21,740 research outputs found
A rapid cosmic-ray increase in BC 3372-3371 from ancient buried tree rings in China
Cosmic rays interact with the Earth's atmosphere to produce C, which
can be absorbed by trees. Therefore, rapid increases of C in tree rings
can be used to probe previous cosmic-ray events. By this method, three C
rapidly increasing events have been found. Plausible causes of these events
include large solar proton events, supernovae or short gamma-ray bursts.
However, due to the lack of measurements of C by year, the occurrence
frequency of such C rapidly increasing events is poorly known. In
addition, rapid increases may be hidden in the IntCal13 data with five-year
resolution. Here we report the result of C measurements using an ancient
buried tree during the period between BC 3388 and 3358. We find a rapid
increase of about 9\textperthousand~ in the C content from BC 3372 to BC
3371. We suggest that this event could originate from a large solar proton
event.Comment: 23 pages, 3 figures, 2 tables, published in Nature Communication
Ambiguities in recurrence-based complex network representations of time series
Recently, different approaches have been proposed for studying basic
properties of time series from a complex network perspective. In this work, the
corresponding potentials and limitations of networks based on recurrences in
phase space are investigated in some detail. We discuss the main requirements
that permit a feasible system-theoretic interpretation of network topology in
terms of dynamically invariant phase-space properties. Possible artifacts
induced by disregarding these requirements are pointed out and systematically
studied. Finally, a rigorous interpretation of the clustering coefficient and
the betweenness centrality in terms of invariant objects is proposed
Vector magnetic field sensing by single nitrogen vacancy center in diamond
In this Letter, we proposed and experimentally demonstrated a method to
detect vector magnetic field with a single nitrogen vacancy (NV) center in
diamond. The magnetic field in parallel with the axis of the NV center can be
obtained by detecting the electron Zeeman shift, while the Larmor precession of
an ancillary nuclear spin close to the NV center can be used to measure the
field perpendicular to the axis. Experimentally, both the Zeeman shift and
Larmor precession can be measured through the fluorescence from the NV center.
By applying additional calibrated magnetic fields, complete information of the
vector magnetic field can be achieved with such a method. This vector magnetic
field detection method is insensitive to temperature fluctuation and it can be
applied to nanoscale magnetic measurement.Comment: 5 pages, 5 figure
Cross-Task Transfer for Geotagged Audiovisual Aerial Scene Recognition
Aerial scene recognition is a fundamental task in remote sensing and has
recently received increased interest. While the visual information from
overhead images with powerful models and efficient algorithms yields
considerable performance on scene recognition, it still suffers from the
variation of ground objects, lighting conditions etc. Inspired by the
multi-channel perception theory in cognition science, in this paper, for
improving the performance on the aerial scene recognition, we explore a novel
audiovisual aerial scene recognition task using both images and sounds as
input. Based on an observation that some specific sound events are more likely
to be heard at a given geographic location, we propose to exploit the knowledge
from the sound events to improve the performance on the aerial scene
recognition. For this purpose, we have constructed a new dataset named AuDio
Visual Aerial sceNe reCognition datasEt (ADVANCE). With the help of this
dataset, we evaluate three proposed approaches for transferring the sound event
knowledge to the aerial scene recognition task in a multimodal learning
framework, and show the benefit of exploiting the audio information for the
aerial scene recognition. The source code is publicly available for
reproducibility purposes.Comment: ECCV 202
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