Aerodynamic configuration development of the highly maneuverable aircraft technology remotely piloted research vehicle

The aerodynamic development of the highly maneuverable aircraft technology remotely piloted research vehicle (HiMAT/RPRV) from the conceptual design to the final configuration is presented. The design integrates several advanced concepts to achieve a high degree of transonic maneuverability, and was keyed to sustained maneuverability goals while other fighter typical performance characteristics were maintained. When tests of the baseline configuration indicated deficiencies in the technology integration and design techniques, the vehicle was reconfigured to satisfy the subcritical and supersonic requirements. Drag-due-to-lift levels only 5 percent higher than the optimum were obtained for the wind tunnel model at a lift coefficient of 1 for Mach numbers of up to 0.8. The transonic drag rise was progressively lowered with the application of nonlinear potential flow analyses coupled with experimental data

Tourism To Parks In Zimbabwe: 1969-1988

A GJZ (geographic Journal of Zimbabwe) article on tourism.International and domestic tourism creates considerable economic activity in Zimbabwe and is an important source of foreign currency. The Zimbabwean tourist industry is largely based upon marketing a ‘wilderness experience’ and relies heavily upon the national parks and other protected areas within the country. By providing visitor accommodation and other services within the areas it controls, the Department of National Parks and Wild Life Management (DNPWLM) is one of the country’s major tourist organizations

Conditional Regressive Random Forest Stereo-based Hand Depth Recovery

This paper introduces Conditional Regressive Random Forest (CRRF), a novel method that combines a closed-form Conditional Random Field (CRF), using learned weights, and a Regressive Random Forest (RRF) that employs adaptively selected expert trees. CRRF is used to estimate a depth image of hand given stereo RGB inputs. CRRF uses a novel superpixel-based regression framework that takes advantage of the smoothness of the hand’s depth surface. A RRF unary term adaptively selects different stereo-matching measures as it implicitly determines matching pixels in a coarse-to-fine manner. CRRF also includes a pair-wise term that encourages smoothness between similar adjacent superpixels. Experimental results show that CRRF can produce high quality depth maps, even using an inexpensive RGB stereo camera and produces state-of-the-art results for hand depth estimation

Quantized Census for Stereoscopic Image Matching

Current depth capturing devices show serious drawbacks in certain applications, for example ego-centric depth recovery: they are cumbersome, have a high power requirement, and do not portray high resolution at near distance. Stereo-matching techniques are a suitable alternative, but whilst the idea behind these techniques is simple it is well known that recovery of an accurate disparity map by stereo-matching requires overcoming three main problems: occluded regions causing absence of corresponding pixels; existence of noise in the image capturing sensor and inconsistent color and brightness in the captured images. We propose a modified version of the Census-Hamming cost function which allows more robust matching with an emphasis on improving performance under radiometric variations of the input images

Data-driven Recovery of Hand Depth using Conditional Regressive Random Forest on Stereo Images

Hand pose is emerging as an important interface for human-computer interaction. This paper presents a data-driven method to estimate a high-quality depth map of a hand from a stereoscopic camera input by introducing a novel superpixel based regression framework that takes advantage of the smoothness of the depth surface of the hand. To this end, we introduce Conditional Regressive Random Forest (CRRF), a method that combines a Conditional Random Field (CRF) and a Regressive Random Forest (RRF) to model the mapping from a stereo RGB image pair to a depth image. The RRF provides a unary term that adaptively selects different stereo-matching measures as it implicitly determines matching pixels in a coarse-to-fine manner. While the RRF makes depth prediction for each super-pixel independently, the CRF unifies the prediction of depth by modeling pair-wise interactions between adjacent superpixels. Experimental results show that CRRF can generate a depth image more accurately than the leading contemporary techniques using an inexpensive stereo camera

Adiabatic motion of a neutral spinning particle in an inhomogeneous magnetic field

The motion of a neutral particle with a magnetic moment in an inhomogeneous magnetic field is considered. This situation, occurring, for example, in a Stern-Gerlach experiment, is investigated from classical and semiclassical points of view. It is assumed that the magnetic field is strong or slowly varying in space, i.e., that adiabatic conditions hold. To the classical model, a systematic Lie-transform perturbation technique is applied up to second order in the adiabatic-expansion parameter. The averaged classical Hamiltonian contains not only terms representing fictitious electric and magnetic fields but also an additional velocity-dependent potential. The Hamiltonian of the quantum-mechanical system is diagonalized by means of a systematic WKB analysis for coupled wave equations up to second order in the adiabaticity parameter, which is coupled to Planck’s constant. An exact term-by-term correspondence with the averaged classical Hamiltonian is established, thus confirming the relevance of the additional velocity-dependent second-order contribution

