Performance of GPS/GPRS tracking devices improves with increased fix interval and is not affected by animal deployment

The use of GPS tracking technologies has revolutionized the study of animal movement providing unprecedentedly detailed information. The characterization of GPS accuracy and precision under different conditions is essential to correctly identify the spatial and temporal resolution at which studies can be conducted. Here, we examined the influence of fix acquisition interval and device deployment on the performance of a new GPS/GSM solar powered device. Horizontal and vertical accuracy and precision of locations were obtained under different GPS fix acquisition intervals (1min, 20 min and 60 min) in a stationary test. The test devices were deployed on pre-fledgling white storks (Ciconia ciconia) and we quantified accuracy and precision after deployment while controlling for bias caused by variation in habitat, topography, and animal movement. We also assessed the performance of GPSError, a metric provided by the device, at identifying inaccurate locations (> 10 m). Average horizontal accuracy varied between 3.4 to 6.5 m, and vertical accuracy varied between 4.9 to 9.7 m, in high (1 min) and low frequency (60 min) GPS fix intervals. These values were similar after the deployment on white storks. Over 84% of GPS horizontal positions and 71% of vertical positions had less than 10m error in accuracy. Removing 3% of data with highest GPS-Error eliminated over 99% of inaccurate positions in high GPS frequency intervals, but this metric was not effective in the low frequency intervals. We confirmed the suitability of these devices for studies requiring horizontal and vertical accuracies of 5-10m. For higher accuracy data, intensive GPS fix intervals should be used, but this requires more sophisticated battery management, or larger batteries and devicesinfo:eu-repo/semantics/publishedVersio

Density of states "width parity" effect in d-wave superconducting quantum wires

We calculate the density of states (DOS) in a clean mesoscopic d-wave superconducting quantum wire, i.e. a sample of infinite length but finite width $N$. For open boundary conditions, the DOS at zero energy is found to be zero if $N$ is even, and nonzero if $N$ is odd. At finite chemical potential, all chains are gapped but the qualtitative differences between even and odd $N$ remain.Comment: 7 pages, 8 figures, new figures and extended discussio

Time-in-area represents foraging activity in a wide-ranging pelagic forager

Successful Marine Spatial Planning depends upon the identification of areas with high importance for particular species, ecosystems or processes. For seabirds, advancements in biologging devices have enabled us to identify these areas through the detailed study of at-sea behaviour. However, in many cases, only positional data are available and the presence of local biological productivity and hence seabird foraging behaviour is inferred from these data alone, under the untested assumption that foraging activity is more likely to occur in areas where seabirds spend more time. We fitted GPS devices and accelerometers to northern gannets Morus bassanus and categorised the behaviour of individuals outside the breeding colony as plunge diving, surface foraging, floating and flying. We then used the locations of foraging events to test the efficiency of 2 approaches: time-in-area and kernel density (KD) analyses, which are widely employed to detect highly-used areas and interpret foraging behaviour from positional data. For KD analyses, the smoothing parameter (h) was calculated using the ad hoc method (KDad hoc), and KDh=9.1, where h = 9.1 km, to designate core foraging areas from location data. A high proportion of foraging events occurred in core foraging areas designated using KDad hoc, KDh=9.1, and time-in-area. Our findings demonstrate that foraging activity occurs in areas where seabirds spend more time, and that both KD analysis and the time-in-area approach are equally efficient methods for this type of analysis. However, the time-in-area approach is advantageous in its simplicity, and in its ability to provide the shapes commonly used in planning. Therefore, the time-in-area approach can be used as a simple way of using seabirds to identify ecologically important locations from both tracking and survey data

Fokker-Planck equations and density of states in disordered quantum wires

We propose a general scheme to construct scaling equations for the density of states in disordered quantum wires for all ten pure Cartan symmetry classes. The anomalous behavior of the density of states near the Fermi level for the three chiral and four Bogoliubov-de Gennes universality classes is analysed in detail by means of a mapping to a scaling equation for the reflection from a quantum wire in the presence of an imaginary potential.Comment: 10 pages, 5 figures, revised versio

Information for decision making from imperfect national data: tracking major changes in health care use in Kenya using geostatistics

