Optimization of Optical Follow-up Strategies Based on Covariance Analysis

An in-depth study, using simulations and covariance analysis, is performed to identify the optimal sequence of observations to obtain the most accurate orbit propagation. The accuracy of the results of an orbit determination/ improvement process depends on: tracklet length, number of observations, type of orbit, astrometric error, time interval between tracklets and observation geometry. The latter depends on the position of the object along its orbit and the location of the observing station. This covariance analysis aims to optimize the observation strategy taking into account the influence of the orbit shape, of the relative object-observer geometry and the interval between observations.

A Genetic Algorithm to associate optical measurements and estimate orbits of geocentric objects

Cataloging geocentric objects can be put in the framework of Multiple Target Tracking (MTT). Current work tends to focus on the S = 2 MTT problem because of its favorable computational complexity of O(n²). The MTT problem becomes NP-hard for a dimension of S˃3. The challenge is to find an approximation to the solution within a reasonable computation time. To effciently approximate this solution a Genetic Algorithm is used. The algorithm is applied to a simulated test case. These results represent the first steps towards a method that can treat the S˃3 problem effciently and with minimal manual intervention.

A covariance analysis to optimize the optical follow-up strategies

The Astronomical Institute of the University of Bern (AIUB) is conducting several search campaigns for space debris using optical sensors. The debris objects are discovered during systematic survey observations. In general, the result of a discovery consists in only a short observation arc, or tracklet, which is used to perform a first orbit determination in order to be able to observe t he object again in subsequent follow-up observations. The additional observations are used in the orbit improvement process to obtain accurate orbits to be included in a catalogue. In order to obtain the most accurate orbit within the time available it is necessary to optimize the follow-up observations strategy. In this paper an in‐depth study, using simulations and covariance analysis, is performed to identify the optimal sequence of follow-up observations to obtain the most accurate orbit propagation to be used for the space debris catalogue maintenance. The main factors that determine the accuracy of the results of an orbit determination/improvement process are: tracklet length, number of observations, type of orbit, astrometric error of the measurements, time interval between tracklets, and the relative position of the object along its orbit with respect to the observing station. The main aim of the covariance analysis is to optimize the follow-up strategy as a function of the object-observer geometry, the interval between follow-up observations and the shape of the orbit. This an alysis can be applied to every orbital regime but particular attention was dedicated to geostationary, Molniya, and geostationary transfer orbits. Finally the case with more than two follow-up observations and the influence of a second observing station are also analyzed.

Relative estimate of accuracy in orbit determination from a short tracklet

The Astronomical Institute of the University of Bern (AIUB) is conducting several search campaigns for orbital debris. The debris objects are discovered during systematic survey observations. In general only a short observation arc, or tracklet, is available for most of these objects. From this discovery tracklet a first orbit determination is computed in order to be able to find the object again in subsequent follow-up observations. The additional observations are used in the orbit improvement process to obtain accurate orbits to be included in a catalogue. In this paper, the accuracy of the initial orbit determination is analyzed. This depends on a number of factors: tracklet length, number of observations, type of orbit, astrometric error, and observation geometry. The latter is characterized by both the position of the object along its orbit and the location of the observing station. Different positions involve different distances from the target object and a different observing angle with respect to its orbital plane and trajectory. The present analysis aims at optimizing the geometry of the discovery observation is depending on the considered orbit.

A Thalamic-Fronto-Parietal Structural Covariance Network Emerging in the Course of Recovery from Hand Paresis after Ischemic Stroke.

