1,458 research outputs found
Towards dense object tracking in a 2D honeybee hive
From human crowds to cells in tissue, the detection and efficient tracking of
multiple objects in dense configurations is an important and unsolved problem.
In the past, limitations of image analysis have restricted studies of dense
groups to tracking a single or subset of marked individuals, or to
coarse-grained group-level dynamics, all of which yield incomplete information.
Here, we combine convolutional neural networks (CNNs) with the model
environment of a honeybee hive to automatically recognize all individuals in a
dense group from raw image data. We create new, adapted individual labeling and
use the segmentation architecture U-Net with a loss function dependent on both
object identity and orientation. We additionally exploit temporal regularities
of the video recording in a recurrent manner and achieve near human-level
performance while reducing the network size by 94% compared to the original
U-Net architecture. Given our novel application of CNNs, we generate extensive
problem-specific image data in which labeled examples are produced through a
custom interface with Amazon Mechanical Turk. This dataset contains over
375,000 labeled bee instances across 720 video frames at 2 FPS, representing an
extensive resource for the development and testing of tracking methods. We
correctly detect 96% of individuals with a location error of ~7% of a typical
body dimension, and orientation error of 12 degrees, approximating the
variability of human raters. Our results provide an important step towards
efficient image-based dense object tracking by allowing for the accurate
determination of object location and orientation across time-series image data
efficiently within one network architecture.Comment: 15 pages, including supplementary figures. 1 supplemental movie
available as an ancillary fil
Does Every Quasar Harbor A Blazar?
Assuming there is a blazar type continuum in every radio-loud quasar, we find
that the free-free heating due to the beamed infrared continuum can greatly
enhance collisionally excited lines, and thus explain the stronger CIV
1549 line emission observed in radio loud quasars. We further predict
that the CIV line should show variability {\it not} associated with observed
continuum or Ly variability.Comment: 15 pages, 3 figures; to appear in Astrophys. J. Let
Illuminating dark matter and primordial black holes with interstellar antiprotons
Interstellar antiproton fluxes can arise from dark matter annihilating or
decaying into quarks or gluons that subsequently fragment into antiprotons.
Evaporation of primordial black holes also can produce a significant antiproton
cosmic-ray flux. Since the background of secondary antiprotons from spallation
has an interstellar energy spectrum that peaks at \sim 2\gev and falls
rapidly for energies below this, low-energy measurements of cosmic antiprotons
are useful in the search for exotic antiproton sources. However, measurement of
the flux near the earth is challenged by significant uncertainties from the
effects of the solar wind. We suggest evading this problem and more effectively
probing dark-matter signals by placing an antiproton spectrometer aboard an
interstellar probe currently under discussion. We address the experimental
challenges of a light, low-power-consuming detector, and present an initial
design of such an instrument. This experimental effort could significantly
increase our ability to detect, and have confidence in, a signal of exotic,
nonstandard antiproton sources. Furthermore, solar modulation effects in the
heliosphere would be better quantified and understood by comparing results to
inverse modulated data derived from existing balloon and space-based detectors
near the earth.Comment: 18 pages, 3 figure
Sympathetic autonomic dysfunction and impaired cardiovascular performance in higher risk surgical patients: implications for perioperative sympatholysis
OBJECTIVE: Recent perioperative trials have highlighted the urgent need for a better understanding of why sympatholytic drugs intended to reduce myocardial injury are paradoxically associated with harm (stroke, myocardial infarction). We hypothesised that following a standardised autonomic challenge, a subset of patients may demonstrate excessive sympathetic activation which is associated with exercise-induced ischaemia and impaired cardiac output. METHODS: Heart rate rise during unloaded pedalling (zero workload) prior to the onset of cardiopulmonary exercise testing (CPET) was measured in 2 observation cohorts of elective surgical patients. The primary outcome was exercise-evoked, ECG-defined ischaemia (>1 mm depression; lead II) associated with an exaggerated increase in heart rate (EHRR ≥12 bpm based on prognostic data for all-cause cardiac death in preceding epidemiological studies). Secondary outcomes included cardiopulmonary performance (oxygen pulse (surrogate for left ventricular stroke volume), peak oxygen consumption (VO2peak), anaerobic threshold (AT)) and perioperative heart rate. RESULTS: EHRR was present in 40.4-42.7% in both centres (n=232, n=586 patients). Patients with EHRR had higher heart rates perioperatively (p<0.05). Significant ST segment depression during CPET was more common in EHRR patients (relative risk 1.7 (95% CI 1.3 to 2.1); p<0.001). EHRR was associated with 11% (95%CI 7% to 15%) lower predicted oxygen pulse (p<0.0001), consistent with impaired left ventricular function. CONCLUSIONS: EHRR is common and associated with ECG-defined ischaemia and impaired cardiac performance. Perioperative sympatholysis may further detrimentally affect cardiac output in patients with this phenotype
Towards dense object tracking in a 2D honeybee hive
