Calibration of the visible and near-infrared channels of the NOAA-9 AVHRR using high-altitude aircraft measurements from August 1985 and October 1986

Visible and near infrared wavelength sensors mounted on operational satellites now in use do not have onboard absolute calibration devices. One means of establishing an in-orbit calibration for a satellite sensor is to make simultaneous measurement of a bright, relatively uniform scene along the satellite view vector from a calibrated instrument on board a high altitude aircraft. Herein, aircraft data were recorded over White Sands, New Mexico at satellite overpass time. Comparison of the coincident aircraft and orbiting satellite data for the visible and near infrared wavelength channels of the NOAA-9 Advanced Very High Resolution Radiometer shows that the calibration of the visible channel was unchanged from prelaunch values, but that the near infrared channel has degraded 6 percent by Aug. 1985. By Oct. 1986 the visible channel had degraded 13 percent and the near infrared channel had degraded 19 percent

Visible and near-infrared channel calibration of the GOES-6 VISSR using high-altitude aircraft measurements

Present and future visible and near-infrared wavelength sensors mounted on operational satellites do not have on-board absolute calibration devices. One means of establishing an in-orbit calibration for a satellite sensor is to make simultaneous measurements of a bright, relatively uniform scene along the satellite view vector from a calibrated instrument on board a high altitude aircraft. Aircraft data were recorded over White Sands, New Mexico, and the coincident aircraft and orbiting satellite data is compared for the visible and near-infrared wavelength channel of the GOES-6 Visible Infrared Spin-Scan Radiometer

Factors affecting the identification of phytoplankton groups by means of remote sensing

A literature review was conducted on the state of the art as to whether or not information about communities and populations of phytoplankton in aquatic environments can be derived by remote sensing. In order to arrive at this goal, the spectral characteristics of various types of phytoplankton were compared to determine first, whether there are characteristic differences in pigmentation among the types and second, whether such differences can be detected remotely. In addition to the literature review, an extensive, but not exhaustive, annotated bibliography of the literature that bears on these questions is included as an appendix, since it constitutes a convenient resource for anyone wishing an overview of the field of ocean color. The review found some progress has already been made in remote sensing of assemblages such as coccolithophorid blooms, mats of cyanobacteria, and red tides. Much more information about the composition of algal groups is potentially available by remote sensing particularly in water bodies having higher phytoplankton concentrations, but it will be necessary to develop the remote sensing techniques required for working in so-called Case 2 waters. It is also clear that none of the satellite sensors presently available or soon to be launched is ideal from the point of view of what we might wish to know; it would seem wise to pursue instruments with the planned characteristics of the Moderate Resolution Imaging Spectrometer-Tilt (MODIS-T) or Medium Resolution Imaging Spectrometer (MERIS)

Using remotely sensed night-time light as a proxy for poverty in Africa

BACKGROUND: Population health is linked closely to poverty. To assess the effectiveness of health interventions it is critical to monitor the spatial and temporal changes in the health indicators of populations and outcomes across varying levels of poverty. Existing measures of poverty based on income, consumption or assets are difficult to compare across geographic settings and are expensive to construct. Remotely sensed data on artificial night time lights (NTL) have been shown to correlate with gross domestic product in developed countries. METHODS: Using national household survey data, principal component analysis was used to compute asset-based poverty indices from aggregated household asset variables at the Administrative 1 level (n = 338) in 37 countries in Africa. Using geographical information systems, mean brightness of and distance to NTL pixels and proportion of area covered by NTL were computed for each Administrative1 polygon. Correlations and agreement of asset-based indices and the three NTL metrics were then examined in both continuous and ordinal forms. RESULTS: At the Administrative 1 level all the NTL metrics distinguished between the most poor and least poor quintiles with greater precision compared to intermediate quintiles. The mean brightness of NTL, however, had the highest correlation coefficient with the asset-based wealth index in continuous (Pearson correlation = 0.64, p < 0.01) and ordinal (Spearman correlation = 0.79, p < 0.01; Kappa = 0.64) forms. CONCLUSION: Metrics of the brightness of NTL data offer a robust and inexpensive alternative to asset-based poverty indices derived from survey data at the Administrative 1 level in Africa. These could be used to explore economic inequity in health outcomes and access to health interventions at sub-national levels where household assets data are not available at the required resolution

