High-resolution Density Research Articles

Estimation of full‐field dynamic strains from digital video measurements of output‐only beam structures by video motion processing and modal superposition

Strain is an essential quantity to characterize local structural behaviors and directly correlates with structural damage initiation and development that is within local regions. Strain measurement at high spatial resolution (density) locations is thus required to characterize local structural behaviors and detect potential local damage. Traditional contact‐type strain gauges are mostly discrete point‐wise sensors that can only be placed in a limited number of positions. Distributed optical fiber sensing techniques can measure strains at spatially dense measurement points, but their instrumentation is a time‐ and labor‐intensive process associated with the issue of the fragility of fibers. Noncontact optical measurement techniques, such as a family of interferometry techniques using laser beams (e.g., laser Doppler vibrometers), can provide vibration measurement at high density spatial points without the need to install sensors on the structure. However, these measurement devices are active sensing methods that are relatively expensive and vulnerable to ambient motion. Photogrammetry is an alternative noncontact optical measurement method using (passive) white‐light imaging of digital video cameras that are relatively low‐cost, agile, and provides simultaneous measurements at high spatial density locations where every pixel becomes a measurement point. Among others, digital image correlation can achieve full‐field deformation measurements and subsequently estimate the full‐field strains. However, it is computationally extensive. This study develops a new efficient approach to estimate the full‐field (as many measurement points as the pixel number of the video frame on the structure) dynamic strains at high‐spatial (pixel)‐resolution/density location points from the digital video measurement of output‐only vibrating structures. The developed approach is based on phase‐based video motion estimation and modal superposition of structural dynamic response. Furthermore, the method is augmented by a high‐fidelity finite element model, which is updated with the full‐field experimental modal parameters “blindly” identified from the video measurement of the output‐only structure. Laboratory experiments are conducted to validate the method on a bench‐scale cantilever beam structure. Results demonstrate that the full‐field dynamic strain estimated by the developed approach from the video measurement of the output‐only vibrating beam match very well those directly measured by the strain gauges (at discrete measurement points). Some factors associated with the effectiveness of the method are experimentally studied and discussed.

Abstract 1985: Reassessment of exosome composition

Abstract The heterogeneity of small extracellular vesicles and the presence of non-vesicular extracellular matter is a major obstacle to the study of exosomes. Here we employ two complementary methods, high-resolution density gradient fractionation and direct immunoaffinity capture, to demonstrate separation of small extracellular vesicles from non-vesicular material, and exosomes from other types of small extracellular vesicles. Cells secrete Argonaute 1-4 independently of exosomes. Extracellular RNA and RNA-binding proteins are differentially expressed between exosome and non-vesicle compartments. Exosomes do not possess a cytoskeleton and exclude glycolytic enzymes. Annexin A1 is a novel and specific membrane-associated protein marker of microvesicles shed directly from the cell plasma membrane, distinct from exosomes in vitro and in vivo. Small extracellular vesicles are not vehicles of active DNA release. Instead we propose a new model for active secretion of extracellular DNA through an autophagy- and multivesicular endosome-dependent but exosome-independent mechanism. A reassessment of exosome composition is necessary. Citation Format: Dennis K. Jeppesen, Jeffrey L. Franklin, James N. Higginbotham, Qin Zhang, Robert J. Coffey. Reassessment of exosome composition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1985.

Synergistic effect of metal-organic framework-derived boron and nitrogen heteroatom-doped three-dimensional porous carbons for precious-metal-free catalytic reduction of nitroarenes

