Wavelength Dependence of Raman Enhancement from Gold Nanorod Arrays: Quantitative Experiment and Modeling of a Hot Spot Dominated System

Surface-enhanced Raman scattering (SERS) spectra from molecules adsorbed on the surface of vertically aligned gold nanorod arrays exhibit a variation in enhancement factor (EF) as a function of excitation wavelength that displays little correlation with the elastic optical properties of the surface. The key to understanding this lack of correlation and to obtaining agreement between experimental and calculated EF spectra lies with consideration of randomly distributed, sub-10 nm gaps between nanorods forming the substrate. Intense fields in these enhancement “hot spots” make a dominant contribution to the Raman scattering and have a very different spectral profile to that of the elastic optical response. Detailed modeling of the electric field enhancement at both excitation and scattering wavelengths was used to quantitatively predict both the spectral profile and the magnitude of the observed EF.

Moving Object Scanning Apparatus and Method

Apparatus for scanning a moving object includes a visible waveband sensor oriented to collect a series of images of the object as it passes through a field of view. An image processor uses the series of images to form a composite image. The image processor stores image pixel data for a current image and predecessor image in the series. It uses information in the current image and its predecessor to analyse images and derive likelihood measures indicating probabilities that current image pixels correspond to parts of the object. The image processor estimates motion between the current image and its predecessor from likelihood weighted pixels. It generates the composite image from frames positioned according to respective estimates of object image motion. Image motion may alternatively be detected be a speed sensor such as Doppler radar sensing object motion directly and providing image timing signals

Animal foraging from an individual perspective: an object orientated model

A model system, HOOFS (Hierarchical Object Orientated Foraging Simulator), has been developed to study foraging by animals in a complex environment. The model is implemented using an individual-based object-orientated structure. Different species of animals inherit their general properties from a generic animal object which inherits from the basic dynamic object class. Each dynamic object is a separate program thread under the control of a central scheduler. The environment is described as a map of small hexagonal patches, each with their own level of resources and a patch-specific rate of resource replenishment. Each group of seven patches (0th order) is grouped into a Ist order super-patch with seven nth order super-patches making up a n + 1th order super-patch for n up to a specified value. At any time each animal is associated with a single patch. Patch choice is made by combining the information on the resources available within different order patches and super-patches along with information on the spatial location of other animals. The degree of sociality of an animal is defined in terms of optimal spacing from other animals and by the weighting of patch choice based on social factors relative to that based on food availability. Information, available to each animal, about patch resources diminishes with distance from that patch. The model has been used to demonstrate that social interactions can constrain patch choice and result in a short-term reduction of intake and a greater degree of variability in the level of resources in patches. We used the model to show that the effect of this variability on the animal's intake depends on the pattern of patch replenishment. (C) 1998 Elsevier Science B.V. All rights reserved.</p>

Modelling 3D camera movement for vibration characterisation and multiple object identification with application to lighting assessment

Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.

A Bayesian framework for age modeling of radiocarbon-dated peat deposits: Case studies from the Netherlands

Recently, Bayesian statistical software has been developed for age-depth modeling (wiggle-match dating) of sequences of densely spaced radiocarbon dates from peat cores. The method is described in non-statistical terms, and is compared with an alternative method of chronological ordering of 14C dates. Case studies include the dating of the start of agriculture in the northeastern part of the Netherlands, and of a possible Hekla-3 tephra layer in the same country. We discuss future enhancements in Bayesian age modeling.

MALTS: A Tool to Simulate Lorentz Transmission Electron Microscopy From Micromagnetic Simulations

Here we describe the development of the MALTS software which is a generalized tool that simulates Lorentz Transmission Electron Microscopy (LTEM) contrast of magnetic nanostructures. Complex magnetic nanostructures typically have multiple stable domain structures. MALTS works in conjunction with the open access micromagnetic software Object Oriented Micromagnetic Framework or MuMax. Magnetically stable trial magnetization states of the object of interest are input into MALTS and simulated LTEM images are output. MALTS computes the magnetic and electric phases accrued by the transmitted electrons via the Aharonov-Bohm expressions. Transfer and envelope functions are used to simulate the progression of the electron wave through the microscope lenses. The final contrast image due to these effects is determined by Fourier Optics. Similar approaches have been used previously for simulations of specific cases of LTEM contrast. The novelty here is the integration with micromagnetic codes via a simple user interface enabling the computation of the contrast from any structure. The output from MALTS is in good agreement with both experimental data and published LTEM simulations. A widely-available generalized code for the analysis of Lorentz contrast is a much needed step towards the use of LTEM as a standardized laboratory technique.

