Ray-optical refraction with confocal lenslet arrays

Two parallel lenslet arrays with focal lengths f1 and f2 that share a common focal plane (that is, which are separated by a distance f1+f2) can refract transmitted light rays according to Snell's law, but with the 'sin's replaced with 'tan's. This is the case for a limited range of input angles and other conditions. Such confocal lenslet arrays can therefore simulate the interface between optical media with different refractive indices, n1 and n2, whereby the ratio η=-f2/f1 plays the role of the refractive-index ratio n2/n1. Suitable choices of focal lengths enable positive and negative refraction. In contrast to Snell's law, which leads to nontrivial geometric imaging by a planar refractive-index interface only for the special case of n1=±n2, the modified refraction law leads to geometric imaging by planar confocal lenslet arrays for any value of η. We illustrate some of the properties of confocal lenslet arrays with images rendered using ray-tracing software

Conformal Invariance and Shape-Dependent Conductance of Graphene Samples

For a sample of an arbitrary shape, the dependence of its conductance on the longitudinal and Hall conductivity is identical to that of a rectangle. We use analytic results for a conducting rectangle, combined with the semicircle model for transport coefficients, to study properties of the monolayer and bilayer graphene. A conductance plateau centered at the neutrality point, predicted for square geometry, is in agreement with recent experiments. For rectangular geometry, the conductance exhibits maxima at the densities of compressible quantum Hall states for wide samples, and minima for narrow samples. The positions and relative sizes of these features are different in the monolayer and bilayer cases, indicating that the conductance can be used as a tool for sample diagnostic.Comment: 9 pages, 6 figure

The roles of motivation and ability in controlling the consequences of stereotype suppression

Two experiments investigated the conditions under which previously suppressed stereotypes are applied in impression formation. In Experiment 1, the extent to which a previously suppressed racial stereotype influenced subsequent impressions depended on the race of the target who was subsequently encountered. Whereas impressions of race-unspecified targets were assimilated to the stereotype following its suppression, no such effects were observed when the target belonged to the racial group whose stereotype had been initially suppressed. These results demonstrate that when perceivers are motivated to avoid stereo-typing individuals, the influence of a stereotype that has been previously activated through suppression is minimized. Experiment 2 demonstrated that these processing goals effectively reduce the impact of suppression-activated stereotypes only when perceivers have sufficient capacity to enact the goals. These results suggest that both sufficient motivation and capacity are necessary to prevent heightened stereotyping following stereotype suppression

Wavelength-scale stationary-wave integrated Fourier-transform spectrometry

Spectrometry is a general physical-analysis approach for investigating light-matter interactions. However, the complex designs of existing spectrometers render them resistant to simplification and miniaturization, both of which are vital for applications in micro- and nanotechnology and which are now undergoing intensive research. Stationary-wave integrated Fourier-transform spectrometry (SWIFTS)-an approach based on direct intensity detection of a standing wave resulting from either reflection (as in the principle of colour photography by Gabriel Lippmann) or counterpropagative interference phenomenon-is expected to be able to overcome this drawback. Here, we present a SWIFTS-based spectrometer relying on an original optical near-field detection method in which optical nanoprobes are used to sample directly the evanescent standing wave in the waveguide. Combined with integrated optics, we report a way of reducing the volume of the spectrometer to a few hundreds of cubic wavelengths. This is the first attempt, using SWIFTS, to produce a very small integrated one-dimensional spectrometer suitable for applications where microspectrometers are essential

A hybrid nonlinear-discriminant analysis feature projection technique

Feature set dimensionality reduction via Discriminant Analysis (DA) is one of the most sought after approaches in many applications. In this paper, a novel nonlinear DA technique is presented based on a hybrid of Artificial Neural Networks (ANN) and the Uncorrelated Linear Discriminant Analysis (ULDA). Although dimensionality reduction via ULDA can present a set of statistically uncorrelated features, but similar to the existing DA's it assumes that the original data set is linearly separable, which is not the case with most real world problems. In order to overcome this problem, a one layer feed-forward ANN trained with a Differential Evolution (DE) optimization technique is combined with ULDA to implement a nonlinear feature projection technique. This combination acts as nonlinear discriminant analysis. The proposed approach is validated on a Brain Computer Interface (BCI) problem and compared with other techniques. © 2008 Springer Berlin Heidelberg

Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems

Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which they are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person’s intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy

Dissolved noble gases and stable isotopes as tracers of preferential fluid flow along faults in the Lower Rhine Embayment, Germany

Groundwater in shallow unconsolidated sedimentary aquifers close to the Bornheim fault in the Lower Rhine Embayment (LRE), Germany, has relatively low δ2H and δ18O values in comparison to regional modern groundwater recharge, and 4He concentrations up to 1.7 × 10−4 cm3 (STP) g–1 ± 2.2 % which is approximately four orders of magnitude higher than expected due to solubility equilibrium with the atmosphere. Groundwater age dating based on estimated in situ production and terrigenic flux of helium provides a groundwater residence time of ∼107 years. Although fluid exchange between the deep basal aquifer system and the upper aquifer layers is generally impeded by confining clay layers and lignite, this study’s geochemical data suggest, for the first time, that deep circulating fluids penetrate shallow aquifers in the locality of fault zones, implying  that sub-vertical fluid flow occurs along faults in the LRE. However, large hydraulic-head gradients observed across many faults suggest that they act as barriers to lateral groundwater flow. Therefore, the geochemical data reported here also substantiate a conduit-barrier model of fault-zone hydrogeology in unconsolidated sedimentary deposits, as well as corroborating the concept that faults in unconsolidated aquifer systems can act as loci for hydraulic connectivity between deep and shallow aquifers. The implications of fluid flow along faults in sedimentary basins worldwide are far reaching and of particular concern for carbon capture and storage (CCS) programmes, impacts of deep shale gas recovery for shallow groundwater aquifers, and nuclear waste storage sites where fault zones could act as potential leakage pathways for hazardous fluids

Current research into brain barriers and the delivery of therapeutics for neurological diseases: a report on CNS barrier congress London, UK, 2017.

This is a report on the CNS barrier congress held in London, UK, March 22-23rd 2017 and sponsored by Kisaco Research Ltd. The two 1-day sessions were chaired by John Greenwood and Margareta Hammarlund-Udenaes, respectively, and each session ended with a discussion led by the chair. Speakers consisted of invited academic researchers studying the brain barriers in relation to neurological diseases and industry researchers studying new methods to deliver therapeutics to treat neurological diseases. We include here brief reports from the speakers

First principles theory of inelastic currents in a scanning tunneling microscope

A first principles theory of inelastic tunneling between a model probe tip and an atom adsorbed on a surface is presented, extending the elastic tunneling theory of Tersoff and Hamann. The inelastic current is proportional to the change in the local density of states at the center of the tip due to the addition of the adsorbate. We use the theory to investigate the vibrational heating of an adsorbate below an STM tip. We calculate the desorption rate of H from Si(100)-H(2$\times$1) as function of the sample bias and tunnel current, and find excellent agreement with recent experimental data.Comment: 5 pages, RevTeX, epsf file

The HADES Tracking System

The tracking system of the dielectron spectrometer HADES at GSI Darmstadt is formed out of 24 low-mass, trapezoidal multi-layer drift chambers providing in total about 30 square meter of active area. Low multiple scattering in the in total four planes of drift chambers before and after the magnetic field is ensured by using helium-based gas mixtures and aluminum cathode and field wires. First in-beam performance results are contrasted with expectations from simulations. Emphasis is placed on the energy loss information, exploring its relevance regarding track recognition.Comment: 6 pages, 4 figures, presented at the 10th Vienna Conference on Instrumentation, Vienna, February 2004, to be published in NIM A (special issue