We report a scalable and controllable synthesis of metal-organic framework (MOF)-derived three-dimensional boron and nitrogen heteroatom-doped porous carbons (3D-BNPCs) and their synergistic effect for metal-free catalytic 4-nitrophenol (4-NP) reduction. The substitution of boron atoms into zeolitic imidazole framework-8 (ZIF-8)-derived nitrogen-doped porous carbon (B-NPC-1200) significantly improves the electrical conductivity and the catalytic 4-NP reduction. We propose the heteroatom-doping of boron, nitrogen and oxygen in the 3D- B-N PC catalysts creates synergistic effect on 4-NP reduction by creating more catalytically active sites. High-Resolution X-ray Photoelectron Spectroscopy (HR-XPS) and Density Functional Theory (DFT) calculations were carried out to confirm and investigate the role of active sites on adsorption of 4-NP molecules in B-NPC-1200. We find that the strongly active sites can only be created based on the synergistic effect between nitrogen, boron and oxygen atoms, and the increased density of the active sites are responsible for the lowering of the apparent activation energy in B-NPC-1200 structure. As synthesized B-NPC-1200 exhibits superior catalytic activities for 4-NP reduction with a low apparent activation energy of 27.0 kJ/mol and a high reaction rate constant of 2.3*10^−3 (s-1). The catalyst can run five times without decreasing significant catalytic activity. The reduction reactions of various nitroarene compounds have been further tested using the B-N PC-1200 material as the precious-metal-free catalyst.

Predict-first experiments and modeling of perturbative cold pulses in the DIII-D tokamak

Cold pulses are introduced in Ohmic DIII-D tokamak plasmas via injection of impurities with a laser blow-off system, revealing for the first time in this machine a quick increase in core electron temperature shortly after the edge cold-pulse injection at low collisionality. The experimental results are consistent with predict-first simulations of heat transport enabled by the Trapped Gyro-Landau-Fluid transport model. Measurements of electron density evolution during the cold-pulse propagation are enabled by a high time resolution density profile reflectometer. The density evolution reveals the quick propagation of a pulse from edge to core, which is a mechanism to transiently increase core temperature in low-collisionality plasmas. Local transport simulations with measured density evolution demonstrate that the core temperature response can indeed be explained by the stabilization of Trapped Electron Mode turbulence at low collisionality, thus providing confidence that local transport modeling is enough to explain cold-pulse propagation and associated phenomenology.

On-Surface Fabrication of Small-Sized Nanoporous Graphene

From the interplay of high-resolution scanning tunneling microscopy and density functional theory calculations, we have successfully obtained small-sized nanoporous graphene via a hierarchical reac...

Three-dimensional stochastic assimilation of gravity data in Lalor volcanogenic massive sulphide, Manitoba, Canada

We propose a new numerical workflow based on stochastic data integration where we merge a conceptual geological model, drillhole geophysical and geological logs, and surface geophysical data to compute a unified numerical model of a volcanogenic massive sulphide (VMS) deposit. The first step of the workflow consists in building a three-dimensional (3D) numerical conceptual model of the geology. This conceptual model, as well as geological logs, is then used to generate multiple equiprobable scenarios of the geology by means of multiple-point simulation (MPS). The MPS method studies high-order statistics in the space of a numerical conceptual model, making it possible to reproduce complex geological structures. We then use conventional conditional sequential Gaussian simulation, which is a method based on a node-by-node sequential process, to stochastically populate the geological grid with densities. For this purpose we use available density logs to simulate multiple equiprobable spatial distributions of the density at high spatial resolution within each geological unit separately. The stochastic high-resolution density models are iteratively combined by the gradual deformation method to minimize the difference between measured Bouguer anomaly data and the data computed on the combined realizations of density. Application of the proposed method to the Lalor deposit, a VMS deposit in Manitoba, Canada, produces a density model that honours the geology of the deposit and the Bouguer anomaly data. This unified model has the advantage to include all the available information (geological and density logs and surface geophysics) at scales appropriate for mining applications.

Reassessment of Exosome Composition

The heterogeneity of small extracellular vesicles and presence of non-vesicular extracellular matter have led to debate about contents and functional properties of exosomes. Here, we employ high-resolution density gradient fractionation and direct immunoaffinity capture to precisely characterize the RNA, DNA, and protein constituents of exosomes and other non-vesicle material. Extracellular RNA, RNA-binding proteins, and other cellular proteins are differentially expressed in exosomes and non-vesicle compartments. Argonaute 1-4, glycolytic enzymes, and cytoskeletal proteins were not detected in exosomes. Weidentify annexin A1 as a specific marker for microvesicles that are shed directly from the plasma membrane. We further show that small extracellular vesicles are not vehicles of active DNA release. Instead, we propose a new model for active secretion of extracellular DNA through an autophagy- and multivesicular-endosome-dependent but exosome-independent mechanism. This study demonstrates the need for a reassessment of exosome composition and offers a framework for a clearer understanding of extracellular vesicle heterogeneity.

