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Mariussen E.,Norwegian Defence Research Establishment
Archives of Toxicology | Year: 2012

Perfluoroalkylated compounds (PFCs) are used in fire-fighting foams, treatment of clothes, carpets and leather products, and as lubricants, pesticides, in paints and medicine. Recent developments in chemical analysis have revealed that fluorinated compounds have become ubiquitously spread and are regarded as a potential threats to the environment. Due to the carbon-fluorine bond, which has a very high bond strength, these chemicals are extremely persistent towards degradation and some PFCs have a potential for bioaccumulation in organisms. Of particular concern has been the developmental toxicity of PFOS and PFOA, which has been manifested in rodent studies as high mortality of prenatally exposed newborn rats and mice within 24 h after delivery. The nervous system appears to be one of the most sensitive targets of environmental contaminants. The serious developmental effects of PFCs have lead to the upcoming of studies that have investigatedneurotoxic effects of these substances. In this review the major findings of the neurotoxicity of the main PFCs and their suggested mechanisms of action are presented. The neurotoxic effects are discussed in light of other toxic effects of PFCs to indicate the significance of PFCs as neurotoxicants. The main findings are that PFCs may induce neurobehavioral effects, particularly in developmentally exposed animals. The effects are, however, subtle and inconclusive and are often induced at concentrations where other toxic effects also are expected. Mechanistic studies have shown that PFCs may affect the thyroid system, influence the calcium homeostasis, protein kinase C, synaptic plasticity and cellular differentiation. Compared to other environmental toxicants the human blood levels of PFCs are high and of particular concern is that susceptible groups may be exposed to a cocktail of substances that in combination reach harmful concentrations. © Springer-Verlag 2012. Source


Solberg S.,Norwegian Forest And Landscape Institute | Astrup R.,Norwegian Forest And Landscape Institute | Breidenbach J.,Norwegian Forest And Landscape Institute | Nilsen B.,Norwegian Forest And Landscape Institute | Weydahl D.,Norwegian Defence Research Establishment
Remote Sensing of Environment | Year: 2013

There is a need for monitoring methods for forest volume, biomass and carbon based on satellite remote sensing. In the present study we tested interferometric X-band SAR (InSAR) from the Tandem-X mission. The aim of the study was to describe how accurate volume and biomass could be estimated from InSAR height and test whether the relationships were curvilinear or not. The study area was a spruce dominated forest in southeast Norway. We selected 28 stands in which we established 192 circular sample plots of 250m2, accurately positioned by a Differential Global Positioning System (dGPS). Plot level data on stem volume and aboveground biomass were derived from field inventory. Stem volume ranged from zero to 596m3/ha, and aboveground biomass up to 338t/ha. We generated 2 Digital Surface Models (DSMs) from InSAR processing of two co-registered, HH-polarized TanDEM-X image pairs - one ascending and one descending pair. We used a Digital Terrain Model (DTM) from airborne laser scanning (ALS) as a reference and derived a 10m×10m Canopy Height Model (CHM), or InSAR height model. We assigned each plot to the nearest 10m×10m InSAR height pixel. We applied a nonlinear, mixed model for the volume and biomass modeling, and from a full model we removed effects with a backward stepwise approach. InSAR height was proportional to volume and aboveground biomass, where a 1m increase in InSAR height corresponded to a volume increase of 23m3/ha and a biomass increase of 14t/ha. Root Mean Square Error (RMSE) values were 43-44% at the plot level and 19-20% at the stand level. © 2013 Elsevier Inc. Source


Olsen K.E.,Norwegian Defence Research Establishment | Woodbridge K.,University College London
IEEE Aerospace and Electronic Systems Magazine | Year: 2012

The performance of a mathematical processing scheme has been presented. The algorithm is inspired by the HRR approaches used in HRR radar systems on how to exploit multiple nonadjacent broadcast channels or bands in the PBR range correlation to achieve higher range resolution while maintaining Doppler resolution from relatively long integration times. The broadcast channels or bands are assumed to be from a single transmitter. The following problems have been addressed and solved [26]-[28], [31]: By using broadcast signals at different carrier frequencies, the target Doppler shift is different, and the proposed method takes this into account. By using time-varying waveforms (signals of opportunity, i.e., FM, DAB, DVB-T, or pseudonoise) in the range correlation, a time-varying result is achieved. If this becomes an issue, it should be countered by increasing the range correlation time. This might be achieved either by increasing the total CPI or by keeping the CPI constant and reducing the Doppler resolution. Combining multiple bands results in cochannel correlation, as well as cross-channel correlation. While only the former is sought, it is shown that the cross terms may be neglected due to their correlation properties with respect to each other. This is also helped by their destructive frequency component from the demodulation. Even though good individual correlation performances are achieved for single channels or bands, summing the correlation contributions for the different channels or bands might cause an out-of-phase summation that modulates the range correlation peak in a way that may cause erroneous range estimates to be made. The algorithm estimates a phase correction term that, once applied, makes all contributions in phase; thus, erroneous range estimates, as well as destructive summing of target responses, are avoided. © 1986-2012 IEEE. Source


Skauli T.,Norwegian Defence Research Establishment
Optics Express | Year: 2012

Coregistration errors in multi- and hyperspectral imaging sensors arise when the spatial sensitivity pattern differs between bands or when the spectral response varies across the field of view, potentially leading to large errors in the recorded image data. In imaging spectrometers, spectral and spatial offset errors are customarily specified as "smile" and "keystone" distortions. However these characteristics do not account for errors resulting from variations in point spread function shape or spectral bandwidth. This paper proposes improved metrics for coregistration error both in the spatial and spectral dimensions. The metrics are essentially the integrated difference between point spread functions. It is shown that these metrics correspond to an upper bound on the error in image data. The metrics enable estimation of actual data errors for a given image, and can be used as part of the merit function in optical design optimization, as well as for benchmarking of spectral image sensors. © 2012 Optical Society of America. Source


Moxnes J.F.,Norwegian Defence Research Establishment | Sandbakk O.,Norwegian University of Science and Technology
Theoretical Biology and Medical Modelling | Year: 2012

Background: Based on a literature review, the current study aimed to construct mathematical models of lactate production and removal in both muscles and blood during steady state and at varying intensities during whole-body exercise. In order to experimentally test the models in dynamic situations, a cross-country skier performed laboratory tests while treadmill roller skiing, from where work rate, aerobic power and blood lactate concentration were measured. A two-compartment simulation model for blood lactate production and removal was constructed. Results: The simulated and experimental data differed less than 0.5 mmol/L both during steady state and varying sub-maximal intensities. However, the simulation model for lactate removal after high exercise intensities seems to require further examination. Conclusions: Overall, the simulation models of lactate production and removal provide useful insight into the parameters that affect blood lactate response, and specifically how blood lactate concentration during practical training and testing in dynamical situations should be interpreted. © 2012 Moxnes and Sandbakk; licensee BioMed Central Ltd. Source

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