From human crowds to cells in tissue, the detection and efficient tracking of multiple objects in dense configurations is an important and unsolved problem. In the past, limitations of image analysis have restricted studies of dense groups to tracking a single or subset of marked individuals, or to coarse-grained group-level dynamics, all of which yield incomplete information. Here, we combine convolutional neural networks (CNNs) with the model environment of a honeybee hive to automatically recognize all individuals in a dense group from raw image data. We create new, adapted individual labeling and use the segmentation architecture U-Net with a loss function dependent on both object identity and orientation. We additionally exploit temporal regularities of the video recording in a recurrent manner and achieve near human-level performance while reducing the network size by 94% compared to the original U-Net architecture. Given our novel application of CNNs, we generate extensive problem-specific image data in which labeled examples are produced through a custom interface with Amazon Mechanical Turk. This dataset contains over 375,000 labeled bee instances across 720 video frames at 2FPS, representing an extensive resource for the development and testing of tracking methods. We correctly detect 96% of individuals with a location error of ~ 7% of a typical body dimension, and orientation error of 12°, approximating the variability of human raters. Our results provide an important step towards efficient image-based dense object tracking by allowing for the accurate determination of object location and orientation across time-series image data efficiently within one network architecture.Funding for this work was provided by the OIST Graduate
University to ASM and GS. Additional funding was provided by KAKENHI grants 16H06209 and 16KK0175 from
the Japan Society for the Promotion of Science to AS
On the linear fractional self-attracting diffusion
In this paper, we introduce the linear fractional self-attracting diffusion
driven by a fractional Brownian motion with Hurst index 1/2<H<1, which is
analogous to the linear self-attracting diffusion. For 1-dimensional process we
study its convergence and the corresponding weighted local time. For
2-dimensional process, as a related problem, we show that the renormalized
self-intersection local time exists in L^2 if .Comment: 14 Pages. To appear in Journal of Theoretical Probabilit
The influence of phosphonic acid protonation state on the efficiency of bis(diimine)copper(I) dye-sensitized solar cells
We present an investigation of the effects of a change in the protonation state of the phosphonic acid anchoring ligand in the dye [Cu(H 4 1 )( 2 )][PF 6 ] (H 4 1 = ((6,6'-dimethyl-[2,2'-bipyridine]-4,4'-diyl)bis(4,1-phenylene))bis(phosphonic acid), 2 = 4,4'-bis(4-bromophenyl)-6,6'-dimethyl-2,2'-bipyridine) on the performance of n-type dye-sensitized solar cells (DSCs). FTO/TiO 2 electrodes were immersed in solutions of H 4 1 in the presence of base (0–4 equivalents). TiO 2 -anchored heteroleptic copper(I) sensitizers were subsequently formed by ligand exchange between the homoleptic complex [Cu( 2 ) 2 ][PF 6 ] and the anchored ligand [H 4– n 1 ] n – . The results demonstrate that the addition of one equivalent of base during the initial surface functionalization can afford up to a 26% increase in DSC efficiency, while the addition of ≥3 equivalents of base significantly hinders DSC performance. Deprotonation of H 4 1 has been investigated using 1 H and 31 P NMR spectroscopic titrations. Further insight into DSC performance has been gained by using electrochemical impedance spectroscopy, and a comparison is made between DSCs in which the working electrodes are either pre-treated with a base, or exposed to a base post heteroleptic copper(I) dye-assembly
Distinct Fractions of an Artemisia scoparia Extract Contain Compounds With Novel Adipogenic Bioactivity
Adipocytes are important players in metabolic health and disease, and disruption of adipocyte development or function contributes to metabolic dysregulation. Hence, adipocytes are significant targets for therapeutic intervention in obesity and metabolic syndrome. Plants have long been sources for bioactive compounds and drugs. In previous studies, we screened botanical extracts for effects on adipogenesis in vitro and discovered that an ethanolic extract of Artemisia scoparia (SCO) could promote adipocyte differentiation. To follow up on these studies, we have used various separation methods to identify the compound(s) responsible for SCO's adipogenic properties. Fractions and subfractions of SCO were tested for effects on lipid accumulation and adipogenic gene expression in differentiating 3T3-L1 adipocytes. Fractions were also analyzed by Ultra Performance Liquid Chromatography- Mass Spectrometry (UPLC-MS), and resulting peaks were putatively identified through high resolution, high mass accuracy mass spectrometry, literature data, and available natural products databases. The inactive fractions contained mostly quercetin derivatives and chlorogenates, including chlorogenic acid and 3,5-dicaffeoylquinic acid, which had no effects on adipogenesis when tested individually, thus ruling them out as pro-adipogenic bioactives in SCO. Based on these studies we have putatively identified the principal constituents in SCO fractions and subfractions that promoted adipocyte development and fat cell gene expression as prenylated coumaric acids, coumarin monoterpene ethers, 6-demethoxycapillarisin and two polymethoxyflavones
Unraveling critical dynamics: The formation and evolution of topological textures
We study the formation of topological textures in a nonequilibrium phase
transition of an overdamped classical O(3) model in 2+1 dimensions. The phase
transition is triggered through an external, time-dependent effective mass,
parameterized by quench timescale \tau. When measured near the end of the
transition the texture separation and the texture width scale respectively as
\tau^(0.39 \pm 0.02) and \tau^(0.46 \pm 0.04), significantly larger than
\tau^(0.25) predicted from the Kibble-Zurek mechanism. We show that
Kibble-Zurek scaling is recovered at very early times but that by the end of
the transition the power-laws result instead from a competition between the
length scale determined at freeze-out and the ordering dynamics of a textured
system. In the context of phase ordering these results suggest that the
multiple length scales characteristic of the late-time ordering of a textured
system derive from the critical dynamics of a single nonequilibrium correlation
length. In the context of defect formation these results imply that significant
evolution of the defect network can occur before the end of the phase
transition. Therefore a quantitative understanding of the defect network at the
end of the phase transition generally requires an understanding of both
critical dynamics and the interactions among topological defects.Comment: 12 pages, revtex, 9 figures in eps forma
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