The effect of divertor closure on detachment onset in DIII-D

Abstract Experiments at DIII-D use different divertor geometries to measure the effect of divertor closure on detachment onset. We compare matched H-mode discharges in the closed (upper) divertor and the open (lower) divertor and use as a detachment onset metric the rollover in peak ion flux to the target, Jsat, as a function of upstream pedestal top density, ne,ped. Measurements of electron temperature in the lower divertor confirm that this metric captures the transition from attached to detached divertor for this data set. Experiments at two different neutral beam injection powers demonstrate an ≈ 20–40% decrease in pedestal density at detachment onset in the closed case compared to the open. High-resolution edge density and temperature measurements and power balance analysis allow us to determine the difference in upstream separatrix density ne,sep at detachment onset, which we find to be ≈ 15–25% lower in the closed divertor case. The effect of closure on detachment seen in separatrix density is hence only about 60–75% the effect seen in pedestal density, with the remainder due to differences in ne,sep/ne,ped. Future devices are expected to have a scrape off layer that is opaque to neutrals, and hence will not have the same pedestal fueling to affect ne,sep/ne,ped; this suggests that the effect of closure on detachment onset seen in future devices will be less than that seen in current experiments, and closer to the magnitude of the effect we see here in the separatrix for a similar degree of divertor closure.

High-resolution maps of Swiss apiaries and their applicability to study spatial distribution of bacterial honey bee brood diseases.

Honey bees directly affect and are influenced by their local environment, in terms of food sources, pollinator densities, pathogen and toxin exposure and climate. Currently, there is a lack of studies analyzing these data with Geographic Information Systems (GIS) to investigate spatial relationships with the environment. Particularly for inter-colonial pathogen transmission, it is known that the likelihood of a healthy colony to become infested (e.g., Varroosis) or infected (e.g., American foulbrood—AFB, European foulbrood—EFB) increases with higher colony density. Whether these transmission paths can actually be asserted at apiary level is largely unknown. Here, we unraveled spatial distribution and high-resolution density of apiaries and bacterial honey bee brood diseases in Switzerland based on available GIS data. Switzerland as ‘model country’ offers the unique opportunity to get apiary data since 2010 owing to compulsory registration for every beekeeper. Further, both destructive bee brood diseases (AFB and EFB) are legally notifiable in Switzerland, and EFB has an epizootic character for the last decades. As governmental data sets have to be ameliorated, raw data from the cantonal agricultural or veterinary offices have been included. We found a mean density of 0.56 apiaries per km2, and high resolution spatial analyzes showed strong correlation between density of apiaries and human population density as well as agricultural landscape type. Concerning two bacterial bee brood diseases (AFB, EFB), no significant correlation was detectable with density of apiaries on cantonal level, though a high correlation of EFB cases and apiary density became obvious on higher resolution (district level). Hence, Swiss EFB epizootics seem to have benefited from high apiary densities, promoting the transmission of pathogens by adult bees. The GIS-based method presented here, might also be useful for other bee diseases, anthropogenic or environmental factors affecting bee colonies.

High-resolution temperature profiles retrieved from bichromatic stellar scintillation measurements by GOMOS/Envisat

