially pandemic strains., National Institute of Allergy and Infectious Diseases (U.S.) (Contract HHSN266200700010C), Massachusetts Institute of Technology