Context-based urban terrain reconstruction from uav-videos for geoinformation applications

Urban terrain reconstruction has many applications in areas of civil engineering, urban planning, surveillance and defense research. Therefore the needs of covering ad-hoc demand and performing a close-range urban terrain reconstruction with miniaturized and relatively inexpensive sensor platforms are constantly growing. Using (miniaturized) unmanned aerial vehicles, (M) UAVs, represents one of the most attractive alternatives to conventional large-scale aerial imagery. We cover in this paper a four-step procedure of obtaining georeferenced 3D urban models from video sequences. The four steps of the procedure - orientation, dense reconstruction, urban terrain modeling and geo-referencing - are robust, straight-forward, and nearly fully-automatic. The two last steps - namely, urban terrain modeling from almost-nadir videos and co-registration of models - represent the main contribution of this work and will therefore be covered with more detail. The essential substeps of the third step include digital terrain model (DTM) extraction, segregation of buildings from vegetation, as well as instantiation of building and tree models. The last step is subdivided into quasi-intrasensorial registration of Euclidean reconstructions and intersensorial registration with a geo-referenced orthophoto. Finally, we present reconstruction results from a real data-set and outline ideas for future work

Frequency and power of human alpha oscillations drift systematically with time-on-task

Oscillatory neural activity is a fundamental characteristic of the mammalian brain spanning multiple levels of spatial and temporal scale. Current theories of neural oscillations and analysis techniques employed to investigate their functional significance are based on an often implicit assumption: In the absence of experimental manipulation, the spectral content of any given EEG- or MEG-recorded neural oscillator remains approximately stationary over the course of a typical experimental session (∼1 h), spontaneously fluctuating only around its dominant frequency. Here, we examined this assumption for ongoing neural oscillations in the alpha-band (8–13 Hz). We found that alpha peak frequency systematically decreased over time, while alpha-power increased. Intriguingly, these systematic changes showed partial independence of each other: Statistical source separation (independent component analysis) revealed that while some alpha components displayed concomitant power increases and peak frequency decreases, other components showed either unique power increases or frequency decreases. Interestingly, we also found these components to differ in frequency. Components that showed mixed frequency/power changes oscillated primarily in the lower alpha-band (∼8–10 Hz), while components with unique changes oscillated primarily in the higher alpha-band (∼9–13 Hz). Our findings provide novel clues on the time-varying intrinsic properties of large-scale neural networks as measured by M/EEG, with implications for the analysis and interpretation of studies that aim at identifying functionally relevant oscillatory networks or at driving them through external stimulation

Adaptive self-organization in a realistic neural network model

Information processing in complex systems is often found to be maximally efficient close to critical states associated with phase transitions. It is therefore conceivable that also neural information processing operates close to criticality. This is further supported by the observation of power-law distributions, which are a hallmark of phase transitions. An important open question is how neural networks could remain close to a critical point while undergoing a continual change in the course of development, adaptation, learning, and more. An influential contribution was made by Bornholdt and Rohlf, introducing a generic mechanism of robust self-organized criticality in adaptive networks. Here, we address the question whether this mechanism is relevant for real neural networks. We show in a realistic model that spike-time-dependent synaptic plasticity can self-organize neural networks robustly toward criticality. Our model reproduces several empirical observations and makes testable predictions on the distribution of synaptic strength, relating them to the critical state of the network. These results suggest that the interplay between dynamics and topology may be essential for neural information processing.Comment: 6 pages, 4 figure

Quasiparticle band structure of infinite hydrogen fluoride and hydrogen chloride chains

We study the quasiparticle band structure of isolated, infinite HF and HCl bent (zigzag) chains and examine the effect of the crystal field on the energy levels of the constituent monomers. The chains are one of the simplest but realistic models of the corresponding three-dimensional crystalline solids. To describe the isolated monomers and the chains, we set out from the Hartree-Fock approximation, harnessing the advanced Green's function methods "local molecular orbital algebraic diagrammatic construction" (ADC) scheme and "local crystal orbital ADC" (CO-ADC) in a strict second order approximation, ADC(2,2) and CO-ADC(2,2), respectively, to account for electron correlations. The configuration space of the periodic correlation calculations is found to converge rapidly only requiring nearest-neighbor contributions to be regarded. Although electron correlations cause a pronounced shift of the quasiparticle band structure of the chains with respect to the Hartree-Fock result, the bandwidth essentially remains unaltered in contrast to, e.g., covalently bound compounds.Comment: 11 pages, 6 figures, 6 tables, RevTeX4, corrected typoe

Involvement of Basal Ganglia Network in Motor Disabilities Induced by Typical Antipsychotics