Abstract. In this paper, we describe the inversion algorithm for retrievals of high vertical resolution temperature profiles (HRTPs) using bichromatic stellar scintillation measurements in the occultation geometry. This retrieval algorithm has been improved with respect to nominal ESA processing and applied to the measurements by Global Ozone Monitoring by Occultation of Stars (GOMOS) operated on board Envisat in 2002–2012. The retrieval method exploits the chromatic refraction in the Earth's atmosphere. The bichromatic scintillations allow the determination of the refractive angle, which is proportional to the time delay between the photometer signals. The paper discusses the basic principle and detailed inversion algorithm for reconstruction of high-resolution density, pressure and temperature profiles in the stratosphere from scintillation measurements. The HRTPs are retrieved with a very good vertical resolution of ∼200 m and high precision (random uncertainty) of ∼1–3 K for altitudes of 15–32 km and with a global coverage. The best accuracy is achieved for in-orbital-plane occultations, and the precision weakly depends on star brightness. The whole GOMOS dataset has been processed with the improved HRTP inversion algorithm using the FMI's scientific processor; and the dataset (HRTP FSP v1) is in open access. The validation of small-scale fluctuations in the retrieved HRTPs is performed via comparison of vertical wavenumber spectra of temperature fluctuations in HRTPs and in collocated radiosonde data. We found that the spectral features of temperature fluctuations are very similar in HRTPs and collocated radiosonde temperature profiles. HRTPs can be assimilated into atmospheric models, used in studies of stratospheric clouds and used for the analysis of internal gravity waves' activity. As an example of geophysical applications, gravity wave potential energy has been estimated using the HRTP dataset. The obtained spatiotemporal distributions of gravity wave energy are in good agreement with the previous analyses using other measurements.

Effective use of convolutional neural networks and diverse deep supervision for better crowd counting

In this paper, we focus on the task of estimating crowd count and high-quality crowd density maps. Among crowd counting methods, crowd density map estimation is especially promising because it preserves spatial information which makes it useful for both counting and localization (detection and tracking). Convolutional neural networks have enabled significant progress in crowd density estimation recently, but there are still open questions regarding suitable architectures. We revisit CNNs design and point out key adaptations, enabling plain a signal column CNNs to obtain high resolution and high-quality density maps on all major dense crowd counting datasets. The regular deep supervision utilizes the general ground truth to guide intermediate predictions. Instead, we build hierarchical supervisory signals with additional multi-scale labels to consider the diversities in deep neural networks. We begin by obtaining multi-scale labels based on different Gaussian kernels. These multi-scale labels can be seen as diverse representations in the supervision and can achieve high performance for better quality crowd density map estimation. Extensive experiments demonstrate that our approach achieves the state-of-the-art performance on the ShanghaiTech, UCF_CC_50 and UCSD datasets.

Fine-Scale Resolution of Runs of Homozygosity Reveal Patterns of Inbreeding and Substantial Overlap with Recessive Disease Genotypes in Domestic Dogs

Inbreeding leaves distinct genomic traces, most notably long genomic tracts that are identical by descent and completely homozygous. These runs of homozygosity (ROH) can contribute to inbreeding depression if they contain deleterious variants that are fully or partially recessive. Several lines of evidence have been used to show that long (> 5 megabase) ROH are disproportionately likely to harbor deleterious variation, but the extent to which long vs. short tracts contribute to autozygosity at loci known to be deleterious and recessive has not been studied. In domestic dogs, nearly 200 mutations are known to cause recessive diseases, most of which can be efficiently assayed using SNP arrays. By examining genome-wide data from over 200,000 markers, including 150 recessive disease variants, we built high-resolution ROH density maps for nearly 2,500 dogs, recording ROH down to 500 kilobases. We observed over 678 homozygous deleterious recessive genotypes in the panel across 29 loci, 90% of which overlapped with ROH inferred by GERMLINE. Although most of these genotypes were contained in ROH over 5 Mb in length, 14% were contained in short (0.5 - 2.5 megabase) tracts, a significant enrichment compared to the genetic background, suggesting that even short tracts are useful for computing inbreeding metrics like the coefficient of inbreeding estimated from ROH (FROH). In our dataset, FROH differed significantly both within and among dog breeds. All breeds harbored some regions of reduced genetic diversity due to drift or selective sweeps, but the degree of inbreeding and the proportion of inbreeding caused by short vs. long tracts differed between breeds, reflecting their different population histories. Although only available for a few species, large genome-wide datasets including recessive disease variants hold particular promise not only for disentangling the genetic architecture of inbreeding depression, but also evaluating and improving upon current approaches for detecting ROH.

Diamantane Suspended Single Copper Atoms.

