185 research outputs found

    Canadian Battlegroup Badges

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    Memories: A Photo Feature

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    The following is a small selection of the photographs I took during my 12 months with UNPROFOR. In the Spring of 1993, WO Stebbings and myself were the first Terrain Analysis Team sent to UNPROFOR Headquarters, Zagreb, Croatia. We were actually the first Terrain Analysis Team in the Former Yugoslavia. We were the geographic experts for the mission and worked out of Zagreb. The nature of the job allowed us unlimited access to the complete UNPROFOR Theatre of Operations, which included: Croatia, Bosnia and Herzegovina, parts of Serbia and the Former Yugoslav Republic of Macedonia

    Sarajevo: A Retrospective, 1993–2001

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    CH-147D Chinook Nose Art in Afghanistan

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    Nose art is an important component of any combat aircraft’s markings. Nose art not only helps to boost crew morale, esprit de corps and instill pride in the service, but it also adds a distinct character to the aircraft. Although the subject of current nose art has changed since the classic “pin up” girls of the 1940s, today’s artowrk is just as interesting and worthy of study. With the help of imagery taken in Afghanistan and first–hand study of the artwork, this article catalogues and explores the meaning of the artwork now used

    The Success of the Light Armoured Vehicle

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    In order to understand the purchase of military vehicles, one must understand the vehicle and where it falls in the evolution of vehicle procurement. This article, written in response to an earlier article in response to an earlier article in Canadian Military History by Frank Maas, examines the chronology and motivations behind the Canadian acquisition of wheeled armoured fighting vehicles

    Little Known Canadian Units: Royal Canadian Naval Beach Commando “W”

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    Landsat Data Continuity Mission Calibration and Validation

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    The primary payload for the Landsat Data Continuity Mission (LDCM) is the Operational Land Imager (OLI), being built by Ball Aerospace and Technologies, under contract to NASA. The OLI has spectral bands similar to the Landsat-7 ETM+, minus the thermal band and with two new bands, a 443 nm band and 1375 nm cirrus detection band. On-board calibration systems include two solar diffusers (routine and pristine), a shutter and three sets of internal lamps (routine, backup and pristine). Being a pushbroom opposed to a whiskbroom design of ETM+, the system poses new challenges for characterization and calibration, chief among them being the large focal plane with 75000+ detectors. A comprehensive characterization and calibration plan is in place for the instrument and the data throughout the mission including Ball, NASA and the United States Geological Survey, which will take over operations of LDCM after on-orbit commissioning. Driving radiometric calibration requirements for OLI data include radiance calibration to 5% uncertainty (1 q); reflectance calibration to 3% uncertainty (1 q) and relative (detector-to-detector) calibration to 0.5% (J (r). Driving geometric calibration requirements for OLI include bandto- band registration of 4.5 meters (90% confidence), absolute geodetic accuracy of 65 meters (90% CE) and relative geodetic accuracy of 25 meters (90% CE). Key spectral, spatial and radiometric characterization of the OLI will occur in thermal vacuum at Ball Aerospace. During commissioning the OLI will be characterized and calibrated using celestial (sun, moon, stars) sources and terrestrial sources. The USGS EROS ground processing system will incorporate an image assessment system similar to Landsat-7 for characterization and calibration. This system will have the added benefit that characterization data will be extracted as part of the normal image data processing, so that the characterization data available will be significantly larger than for Landsat-7 ETM+

    Seasonal changes in patterns of gene expression in avian song control brain regions.

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    This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Photoperiod and hormonal cues drive dramatic seasonal changes in structure and function of the avian song control system. Little is known, however, about the patterns of gene expression associated with seasonal changes. Here we address this issue by altering the hormonal and photoperiodic conditions in seasonally-breeding Gambel's white-crowned sparrows and extracting RNA from the telencephalic song control nuclei HVC and RA across multiple time points that capture different stages of growth and regression. We chose HVC and RA because while both nuclei change in volume across seasons, the cellular mechanisms underlying these changes differ. We thus hypothesized that different genes would be expressed between HVC and RA. We tested this by using the extracted RNA to perform a cDNA microarray hybridization developed by the SoNG initiative. We then validated these results using qRT-PCR. We found that 363 genes varied by more than 1.5 fold (>log(2) 0.585) in expression in HVC and/or RA. Supporting our hypothesis, only 59 of these 363 genes were found to vary in both nuclei, while 132 gene expression changes were HVC specific and 172 were RA specific. We then assigned many of these genes to functional categories relevant to the different mechanisms underlying seasonal change in HVC and RA, including neurogenesis, apoptosis, cell growth, dendrite arborization and axonal growth, angiogenesis, endocrinology, growth factors, and electrophysiology. This revealed categorical differences in the kinds of genes regulated in HVC and RA. These results show that different molecular programs underlie seasonal changes in HVC and RA, and that gene expression is time specific across different reproductive conditions. Our results provide insights into the complex molecular pathways that underlie adult neural plasticity

    Computational cancer biology: education is a natural key to many locks

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    BACKGROUND: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner. DISCUSSION: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research. SUMMARY: Here we argue that this imbalance, favoring ’wet lab-based activities’, will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization

    Advanced Land Imager Assessment System

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    The Advanced Land Imager Assessment System (ALIAS) supports radiometric and geometric image processing for the Advanced Land Imager (ALI) instrument onboard NASA s Earth Observing-1 (EO-1) satellite. ALIAS consists of two processing subsystems for radiometric and geometric processing of the ALI s multispectral imagery. The radiometric processing subsystem characterizes and corrects, where possible, radiometric qualities including: coherent, impulse; and random noise; signal-to-noise ratios (SNRs); detector operability; gain; bias; saturation levels; striping and banding; and the stability of detector performance. The geometric processing subsystem and analysis capabilities support sensor alignment calibrations, sensor chip assembly (SCA)-to-SCA alignments and band-to-band alignment; and perform geodetic accuracy assessments, modulation transfer function (MTF) characterizations, and image-to-image characterizations. ALIAS also characterizes and corrects band-toband registration, and performs systematic precision and terrain correction of ALI images. This system can geometrically correct, and automatically mosaic, the SCA image strips into a seamless, map-projected image. This system provides a large database, which enables bulk trending for all ALI image data and significant instrument telemetry. Bulk trending consists of two functions: Housekeeping Processing and Bulk Radiometric Processing. The Housekeeping function pulls telemetry and temperature information from the instrument housekeeping files and writes this information to a database for trending. The Bulk Radiometric Processing function writes statistical information from the dark data acquired before and after the Earth imagery and the lamp data to the database for trending. This allows for multi-scene statistical analyses
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