Background: most Ministries of Health across Africa invest substantial resources in some form of health management information system (HMIS) to coordinate the routine acquisition and compilation of monthly treatment and attendance records from health facilities nationwide. Despite the expense of these systems, poor data coverage means they are rarely, if ever, used to generate reliable evidence for decision makers. One critical weakness across Africa is the current lack of capacity to effectively monitor patterns of service use through time so that the impacts ofchanges in policy or service delivery can be evaluated. Here, we present a new approach that, for the first time, allows national changes in health service use during a time of major health policy change to be tracked reliably using imperfect data from a national HMIS.Methods: monthly attendance records were obtained from the Kenyan HMIS for 1 271 government-run and 402 faith-based outpatient facilities nationwide between 1996 and 2004. Aspace-time geostatistical model was used to compensate for the large proportion of missing records caused by non-reporting health facilities, allowing robust estimation of monthly and annualuse of services by outpatients during this period.Results: we were able to reconstruct robust time series of mean levels of outpatient utilisation of health facilities at the national level and for all six major provinces in Kenya. These plots revealed reliably for the first time a period of steady nationwide decline in the use of health facilities in Kenyabetween 1996 and 2002, followed by a dramatic increase from 2003. This pattern was consistent across different causes of attendance and was observed independently in each province.Conclusion: the methodological approach presented can compensate for missing records in health information systems to provide robust estimates of national patterns of outpatient service use. This represents the first such use of HMIS data and contributes to the resurrection of these hugely expensive but underused systems as national monitoring tools. Applying this approach to Kenya has yielded output with immediate potential to enhance the capacity of decision makers in monitoring nationwide patterns of service use and assessing the impact of changes in health policy and service deliver

Evaluating the impact of the community-based health planning and services initiative on uptake of skilled birth care in Ghana

Background: the Community-based Health Planning and Services (CHPS) initiative is a major government policy to improve maternal and child health and accelerate progress in the reduction of maternal mortality in Ghana. However, strategic intelligence on the impact of the initiative is lacking, given the persistent ?problems of patchy geographical access to care for rural women. This study investigates the impact of proximity to CHPS on facilitating uptake of skilled ?birth care in rural areas.Methods and findings: data from the ?2003 and 2008 Demographic and Health Survey, ? on 4,349 births from 463 rural communities were linked to georeferenced data on health facilities, CHPS and topographic data on national road-networks. Distance to nearest health facility and CHPS was computed using the closest facility functionality in ArcGIS 10.1. Multilevel logistic regression was used to examine the effect of proximity to health facilities and CHPS on use of skilled care at birth, adjusting for relevant predictors and clustering within ?communities.? The results show that a substantial proportion of births continue to occur in communities more than 8 km from both ?health facilities and CHPS. Increases in uptake of skilled birth care are more pronounced where both health ?facilities and CHPS compounds are within 8 km, but not in communities within 8 km of CHPS but lack access to health facilities. Where both health facilities and CHPS are within 8 km, the odds of skilled ?birth care is 16% higher than ?where there is only a health facility within 8km. Conclusion: where CHPS compounds are set up near health facilities, there is improved access to care, demonstrating the facilitatory role of CHPS in stimulating access to better care at birth, in areas where health facilities are accessible. <br/

The change in productivity of Chinese state enterprises, 1983–1987

This study estimates the change in productivity of Chinese state enterprises during 1983–1987 using a panel data set of 403 firms. A new approach to productivity measurement is used. Under this approach, the production functions can differ arbitrarily across firms, important given the heterogeneity of the sample. The resulting coefficients estimate the marginal products of each factor as well as overall productivity growth. The results suggest Chinese productivity increased by 4.6% per year, with about half of this growth due to the rapidly improving education of the labor force.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47564/1/11123_2005_Article_BF01073492.pd

A local space–time kriging approach applied to a national outpatient malaria data set

Increases in the availability of reliable health data are widely recognised as essential for efforts to strengthen health-care systems in resource-poor settings worldwide. Effective health-system planning requires comprehensive and up-to-date information on a range of health metrics and this requirement is generally addressed by a Health Management Information System (HMIS) that coordinates the routine collection of data at individual health facilities and their compilation into national databases. In many resource-poor settings, these systems are inadequate and national databases often contain only a small proportion of the expected records. In this paper, we take an important health metric in Kenya (the proportion of outpatient treatments for malaria (MP)) from the national HMIS database and predict the values of MP at facilities where monthly records are missing. The available MP data were densely distributed across a spatiotemporal domain and displayed second-order heterogeneity. We used three different kriging methodologies to make cross-validation predictions of MP in order to test the effect on prediction accuracy of (a) the extension of a spatial-only to a space–time prediction approach, and (b) the replacement of a globally stationary with a locally varying random function model. Space–time kriging was found to produce predictions with 98.4% less mean bias and 14.8% smaller mean imprecision than conventional spatial-only kriging. A modification of space–time kriging that allowed space–time variograms to be recalculated for every prediction location within a spatially local neighbourhood resulted in a larger decrease in mean imprecision over ordinary kriging (18.3%) although the mean bias was reduced less (87.5%)

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results