Single chains of metal atoms are expected to be perfect one-dimensional nanowires in nanotechnology, due to their quantum nature including tunable electronic or spin coupling strengths. However, it is still rather difficult to fabricate such nanowires with metallic atoms under directional and separation control. Here, we succeeded in building higher-order single diamondoid-chains from the lower-order chains using a chemically well-controlled approach that employs diamondoids on metal surfaces. This approach results in higher-order diamondoid double chains by linking two neighboring single chains, and ultimately forms a central chain consisting of single Cu atoms suspended by the diamantane framework. The suspended Cu atoms are placed above the metal surface with a periodic distance of 0.67 ± 0.01 nm. Our bottom-up approach will allow detailed experimental investigations of the properties of these exciting suspended metal atoms (for example, quantized conductance, spin coupling, as well as transfer, etc.). Furthermore, we also identified different spatial configurations on the metal surfaces in on-surface reaction processes using high-resolution AFM imaging and density functional theory computations. Our findings broaden the on-surface synthesis concept from 2D planar aromatic molecules to 3D bulky aliphatic molecules.

Physical properties and chemical composition of the cores in the California molecular cloud

Aims. We aim to reveal the physical properties and chemical composition of the cores in the California molecular cloud (CMC), so as to better understand the initial conditions of star formation. Methods. We made a high-resolution column density map (18.2′′) with Herschel data, and extracted a complete sample of the cores in the CMC with the fellwalker algorithm. We performed new single-pointing observations of molecular lines near 90 GHz with the IRAM 30m telescope along the main filament of the CMC. In addition, we also performed a numerical modeling of chemical evolution for the cores under the physical conditions. Results. We extracted 300 cores, of which 33 are protostellar and 267 are starless cores. About 51% (137 of 267) of the starless cores are prestellar cores. Three cores have the potential to evolve into high-mass stars. The prestellar core mass function (CMF) can be well fit by a log-normal form. The high-mass end of the prestellar CMF shows a power-law form with an index α = −0.9 ± 0.1 that is shallower than that of the Galactic field stellar mass function. Combining the mass transformation efficiency (ε) from the prestellar core to the star of 15 ± 1% and the core formation efficiency (CFE) of 5.5%, we suggest an overall star formation efficiency of about 1% in the CMC. In the single-pointing observations with the IRAM 30m telescope, we find that 6 cores show blue-skewed profile, while 4 cores show red-skewed profile. [HCO+]/[HNC] and [HCO+]/[N2H+] in protostellar cores are higher than those in prestellar cores; this can be used as chemical clocks. The best-fit chemical age of the cores with line observations is ~5 × 104 yr.

High performance LCD for augmented reality and virtual reality displays

ABSTRACTFor augmented reality and virtual reality displays, high-resolution density, high luminance, and fast response time are critically needed. High-resolution density helps eliminate the screen-door effect; high luminance and fast response time enable low duty ratio operation, which plays a key role for suppressing image blurs. By using a low viscosity material and new diamond-shaped electrode configuration, we demonstrate a fringe field switching liquid crystal display, abbreviated as d-FFS LCD, with high transmittance, fast grey-to-grey response time, low operation voltage, wide viewing angle, and indistinguishable colour shift and gamma shift. We also investigate the rubbing angle (α) effects on transmittance and response time. When α = 0°, the virtual wall effect is strong, resulting in fast response time but compromised transmittance. When α ≥ 1.2°, the virtual walls disappear, as a result, the transmittance increases dramatically, but the trade-off is in slower response time.

Delineation of individual deciduous trees in plantations with low-density LiDAR data

ABSTRACTDelineation of individual deciduous trees with Light Detection and Ranging (LiDAR) data has long been sought for accurate forest inventory in temperate forests. Previous attempts mainly focused on high-density LiDAR data to obtain reliable delineation results, which may have limited applications due to the high cost and low availability of such data. Here, the feasibility of individual deciduous tree delineation with low-density LiDAR data was examined using a point-density-based algorithm. First a high-resolution point density model (PDM) was developed from low-density LiDAR point cloud to locate individual trees through the horizontal spatial distribution of LiDAR points. Then, individual tree crowns and associated attributes were delineated with a 2D marker-controlled watershed segmentation. Additionally, the PDM-based approach was compared with a conventional canopy height model (CHM) based delineation. The results demonstrated that the PDM-based approach produced an 89% detection accuracy to identify deciduous trees in our study area. The tree attributes derived from the PDM-based algorithm explained 81% and 83% of tree height and crown width variations of forest stands, respectively. The conventional CHM-based tree attributes, on the other hand, could explain only 71% and 66% of tree height and crown width, respectively. Our results suggest that the application of the PDM-based individual tree identification in deciduous forests with low-density LiDAR data is feasible and has relatively high accuracy to predict tree height and crown width, which are highly desired in large-scale forest inventory and analysis.