Hand Pose Estimation Using Deep Stereovision and Markov-chain Monte Carlo

Hand pose is emerging as an important interface for human-computer interaction. The problem of hand pose estimation from passive stereo inputs has received less attention in the literature compared to active depth sensors. This paper seeks to address this gap by presenting a datadriven method to estimate a hand pose from a stereoscopic camera input, by introducing a stochastic approach to propose potential depth solutions to the observed stereo capture and evaluate these proposals using two convolutional neural networks (CNNs). The first CNN, configured in a Siamese network architecture, evaluates how consistent the proposed depth solution is to the observed stereo capture. The second CNN estimates a hand pose given the proposed depth. Unlike sequential approaches that reconstruct pose from a known depth, our method jointly optimizes the hand pose and depth estimation through Markov-chain Monte Carlo (MCMC) sampling. This way, pose estimation can correct for errors in depth estimation, and vice versa. Experimental results using an inexpensive stereo camera show that the proposed system more accurately measures pose better than competing methods

Non-Adiabatic Potential-Energy Surfaces by Constrained Density-Functional Theory

Non-adiabatic effects play an important role in many chemical processes. In order to study the underlying non-adiabatic potential-energy surfaces (PESs), we present a locally-constrained density-functional theory approach, which enables us to confine electrons to sub-spaces of the Hilbert space, e.g. to selected atoms or groups of atoms. This allows to calculate non-adiabatic PESs for defined charge and spin states of the chosen subsystems. The capability of the method is demonstrated by calculating non-adiabatic PESs for the scattering of a sodium and a chlorine atom, for the interaction of a chlorine molecule with a small metal cluster, and for the dissociation of an oxygen molecule at the Al(111) surface.Comment: 11 pages including 7 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

Rapid identification of mutations in GJC2 in primary lymphoedema using whole exome sequencing combined with linkage analysis with delineation of the phenotype.

Background: Primary lymphoedema describes a chronic, frequently progressive, failure of lymphatic drainage. This disorder is frequently genetic in origin, and a multigenerational family in which eight individuals developed postnatal lymphoedema of all four limbs was ascertained from the joint Lymphoedema/Genetic clinic at St George's Hospital. Methods: Linkage analysis was used to determine a locus, and exome sequencing was employed to look for causative variants. Results: Linkage analysis revealed cosegregation of a 16.1 Mb haplotype on chromosome 1q42 that contained 173 known or predicted genes. Whole exome sequencing in a single affected individual was undertaken, and the search for the causative variant was focused to within the linkage interval. This approach revealed two novel non-synonymous single nucleotide substitutions within the chromosome 1 locus, in NVL and GJC2. NVL and GJC2 were sequenced in an additional cohort of individuals with a similar phenotype and non-synonymous variants were found in GJC2 in four additional families. Conclusion: This report demonstrates the power of exome sequencing efficiently applied to a traditional positional cloning pipeline in disease gene discovery, and suggests that the phenotype produced by GJC2 mutations is predominantly one of 4 limb lymphoedema

State-to-State Differential and Relative Integral Cross Sections for Rotationally Inelastic Scattering of H2O by Hydrogen

State-to-state differential cross sections (DCSs) for rotationally inelastic scattering of H2O by H2 have been measured at 71.2 meV (574 cm-1) and 44.8 meV (361 cm-1) collision energy using crossed molecular beams combined with velocity map imaging. A molecular beam containing variable compositions of the (J = 0, 1, 2) rotational states of hydrogen collides with a molecular beam of argon seeded with water vapor that is cooled by supersonic expansion to its lowest para or ortho rotational levels (JKaKc= 000 and 101, respectively). Angular speed distributions of fully specified rotationally excited final states are obtained using velocity map imaging. Relative integral cross sections are obtained by integrating the DCSs taken with the same experimental conditions. Experimental state-specific DCSs are compared with predictions from fully quantum scattering calculations on the most complete H2O-H2 potential energy surface. Comparison of relative total cross sections and state-specific DCSs show excellent agreement with theory in almost all detailsComment: 46 page