BACKGROUND:Clinical treatments with typical antipsychotic drugs (APDs) are accompanied by extrapyramidal motor side-effects (EPS) such as hypokinesia and catalepsy. As little is known about electrophysiological substrates of such motor disturbances, we investigated the effects of a typical APD, alpha-flupentixol, on the motor behavior and the neuronal activity of the whole basal ganglia nuclei in the rat. METHODS AND FINDINGS:The motor behavior was examined by the open field actimeter and the neuronal activity of basal ganglia nuclei was investigated using extracellular single unit recordings on urethane anesthetized rats. We show that alpha-flupentixol induced EPS paralleled by a decrease in the firing rate and a disorganization of the firing pattern in both substantia nigra pars reticulata (SNr) and subthalamic nucleus (STN). Furthermore, alpha-flupentixol induced an increase in the firing rate of globus pallidus (GP) neurons. In the striatum, we recorded two populations of medium spiny neurons (MSNs) after their antidromic identification. At basal level, both striato-pallidal and striato-nigral MSNs were found to be unaffected by alpha-flupentixol. However, during electrical cortico-striatal activation only striato-pallidal, but not striato-nigral, MSNs were found to be inhibited by alpha-flupentixol. Together, our results suggest that the changes in STN and SNr neuronal activity are a consequence of increased neuronal activity of globus pallidus (GP). Indeed, after selective GP lesion, alpha-flupentixol failed to induce EPS and to alter STN neuronal activity. CONCLUSION:Our study reports strong evidence to show that hypokinesia and catalepsy induced by alpha-flupentixol are triggered by dramatic changes occurring in basal ganglia network. We provide new insight into the key role of GP in the pathophysiology of APD-induced EPS suggesting that the GP can be considered as a potential target for the treatment of EPS

Metabolic correlates of prevalent mild cognitive impairment and Alzheimer's disease in adults with Down syndrome.

IntroductionDisruption of metabolic function is a recognized feature of late onset Alzheimer's disease (LOAD). We sought to determine whether similar metabolic pathways are implicated in adults with Down syndrome (DS) who have increased risk for Alzheimer's disease (AD).MethodsWe examined peripheral blood from 292 participants with DS who completed baseline assessments in the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS) using untargeted mass spectrometry (MS). Our sample included 38 individuals who met consensus criteria for AD (DS-AD), 43 who met criteria for mild cognitive impairment (DS-MCI), and 211 who were cognitively unaffected and stable (CS).ResultsWe measured relative abundance of 8,805 features using MS and 180 putative metabolites were differentially expressed (DE) among the groups at false discovery rate-corrected q< 0.05. From the DE features, a nine-feature classifier model classified the CS and DS-AD groups with receiver operating characteristic area under the curve (ROC AUC) of 0.86 and a two-feature model classified the DS-MCI and DS-AD groups with ROC AUC of 0.88. Metabolite set enrichment analysis across the three groups suggested alterations in fatty acid and carbohydrate metabolism.DiscussionOur results reveal metabolic alterations in DS-AD that are similar to those seen in LOAD. The pattern of results in this cross-sectional DS cohort suggests a dynamic time course of metabolic dysregulation which evolves with clinical progression from non-demented, to MCI, to AD. Metabolomic markers may be useful for staging progression of DS-AD

The CuSPED Mission: CubeSat for GNSS Sounding of the Ionosphere-Plasmasphere Electron Density

The CubeSat for GNSS Sounding of Ionosphere-Plasmasphere Electron Density (CuSPED) is a 3U CubeSat mission concept that has been developed in response to the NASA Heliophysics program's decadal science goal of the determining of the dynamics and coupling of the Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The mission was formulated through a collaboration between West Virginia University, Georgia Tech, NASA GSFC and NASA JPL, and features a 3U CubeSat that hosts both a miniaturized space capable Global Navigation Satellite System (GNSS) receiver for topside atmospheric sounding, along with a Thermal Electron Capped Hemispherical Spectrometer (TECHS) for the purpose of in situ electron precipitation measurements. These two complimentary measurement techniques will provide data for the purpose of constraining ionosphere-magnetosphere coupling models and will also enable studies of the local plasma environment and spacecraft charging; a phenomenon which is known to lead to significant errors in the measurement of low-energy, charged species from instruments aboard spacecraft traversing the ionosphere. This paper will provide an overview of the concept including its science motivation and implementation

Constructing Self-Dual Strings

We present an ADHMN-like construction which generates self-dual string solutions to the effective M5-brane worldvolume theory from solutions to the Basu-Harvey equation. Our construction finds a natural interpretation in terms of gerbes, which we develop in some detail. We also comment on a possible extension to stacks of multiple M5-branes.Comment: 1+19 pages, presentation improved, minor corrections, published versio

Wavelet-Based Linear-Response Time-Dependent Density-Functional Theory

Linear-response time-dependent (TD) density-functional theory (DFT) has been implemented in the pseudopotential wavelet-based electronic structure program BigDFT and results are compared against those obtained with the all-electron Gaussian-type orbital program deMon2k for the calculation of electronic absorption spectra of N2 using the TD local density approximation (LDA). The two programs give comparable excitation energies and absorption spectra once suitably extensive basis sets are used. Convergence of LDA density orbitals and orbital energies to the basis-set limit is significantly faster for BigDFT than for deMon2k. However the number of virtual orbitals used in TD-DFT calculations is a parameter in BigDFT, while all virtual orbitals are included in TD-DFT calculations in deMon2k. As a reality check, we report the x-ray crystal structure and the measured and calculated absorption spectrum (excitation energies and oscillator strengths) of the small organic molecule N-cyclohexyl-2-(4-methoxyphenyl)imidazo[1,2-a]pyridin-3-amine