896 resultados para sensor grid database system


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We obtained partial carcass condemnation (PCC) data for cattle (2009-2010) from a Swiss slaughterhouse. Data on whole carcass condemnations (WCC) carried out at the same slaughterhouse over those years were extracted from the national database for meat inspection. We found that given the differences observed in the WCC and PCC time series, it is likely that both indicators respond to different health events in the population and that one cannot be substituted by the other. Because PCC recordings are promising for syndromic surveillance, the meat inspection database should be capable to record both WCC and PCC data in the future. However, a standardised list of reasons for PCC needs to be defined and used nationwide in all slaughterhouses.

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Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

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Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

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In the California Current System the spring transition from poleward to equatorward alongshore wind stress heralds the beginning of upwelling-favorable conditions. The phytoplankton response to this transition is investigated using 8 years ( 1998-2005) of daily, 4-km resolution, Sea-viewing Wide Field of view Sensor ( SeaWiFS) chlorophyll a concentration data. Cluster analysis of the chlorophyll a time series at each location is used to separate the inshore upwelling region from offshore and oligotrophic areas. An objective method for estimating the timing of bloom initiation is used to construct a map of the mean bloom start date. Interannual variability in bloom timing and magnitude is investigated in four regions: 45 degrees N - 50 degrees N, 40 degrees N - 45 degrees N, 35 degrees N - 40 degrees N and 20 degrees N - 35 degrees N. Daily satellite derived wind data ( QuikSCAT) allow the timing of the first episode of persistently upwelling favorable winds to be estimated. Bloom initiation generally coincides with the onset of upwelling winds ( +/- 15 days). South of similar to 35 degrees N, where winds are southward year-round, the timing of increased chlorophyll concentration corresponds closely to timing of the seasonal increase in upwelling intensity. A 1-D model and satellite derived photosynthetically available radiation data are used to estimate time series of depth- averaged irradiance. In the far north of the region (> 46 degrees N) light is shown to limit phytoplankton growth in early spring. In 2005 the spring bloom in the northern regions (> 35 degrees N) had a "false start''. A sharp increase in chl a in February quickly receded, and a sustained increase in biomass was delayed until July. We hypothesize that this resulted in a mismatch in timing of food availability to higher trophic levels.

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The California Current System encompasses a southward flowing current which is perturbed by ubiquitous mesoscale variability. The extent to which latitudinal patterns of physical variability are reflected in the distribution of biological parameters is poorly known. To investigate the latitudinal distribution of chlorophyll variance, a wavelet analysis is applied to nearly 9 years (October 1997 to July 2006) of 1-km-resolution Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll concentration data at 5-day resolution. Peaks in the latitudinal distribution of chlorophyll variance coincide with features of the coastal topography. Maxima in variance are located offshore of Vancouver Island and downstream of Heceta Bank, Cape Blanco, Point Arena, and possibly Point Conception. An analysis of dominant wavelengths in the chlorophyll data reveals a transfer of energy into smaller scales is generated in the vicinity of the coastal capes. The latitudinal distribution of variance in sea level anomaly corresponds closely to the chlorophyll variance in the nearshore region (<100 km offshore), suggesting that the same processes determine the distribution of both. Farther offshore, there is no correspondence between latitudinal patterns of sea level anomaly and chlorophyll variance. This likely represents a transition from physical to biological control of the phytoplankton distribution.

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This paper describes the creation of a GIS database index to the collection of historical aerial photographs of Connecticut housed in the Map and Geographic Information Center in the Homer Babbidge Library at the University of Connecticut. The index allows patrons to search for scanned aerial photograph images for a specific location across multiple years and to retrieve digital scans from the Library server. Procedures for scanning and georeferencing the images, preparing metadata for the images, and creating the GIS database index are described.

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Identifying accurate numbers of soldiers determined to be medically not ready after completing soldier readiness processing may help inform Army leadership about ongoing pressures on the military involved in long conflict with regular deployment. In Army soldiers screened using the SRP checklist for deployment, what is the prevalence of soldiers determined to be medically not ready? Study group. 15,289 soldiers screened at all 25 Army deployment platform sites with the eSRP checklist over a 4-month period (June 20, 2009 to October 20, 2009). The data included for analysis included age, rank, component, gender and final deployment medical readiness status from MEDPROS database. Methods.^ This information was compiled and univariate analysis using chi-square was conducted for each of the key variables by medical readiness status. Results. Descriptive epidemiology Of the total sample 1548 (9.7%) were female and 14319 (90.2%) were male. Enlisted soldiers made up 13,543 (88.6%) of the sample and officers 1,746 (11.4%). In the sample, 1533 (10.0%) were soldiers over the age of 40 and 13756 (90.0%) were age 18-40. Reserve, National Guard and Active Duty made up 1,931 (12.6%), 2,942 (19.2%) and 10,416 (68.1%) respectively. Univariate analysis. Overall 1226 (8.0%) of the soldiers screened were determined to be medically not ready for deployment. Biggest predictive factor was female gender OR (2.8; 2.57-3.28) p<0.001. Followed by enlisted rank OR (2.01; 1.60-2.53) p<0.001. Reserve component OR (1.33; 1.16-1.53) p<0.001 and Guard OR (0.37; 0.30-0.46) p<0.001. For age > 40 demonstrated OR (1.2; 1.09-1.50) p<0.003. Overall the results underscore there may be key demographic groups relating to medical readiness that can be targeted with programs and funding to improve overall military medical readiness.^