Association of Ficolin-3 with Severity and Outcome of Chronic Heart Failure

BACKGROUND: Inflammatory mechanisms involving complement activation has been shown to take part in the pathophysiology of congestive heart failure, but the initiating mechanisms are unknown. We hypothesized that the main initiator molecules of the lectin complement pathway mannose-binding lectin (MBL), ficolin-2 and ficolin-3 were related to disease severity and outcome in chronic heart failure. METHODS AND RESULTS: MBL, ficolin-2 and ficolin-3 plasma concentrations were determined in two consecutive cohorts comprising 190 patients from Hungary and 183 patients from Norway as well as controls. Disease severity and clinical parameters were determined at baseline, and all-cause mortality was registered after 5-years follow-up. In univariate analysis a low level of ficolin-3, but not that of MBL or ficolin-2, was significantly associated with advanced heart failure (New York Heart Association Class IV, p<0.001 for both cohorts) and showed inverse correlation with B- type natriuretic peptide (BNP) levels (r = -0.609, p<0.001 and r = -0.467, p<0.001, respectively). In multivariable Cox regression analysis, adjusted for age, gender and BNP, decreased plasma ficolin-3 was a significant predictor of mortality (HR 1.368, 95% CI 1.052-6.210; and HR 1.426, 95% CI 1.013-2.008, respectively). Low ficolin-3 levels were associated with increased complement activation product C3a and correspondingly decreased concentrations of complement factor C3. CONCLUSIONS: This study provides evidence for an association of low ficolin-3 levels with advanced heart failure. Concordant results from two cohorts show that low levels of ficolin-3 are associated with advanced heart failure and outcome. The decrease of ficolin-3 was associated with increased complement activation

Social change and the family: Comparative perspectives from the west, China, and South Asia

This paper examines the influence of social and economic change on family structure and relationships: How do such economic and social transformations as industrialization, urbanization, demographic change, the expansion of education, and the long-term growth of income influence the family? We take a comparative and historical approach, reviewing the experiences of three major sociocultural regions: the West, China, and South Asia. Many of the changes that have occurred in family life have been remarkably similar in the three settings—the separation of the workplace from the home, increased training of children in nonfamilial institutions, the development of living arrangements outside the family household, increased access of children to financial and other productive resources, and increased participation by children in the selection of a mate. While the similarities of family change in diverse cultural settings are striking, specific aspects of change have varied across settings because of significant pre-existing differences in family structure, residential patterns of marriage, autonomy of children, and the role of marriage within kinship systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45661/1/11206_2005_Article_BF01124383.pd

Influence of gene expression on hardness in wheat

Puroindoline (Pina and Pinb) genes control grain texture or hardness in wheat. Wild-type/ soft alleles lead to softer grain while a mutation in one or both of these genes results in a hard grain. Variation in hardness in genotypes with identical Pin alleles (wild-type or mutant) is known but the molecular basis of this is not known. We now report the identification of wheat genotypes with hard grain texture and wild-type/soft Pin alleles indicating that hardness in wheat may be controlled by factors other than mutations in the coding region of the Pin genes. RNA-Seq analysis was used to determine the variation in the transcriptome of developing grains of thirty three diverse wheat genotypes including hard (mutant Pin) and soft (wild type) and those that were hard without having Pin mutations. This defined the role of pin gene expression and identified other candidate genes associated with hardness. Pina was not expressed in hard wheat with a mutation in the Pina gene. The ratio of Pina to Pinb expression was generally lower in the hard non mutant genotypes. Hardness may be associated with differences in Pin expression and other factors and is not simply associated with mutations in the PIN protein coding sequences

Expression of the <i>Pina</i> and <i>Pinb</i> genes in developing seeds of several wheat genotypes.

<p>a,b gene expression data at 14 and 30 days post anthesis (dpa), respectively; RPKM, reads per kilo base per million mapped reads. Details in brackets after genotype names on the X-axis indicates grain hardness index and endosperm texture of genotypes classified as hard (H) or soft (S) wheats. Genotypes with HI above 50 were classified as Hard. Wheat genotypes in each group are arranged left to right with respect to increasing hardness index. Boxes on the top indicate <i>Pin</i> alleles present in the genotypes. cDNA prepared from RNA extracted from developing wheat seeds at 14 DPA, was subjected to next generation sequencing. RNA-seq analysis was undertaken using CLC Genomic Workbench V8 to determine gene expression of <i>Pina</i> and <i>Pinb</i>. The star symbol indicates data not available.</p