Image processing for smart browsing of ocean colour data products and subsequent incorporation into a multi-modal sensing framework

Ocean colour is defined as the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments and coloured dissolved organic material and so water colour can provide valuable information on coastal ecosystems. The ‘Ocean Colour project’ collects data from various satellites (e.g. MERIS, MODIS) and makes this data available online. One method of searching the Ocean Colour project data is to visually browse level 1 and level 2 data. Users can search via location (regions), time and data type. They are presented with images which cover chlorophyll, quasi-true colour and sea surface temperature (11 μ) and links to the source data. However it is often preferable for users to search such a complex and large dataset by event and analyse the distribution of colour in an image before examination of the source data. This will allow users to browse and search ocean colour data more efficiently and to include this information more seamlessly into a framework that incorporates sensor information from a variety of modalities. This paper presents a system for more efficient management and analysis of ocean colour data and suggests how this information can be incorporated into a multi-modal sensing framework for a smarter, more adaptive environmental sensor network

Image processing for smarter browsing of ocean color data products: investigating algal blooms

Remote sensing technology continues to play a significant role in the understanding of our environment and the investigation of the Earth. Ocean color is the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments, and colored dissolved organic material and so can provide valuable information on coastal ecosystems. We propose to make the browsing of Ocean Color data more efficient for users by using image processing techniques to extract useful information which can be accessible through browser searching. Image processing is applied to chlorophyll and sea surface temperature images. The automatic image processing of the visual level 1 and level 2 data allow us to investigate the occurrence of algal blooms. Images with colors in a certain range (red, orange etc.) are used to address possible algal blooms and allow us to examine the seasonal variation of algal blooms in Europe (around Ireland and in the Baltic Sea). Yearly seasonal variation of algal blooms in Europe based on image processing for smarting browsing of Ocean Color are presented

Quantum Density Fluctuations in Classical Liquids

We discuss the density fluctuations of a fluid due to zero point motion. These can be regarded as density fluctuations in the phonon vacuum state. We assume a linear dispersion relation with a fixed speed of sound and calculate the density correlation function. We note that this function has the same form as the correlation function for the time derivative of a relativistic massless scalar field, but with the speed of light replaced by the speed of sound. As a result, the study of density fluctuations in a fluid can be a useful analog model for better understanding fluctuations in relativistic quantum field theory. We next calculate the differential cross section for light scattering by the zero point density fluctuations, and find a result proportional to the fifth power of the light frequency. This can be understood as the product of fourth power dependence of the usual Rayleigh cross section with the linear frequency dependence of the spectrum of zero point density fluctuations. We give some estimates of the relative magnitude of this effect compared to the scattering by thermal density fluctuations, and find that it can be of order 0.5% for water at room temperature and optical frequencies. This relative magnitude is proportional to frequency and inversely proportional to temperature. Although the scattering by zero point density fluctuation is small, it may be observable.Comment: 7 page

Environmental factors influence both abundance and genetic diversity in a widespread bird species.

Genetic diversity is one of the key evolutionary variables that correlate with population size, being of critical importance for population viability and the persistence of species. Genetic diversity can also have important ecological consequences within populations, and in turn, ecological factors may drive patterns of genetic diversity. However, the relationship between the genetic diversity of a population and how this interacts with ecological processes has so far only been investigated in a few studies. Here, we investigate the link between ecological factors, local population size, and allelic diversity, using a field study of a common bird species, the house sparrow (Passer domesticus). We studied sparrows outside the breeding season in a confined small valley dominated by dispersed farms and small-scale agriculture in southern France. Population surveys at 36 locations revealed that sparrows were more abundant in locations with high food availability. We then captured and genotyped 891 house sparrows at 10 microsatellite loci from a subset of these locations (N = 12). Population genetic analyses revealed weak genetic structure, where each locality represented a distinct substructure within the study area. We found that food availability was the main factor among others tested to influence the genetic structure between locations. These results suggest that ecological factors can have strong impacts on both population size per se and intrapopulation genetic variation even at a small scale. On a more general level, our data indicate that a patchy environment and low dispersal rate can result in fine-scale patterns of genetic diversity. Given the importance of genetic diversity for population viability, combining ecological and genetic data can help to identify factors limiting population size and determine the conservation potential of populations

Optical BCS conductivity at imaginary frequencies and dispersion energies of superconductors