3D Dirac Plasmons in the Type-II Dirac Semimetal PtTe_{2}.

Transition-metal dichalcogenides showing type-II Dirac fermions are emerging as innovative materials for nanoelectronics. However, their excitation spectrum is mostly unexplored yet. By means of high-resolution electron energy loss spectroscopy and density functional theory, here, we identify the collective excitations of type-II Dirac fermions (3D Dirac plasmons) in PtTe_{2} single crystals. The observed plasmon energy in the long-wavelength limit is ∼0.5 eV, which makes PtTe_{2} suitable for near-infrared optoelectronic applications. We also demonstrate that interband transitions between the two Dirac bands in PtTe_{2} give rise to additional excitations at ∼1 and ∼1.4 eV. Our results are crucial to bringing to fruition type-II Dirac semimetals in optoelectronics.

Diacetylene Linked Anthracene Oligomers Synthesized by One-Shot Homocoupling of Trimethylsilyl on Cu(111)

On-surface chemical reaction has become a very powerful technique to conjugate small precursor molecules and several reactions have been proposed with the aim to fabricate functional nanostructures on surfaces. Here we present an unforeseen adsorption mode of 9,10-bis((trimethylsilyl)ethynyl)anthracene on a Cu(111)surface and the resulting one-shot desilylative homocoupling of of the adsorbate by annealing at 400 K. With a combination of high-resolution atomic force microscopy and density functional theory calculations, we found that the triple bonds and silicon atoms of the monomer chemically interact with the copper surface. After the oligomerization, we discovered that the anthracene units are linked to each other via buta-1,3-diynediyl fragments while keeping the surface clean. Furthermore, the force measurement revealed the chemical nature at the center of anthracene unit.

Constructing atomic structural models into cryo-EM densities using molecular dynamics - Pros and cons.

Accurate structure determination from electron density maps at 3-5 Å resolution necessitates a balance between extensive global and local sampling of atomistic models, yet with the stereochemical correctness of backbone and sidechain geometries. Molecular Dynamics Flexible Fitting (MDFF), particularly through a resolution-exchange scheme, ReMDFF, provides a robust way of achieving this balance for hybrid structure determination. Employing two high-resolution density maps, namely that of β-galactosidase at 3.2 Å and TRPV1 at 3.4 Å, we showcase the quality of ReMDFF-generated models, comparing them against ones submitted by independent research groups for the 2015-2016 Cryo-EM Model Challenge. This comparison offers a clear evaluation of ReMDFF's strengths and shortcomings, and those of data-guided real-space refinements in general. ReMDFF results scored highly on the various metric for judging the quality-of-fit and quality-of-model. However, some systematic discrepancies are also noted employing a Molprobity analysis, that are reproducible across multiple competition entries. A space of key refinement parameters is explored within ReMDFF to observe their impact within the final model. Choice of force field parameters and initial model seem to have the most significant impact on ReMDFF model-quality. To this end, very recently developed CHARMM36m force field parameters provide now more refined ReMDFF models than the ones originally submitted to the Cryo-EM challenge. Finally, a set of good-practices is prescribed for the community to benefit from the MDFF developments.

Transition from linear- to nonlinear-focusing regime of laser filament plasma dynamics

Laser filament properties, including the plasma induced by the filamenting pulse in the medium, depend on the numerical aperture (NA) of the focusing optics used to create them. Recent studies of this dependence have revealed two distinct linear and non-linear filamentation regimes. High-resolution spatial and temporal electron density measurements are presented demonstrating the transition from the linear to nonlinear focusing regime. This study shows that the dominance of geometrical focusing in the linear (high NA) regime produces plasma with high peak densities and large plasma diameters, while filamentation in the nonlinear regime, equivalent to long distance filamentation, leads to low peak densities and small plasma diameters.