Costimulatory blockade-based and anti-CD20 antibody/tacrolimus-based immunosuppressive therapies seem to be comparably safe with steroid therapy in nonhuman primates receiving corneal xenotransplantation, as they did not reactivate Rhesus Cytomegalovirus and maintained manageable systemic status. Although reactivation is rare, antiviral prophylaxis for simian varicella virus should be considered in immunocompromised hosts.

Orbit determination of spacecraft using only magnetometer measurements via the unscented Kalman filter (UKF) is presented. An algorithm was formulated by adopting the UKF and an adequate dynamic model developed for processing geomagnetic field measurements. The paper consists of the analysis of force and estimation models, the dependency of position accuracy on orbit type, and measurement errors, as well as a comparison of the UKF and the extended Kalman filter (EKF). Finally, the developed algorithm used actual magnetometer flight data from the Magnetic Field Satellite (MAGSAT). The results obtained from the MAGSAT data demonstrate that the achieved position error was approximately 2 km. The UKF performs similar to the EKF in position accuracy for a sampling interval of less than 20 s. In contrast, for a sampling interval of 40 s, the EKF yields lower position accuracy than the UKF. In particular, the decomposed position errors are not biased because the UKF is not affected by linearization of the measurement function. This improvement makes the magnetometer-based orbit determination method more robust and reliable as a real-time orbit determination system for small satellites that require moderate position accuracy, and also as a backup orbit determination system for large satellites.Nomenclature a drag = acceleration due to atmospheric drag, m=s 2 a geo = acceleration due to geopotential, m=s 2 a SRP = acceleration due to the solar radiation pressure, m=s 2 a sun=moon = acceleration due to the sun and moon's gravity, m=s 2 B r , B , B = the Earth magnetic field vector components, nT B= inverse of the ballistic coefficient, m 2 =kg e = eccentricity F = system function h = measurement function i = orbital inclination, deg K = Kalman gain matrix P = covariance matrix P a = augmented covariance matrix R = measurement covariance matrix r = radial distance from the Earth, m r = position vector in J2000, m t = time, s T orb = orbital period v = velocity vector in J2000, m=s w = system noise vector W m , W c = weight factors for the state (m) and covariance (c) x = state vector x a = augmented state vector, or x T ; w T T y = measurement, nT y = observed measurement , , , and = scaling parameters for the unscented Kalman filter = measurement of sigma point = measurement noise, nT = east longitude, rad = true anomaly, deg = uncertainty (1 standard deviation) in a parameter pos = estimated standard deviation of position error, or 2x 2 y 2 z q = colatitude from the North Pole, rad = sigma points x ; w = right ascension of ascending node, rad ! = argument of perigee, rad

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Two approaches for receiver differential code biases (DCB) estimation using the GPS data obtained from the Korean GPS network (KGN) in South Korea are suggested: the relative and single (absolute) methods. The relative method uses a GPS network, while the single method determines DCBs from a single station only. Their performance was assessed by comparing the receiver DCB values obtained from the relative method with those estimated by the single method. The daily averaged receiver DCBs obtained from the two different approaches showed good agreement for 7 days. The root mean square (RMS) value of those differences is 0.83 nanoseconds (ns). The standard deviation of the receiver DCBs estimated by the relative method was smaller than that of the single method. From these results, it is clear that the relative method can obtain more stable receiver DCBs compared with the single method over a short-term period. Additionally, the comparison between the receiver DCBs obtained by the Korea Astronomy and Space Science Institute (KASI) and those of the IGS Global Ionosphere Maps (GIM) showed a good agreement at 0.3 ns. As the accuracy of DCB values significantly affects the accuracy of ionospheric total electron content (TEC), more studies are needed to ensure the reliability and stability of the estimated receiver DCBs.

Water vapor in the atmosphere is one of the primary greenhouse gases, and has a significant impact on climate change (Kiehl & Trenberth 1997). For research on climate change and numerical weather forecasting, it is important to have accurate estimates of the amount and the distribution of water vapor. However, this is difficult due to the high spatial and temporal variability of water vapor (Bevis et al. 1992). Zenith total delay (ZTD) estimates based on the Global Navigation Satellite System (GNSS) can be transformed into atmospheric water vapor content (Bevis et