We present an efficient expression for the analytic continuation to arbitrary complex frequencies of the complex optical and AC conductivity of a homogeneous superconductor with arbitrary mean free path. Knowledge of this quantity is fundamental in the calculation of thermodynamic potentials and dispersion energies involving type-I superconducting bodies. When considered for imaginary frequencies, our formula evaluates faster than previous schemes involving Kramers--Kronig transforms. A number of applications illustrates its efficiency: a simplified low-frequency expansion of the conductivity, the electromagnetic bulk self-energy due to longitudinal plasma oscillations, and the Casimir free energy of a superconducting cavity.Comment: 20 pages, 7 figures, calculation of Casimir energy adde

Views from the coalface: chemo-sensors, sensor networks and the semantic sensor web

Currently millions of sensors are being deployed in sensor networks across the world. These networks generate vast quantities of heterogeneous data across various levels of spatial and temporal granularity. Sensors range from single-point in situ sensors to remote satellite sensors which can cover the globe. The semantic sensor web in principle should allow for the unification of the web with the real-word. In this position paper, we discuss the major challenges to this unification from the perspective of sensor developers (especially chemo-sensors) and integrating sensors data in real-world deployments. These challenges include: (1) identifying the quality of the data; (2) heterogeneity of data sources and data transport methods; (3) integrating data streams from different sources and modalities (esp. contextual information), and (4) pushing intelligence to the sensor level

‘‘Lozenge’’ contour plots in scattering from polymer networks

We present a consistent explanation for the appearance of “lozenge” shapes in contour plots of the two dimensional scattering intensity from stretched polymer networks. By explicitly averaging over quenched variables in a tube model, we show that lozenge patterns arise as a result of chain material that is not directly deformed by the stretch. We obtain excellent agreement with experimental data

Understanding wavelength scaling in 19-cell core hollow-core photonic bandgap fibers

First experimental wavelength scaling in 19-cell core HC-PBGF indicates that the minimum loss waveband occurs at longer wavelengths than previously predicted. Record low loss (2.5dB/km) fibers operating around 2µm and gas-purging experiments are also reported

Long-Term and Global Tradeoffs between Bio-Energy, Feed, and Food

Projections of U.S. ethanol production and its impacts on planted acreage, crop prices, livestock production and prices, trade, and retail food costs are presented under the assumption that current tax credits and trade policies are maintained. The projections were made using a multi-product, multi-country deterministic partial equilibrium model. The impacts of higher oil prices, a drought combined with an ethanol mandate, and removal of land from the Conservation Reserve Program (CRP) relative to baseline projections are also presented. The results indicate that expanded U.S. ethanol production will cause long-run crop prices to increase. In response to higher feed costs, livestock farmgate prices will increase enough to cover the feed cost increases. Retail meat, egg, and dairy prices will also increase. If oil prices are permanently $10-per-barrel higher than assumed in the baseline projections, U.S. ethanol will expand significantly. The magnitude of the expansion will depend on the future makeup of the U.S. automobile fleet. If sufficient demand for E-85 from flex-fuel vehicles is available, corn-based ethanol production is projected to increase to over 30 billion gallons per year with the higher oil prices. The direct effect of higher feed costs is that U.S. food prices would increase by a minimum of 1.1% over baseline levels. Results of a model of a 1988-type drought combined with a large mandate for continued ethanol production show sharply higher crop prices, a drop in livestock production, and higher food prices. Corn exports would drop significantly, and feed costs would rise. Wheat feed use would rise sharply. Taking additional land out of the CRP would lower crop prices in the short run. But because long-run corn prices are determined by ethanol prices and not by corn acreage, the long-run impacts on commodity prices and food prices of a smaller CRP are modest. Cellulosic ethanol from switchgrass and biodiesel from soybeans do not become economically viable in the Corn Belt under any of the scenarios. This is so because high energy costs that increase the prices of biodiesel and switchgrass ethanol also increase the price of corn-based ethanol. So long as producers can choose between soybeans for biodiesel, switchgrass for ethanol, and corn for ethanol, they will choose to grow corn. Cellulosic ethanol from corn stover does not enter into any scenario because of the high cost of collecting and transporting corn stover over the large distances required to supply a commercial-sized ethanol facility.biofuels, corn acreage, crop prices, ethanol production, food prices, Resource /Energy Economics and Policy,