AIM To describe structural covariance networks of gray matter volume (GMV) change in 28 patients with first-ever stroke to the primary sensorimotor cortices, and to investigate their relationship to hand function recovery and local GMV change. METHODS Tensor-based morphometry maps derived from high-resolution structural images were subject to principal component analyses to identify the networks. We calculated correlations between network expression and local GMV change, sensorimotor hand function and lesion volume. To verify which of the structural covariance networks of GMV change have a significant relationship to hand function, we performed an additional multivariate regression approach. RESULTS Expression of the second network, explaining 9.1% of variance, correlated with GMV increase in the medio-dorsal (md) thalamus and hand motor skill. Patients with positive expression coefficients were distinguished by significantly higher GMV increase of this structure during stroke recovery. Significant nodes of this network were located in md thalamus, dorsolateral prefrontal cortex, and higher order sensorimotor cortices. Parameter of hand function had a unique relationship to the network and depended on an interaction between network expression and lesion volume. Inversely, network expression is limited in patients with large lesion volumes. CONCLUSION Chronic phase of sensorimotor cortical stroke has been characterized by a large scale co-varying structural network in the ipsilesional hemisphere associated specifically with sensorimotor hand skill. Its expression is related to GMV increase of md thalamus, one constituent of the network, and correlated with the cortico-striato-thalamic loop involved in control of motor execution and higher order sensorimotor cortices. A close relation between expression of this network with degree of recovery might indicate reduced compensatory resources in the impaired subgroup.

Nonperturbative estimate of the heavy quark momentum diffusion coefficient

We estimate the momentum diffusion coefficient of a heavy quark within a pure SU(3) plasma at a temperature of about 1.5Tc. Large-scale Monte Carlo simulations on a series of lattices extending up to 1923×48 permit us to carry out a continuum extrapolation of the so-called color-electric imaginary-time correlator. The extrapolated correlator is analyzed with the help of theoretically motivated models for the corresponding spectral function. Evidence for a nonzero transport coefficient is found and, incorporating systematic uncertainties reflecting model assumptions, we obtain κ=(1.8–3.4)T3. This implies that the “drag coefficient,” characterizing the time scale at which heavy quarks adjust to hydrodynamic flow, is η−1D=(1.8–3.4)(Tc/T)2(M/1.5  GeV)  fm/c, where M is the heavy quark kinetic mass. The results apply to bottom and, with somewhat larger systematic uncertainties, to charm quarks.

A case-control study to estimate the effects of acute clinical infection with the Schmallenberg virus on milk yield, fertility and veterinary costs in Swiss dairy herds.

Schmallenberg virus (SBV) was first detected in Switzerland in July 2012 and many Swiss dairy farmers reported acute clinical signs in dairy cattle during the spread of the virus until December 2012. The objectives of the present study were to investigate the effects of an acute infection with SBV on milk yield, fertility and veterinary costs in dairy farms with clinical signs of SBV infection (case farms), and to compare those farms to a matched control group of dairy farms in which cattle did not show clinical signs of SBV infection. Herd size was significantly (p<0.001) larger in case farms (33 cows, n=77) than in control farms (25 cows, n=84). Within case herds, 14.8% (median) of the cows showed acute clinical signs. Managers from case farms indicated to have observed a higher abortion rate during the year with SBV (6.5%) than in the previous year (3.7%). Analysis of fertility parameters based on veterinary bills and data from the breeding associations showed no significant differences between case and control farms. The general veterinary costs per cow from July to December 2012 were significantly higher (p=0.02) in case (CHF 19.80; EUR 16.50) than in control farms (CHF 15.90; EUR 13.25). No differences in milk yield were found between groups, but there was a significant decrease in milk production in case farms in the second half year in 2012 compared to the same period in 2011 (p<0.001) and 2013 (p=0.009). The average daily milk yield per cow (both groups together) was +0.73kg higher (p=0.03) in the second half year 2011 and +0.52kg (p=0.12) in the second half year 2013 compared to the same half year 2012. Fifty-seven percent of the cows with acute clinical signs (n=461) were treated by a veterinarian. The average calculated loss after SBV infection for a standardized farm was CHF 1606 (EUR 1338), which can be considered as low at the national level, but the losses were subject to great fluctuations between farms, so that individual farms could have very high losses (>CHF 10,000, EUR 8333).