Weathering rinds as mirror images of palaeosols: Examples from the Western Alps with correlation to Antarctica and Mars

Weathering rinds have been used for decades as relative age indicators to differentiate glacial deposits in long Quaternary sequences, but only recently has it been shown that rinds contain long and extensive palaeoenvironmental records that often extend far beyond mere repositories of chemical weathering on both Earth and Mars. When compared with associated palaeosols in deposits of the same age, rinds often carry a zonal weathering record that can be correlated with palaeosol horizon characteristics, with respect to both abiotic and biotic parameters. As demonstrated with examples from the French and Italian Alps, rinds in coarse clastic sediment contain weathering zones that correlate closely with horizon development in associated palaeosols of presumed Late Glacial age. In addition to weathering histories in both rinds and palaeosols, considerable evidence exists to indicate that the black mat impact (12.8 ka) reached the European Alps, a connection with the Younger Dryas readvance supported by both mineral and chemical composition. Preliminary metagenomic microbial analysis using density gradient gel electrophoresis suggests that the eubacterial microbial population found in at least one Ah palaeosol horizon associated with a rind impact site is different from that in other Late Glacial and Younger Dryas surface palaeosol horizons. © 2013 The Geological Society of London.

The Type IIb Supernova 2011dh from a Supergiant Progenitor

A set of hydrodynamical models based on stellar evolutionary progenitors is used to study the nature of SN 2011dh. Our modeling suggests that a large progenitor star ---with R ~200 Rsun---, is needed to reproduce the early light curve of SN 2011dh. This is consistent with the suggestion that the yellow super-giant star detected at the location of the SN in deep pre-explosion images is the progenitor star. From the main peak of the bolometric light curve and expansion velocities we constrain the mass of the ejecta to be ~2 Msun, the explosion energy to be E= 6-10 x 10^50 erg, and the 56Ni mass to be approximately 0.06 Msun. The progenitor star was composed of a helium core of 3 to 4 Msun and a thin hydrogen-rich envelope of ~0.1 M_sun with a main sequence mass estimated to be in the range of 12--15 Msun. Our models rule out progenitors with helium-core masses larger than 8 Msun, which correspond to M_ZAMS > 25 Msun. This suggests that a single star evolutionary scenario for SN 2011dh is unlikely.

Modeling target bulk heating resulting from ultra-intense short pulse laser irradiation of solid density targets

Isochoric heating of solid-density matter up to a few tens of eV is of interest for investigating astrophysical or inertial fusion scenarios. Such ultra-fast heating can be achieved via the energy deposition of short-pulse laser generated electrons. Here, we report on experimental measurements of this process by means of time-and space-resolved optical interferometry. Our results are found in reasonable agreement with a simple numerical model of fast electron-induced heating. (C) 2013 AIP Publishing LLC.

The progenitor mass of the Type IIP supernova SN 2004et from late-time spectral modeling

SN 2004et is one of the nearest and best-observed Type IIP supernovae, with a progenitor detection as well as good photometric and spectroscopic observational coverage well into the nebular phase. Based on nucleosynthesis from stellar evolution/explosion models we apply spectral modeling to analyze its 140-700 day evolution from ultraviolet to mid-infrared. We find a M_ZAMS= 15 Msun progenitor star (with an oxygen mass of 0.8 Msun) to satisfactorily reproduce [O I] 6300, 6364 {\AA} and other emission lines of carbon, sodium, magnesium, and silicon, while 12 Msun and 19 Msun models under- and overproduce most of these lines, respectively. This result is in fair agreement with the mass derived from the progenitor detection, but in disagreement with hydrodynamical modeling of the early-time light curve. From modeling of the mid-infrared iron-group emission lines, we determine the density of the "Ni-bubble" to rho(t) = 7E-14*(t/100d)^-3 g cm^-3, corresponding to a filling factor of f = 0.15 in the metal core region (V = 1800 km/s). We also confirm that silicate dust, CO, and SiO emission are all present in the spectra.

Toward Unconstrained Ear Recognition From Two-Dimensional Images

Ear recognition, as a biometric, has several advantages. In particular, ears can be measured remotely and are also relatively static in size and structure for each individual. Unfortunately, at present, good recognition rates require controlled conditions. For commercial use, these systems need to be much more robust. In particular, ears have to be recognized from different angles ( poses), under different lighting conditions, and with different cameras. It must also be possible to distinguish ears from background clutter and identify them when partly occluded by hair, hats, or other objects. The purpose of this paper is to suggest how progress toward such robustness might be achieved through a technique that improves ear registration. The approach focuses on 2-D images, treating the ear as a planar surface that is registered to a gallery using a homography transform calculated from scale-invariant feature-transform feature matches. The feature matches reduce the gallery size and enable a precise ranking using a simple 2-D distance algorithm. Analysis on a range of data sets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees, and up to 18% occlusion. In addition, recognition remains accurate with masked ear images as small as 20 x 35 pixels.