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Initiation of Myxococcus xanthus multicellular development requires both nutrient limitation and high cell density. The extracellular signal, A signal, which consists of a set of amino acids at specific concentrations, serves as a cell density signal in M. xanthus early development. A reporter gene, designated 4521, that requires both starvation and A signal for developmental expression was used to identify mutations in the signal transduction pathways. A group of point mutations located in the chromosomal sasB locus that bypasses both requirements was previously isolated. One of these point mutations, sasB7, was mapped to the sasS gene, which is predicted to encode a transmembrane histidine protein kinase required for normal development. SasS is a positive regulator of 4521 and a candidate A signal sensor. This dissertation continues the characterization of the sasB locus, focusing on the sasR gene and the functional relationship of SasS and SasR. ^ The sasR gene is located 2.2-kb downstream of sasS. It is predicted to encode an NtrC-like response regulator, which belongs to the family of sigma54 transcriptional activators. SasR is a positive regulator of 4521 gene and is required for normal development. The sasR mutant displays phenotypes similar to that of sasS mutant. Both SasS and SasR are required for the A-signal-dependent 4521 expression. Genetic epistasis analysis indicates that SasR functions downstream of SasS. Biochemical studies show that SasS has autokinase activity, and phosphorylated SasS is able to transfer its phosphate to SasR. We propose that SasS and SasR form a two-component signal transduction system in the A signal transduction pathway. ^ To search for the genes regulated by SasS and SasR, expression patterns of a group of developmental genes were compared in wild-type and sasS null mutant backgrounds. SasS and SasR were found to positively regulate sasN and 4521. The sasN gene was previously identified as a negative regulator of 4521, located at about 170-bp downstream of sasR. It is required for normal fruiting body development. Based on the above data, a regulatory network consisting of sasS, sasR, sasN, and 4521 is hypothesized, and the interactions of the components in this network can now be further studied. ^

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Much advancement has been made in recent years in field data assimilation, remote sensing and ecosystem modeling, yet our global view of phytoplankton biogeography beyond chlorophyll biomass is still a cursory taxonomic picture with vast areas of the open ocean requiring field validations. High performance liquid chromatography (HPLC) pigment data combined with inverse methods offer an advantage over many other phytoplankton quantification measures by way of providing an immediate perspective of the whole phytoplankton community in a sample as a function of chlorophyll biomass. Historically, such chemotaxonomic analysis has been conducted mainly at local spatial and temporal scales in the ocean. Here, we apply a widely tested inverse approach, CHEMTAX, to a global climatology of pigment observations from HPLC. This study marks the first systematic and objective global application of CHEMTAX, yielding a seasonal climatology comprised of ~1500 1°x1° global grid points of the major phytoplankton pigment types in the ocean characterizing cyanobacteria, haptophytes, chlorophytes, cryptophytes, dinoflagellates, and diatoms, with results validated against prior regional studies where possible. Key findings from this new global view of specific phytoplankton abundances from pigments are a) the large global proportion of marine haptophytes (comprising 32 ± 5% of total chlorophyll), whose biogeochemical functional roles are relatively unknown, and b) the contrasting spatial scales of complexity in global community structure that can be explained in part by regional oceanographic conditions. These publicly accessible results will guide future parameterizations of marine ecosystem models exploring the link between phytoplankton community structure and marine biogeochemical cycles.

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Pteropods are a group of holoplanktonic gastropods for which global biomass distribution patterns remain poorly resolved. The aim of this study was to collect and synthesize existing pteropod (Gymnosomata, Thecosomata and Pseudothecosomata) abundance and biomass data, in order to evaluate the global distribution of pteropod carbon biomass, with a particular emphasis on its seasonal, temporal and vertical patterns. We collected 25 902 data points from several online databases and a number of scientific articles. The biomass data has been gridded onto a 360 x 180° grid, with a vertical resolution of 33 WOA depth levels. Data has been converted to NetCDF format. Data were collected between 1951-2010, with sampling depths ranging from 0-1000 m. Pteropod biomass data was either extracted directly or derived through converting abundance to biomass with pteropod specific length to weight conversions. In the Northern Hemisphere (NH) the data were distributed evenly throughout the year, whereas sampling in the Southern Hemisphere was biased towards the austral summer months. 86% of all biomass values were located in the NH, most (42%) within the latitudinal band of 30-50° N. The range of global biomass values spanned over three orders of magnitude, with a mean and median biomass concentration of 8.2 mg C l-1 (SD = 61.4) and 0.25 mg C l-1, respectively for all data points, and with a mean of 9.1 mg C l-1 (SD = 64.8) and a median of 0.25 mg C l-1 for non-zero biomass values. The highest mean and median biomass concentrations were located in the NH between 40-50° S (mean biomass: 68.8 mg C l-1 (SD = 213.4) median biomass: 2.5 mg C l-1) while, in the SH, they were within the 70-80° S latitudinal band (mean: 10.5 mg C l-1 (SD = 38.8) and median: 0.2 mg C l-1). Biomass values were lowest in the equatorial regions. A broad range of biomass concentrations was observed at all depths, with the biomass peak located in the surface layer (0-25 m) and values generally decreasing with depth. However, biomass peaks were located at different depths in different ocean basins: 0-25 m depth in the N Atlantic, 50-100 m in the Pacific, 100-200 m in the Arctic, 200-500 m in the Brazilian region and >500 m in the Indo-Pacific region. Biomass in the NH was relatively invariant over the seasonal cycle, but more seasonally variable in the SH. The collected database provides a valuable tool for modellers for the study of ecosystem processes and global biogeochemical cycles.