Bexar County's dental safety net for children: An estimate of our current capacity and need

Introduction. It has been well established that poor uninsured children lack access to dental care and have greater dental needs than their insured counterparts. ^ Objective. To assess the capacity of Bexar County's dental safety net to treat children. To assess the dental needs of Bexar County children ages 0-18 who are uninsured or are Medicaid or SCHIP recipients. ^ Methods. Information was requested from dental safety net clinics that treat children ages 0-18. Data from the census, NHANES and other sources was used to estimate the dental needs. ^ Results. The capacity of the current safety net to treat children is 33,537 patient encounters per year. The dental needs of the community are 227,124 patient encounters per year. ^ Conclusion. The results of the study indicate that Bexar County is not prepared to treat the dental needs of the underserved children in San Antonio.^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

Aedes aegypti, Aedes albopictus, and Dengue virus in Harris county: An estimate of risk

Recent outbreaks of dengue fever (DF) along the United States/Mexico border, coupled with the high number of reported cases in Mexico suggest that there is the possibility for DF emergence in Houston, Texas1,2. To determine the presence of DF, populations of Aedes aegypti and Aedes albopictus were identified and tested for dengue virus. Maps were created to identify "hot spots" (Figure 1) based on historical data on Ae. aegypti and Ae. albopictus, demographic information, and locations of human cases of dengue fever. BG Sentinel Traps®, in conjunction with BG Lure® attractant, octanol and dry ice, were used to collect mosquitoes, which were then tested for presence of dengue virus using ELISA techniques. All samples tested were negative for dengue virus (DV). Survival of DV ultimately comes down to whether or not it will be vectored by a mosquito to a susceptible human host. The presence of infected humans and contact with the mosquito vectors are two critical factors necessary in the establishment of DF. Historical records indicate the presence of Ae. aegypti and Ae. albopictus in Harris County, which would support localized dengue transmission if infected individuals are present.^ (1) Brunkard JM, Robles-Lopez JL, Ramirez J, Cifuentes E, Rothenberg SJ, Hunsperger EA, Moore CG, Brussolo RM, Villarreal NA, Haddad BM, 2007. Dengue fever seroprevalence and risk factors, Texas-Mexico border, 2004. Emerg Infect Dis 13: 1477-1483. (2) Ramos MM, Mohammed H, Zielinski-Gutierrez E, Hayden MH, Lopez JL, Fournier M, Trujillo AR, Burton R, Brunkard JM, Anaya-Lopez L, Banicki AA, Morales PK, Smith B, Munoz JL, Waterman SH, 2008. Epidemic dengue and dengue hemorrhagic fever at the Texas-Mexico Border: results of a household-based seroepidemiologic survey, December 2005. Am J Trop Med Hyg 78: 364-369.^

THE USE OF MULTIVARIATE ANALYSIS OF COVARIANCE IN EVALUATING THE COMPARABILITY OF LABORATORY DETERMINATIONS IN COOPERATIVE STUDIES

The role of clinical chemistry has traditionally been to evaluate acutely ill or hospitalized patients. Traditional statistical methods have serious drawbacks in that they use univariate techniques. To demonstrate alternative methodology, a multivariate analysis of covariance model was developed and applied to the data from the Cooperative Study of Sickle Cell Disease.^ The purpose of developing the model for the laboratory data from the CSSCD was to evaluate the comparability of the results from the different clinics. Several variables were incorporated into the model in order to control for possible differences among the clinics that might confound any real laboratory differences.^ Differences for LDH, alkaline phosphatase and SGOT were identified which will necessitate adjustments by clinic whenever these data are used. In addition, aberrant clinic values for LDH, creatinine and BUN were also identified.^ The use of any statistical technique including multivariate analysis without thoughtful consideration may lead to spurious conclusions that may not be corrected for some time, if ever. However, the advantages of multivariate analysis far outweigh its potential problems. If its use increases as it should, the applicability to the analysis of laboratory data in prospective patient monitoring, quality control programs, and interpretation of data from cooperative studies could well have a major impact on the health and well being of a large number of individuals. ^

A PROPOSED SAMPLE-BASED TECHNIQUE TO ESTIMATE THE STANDARDIZED MORTALITY RATIO

Evaluation of a series of deaths due to a particular disease is a frequently requested task in occupational epidemiology. There are several techniques available to determine whether a series represents an occupational health problem. Each of these techniques, however, is subject to certain limitations including cost, applicability to a given situation, feasibility relative to available resources, or potential for bias. In light of these problems, a technique was developed to estimate the standardized mortality ratio at a greatly reduced cost. The technique is demonstrated by its application in the investigation of brain cancer among employees of a large chemical company. ^

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^