254 research outputs found
Throughput of Hybrid UAV Networks with Scale-Free Topology
Unmanned Aerial Vehicles (UAVs) hold great potential to support a wide range
of applications due to the high maneuverability and flexibility. Compared with
single UAV, UAV swarm carries out tasks efficiently in harsh environment, where
the network resilience is of vital importance to UAV swarm. The network
topology has a fundamental impact on the resilience of UAV network. It is
discovered that scale-free network topology, as a topology that exists widely
in nature, has the ability to enhance the network resilience. Besides,
increasing network throughput can enhance the efficiency of information
interaction, improving the network resilience. Facing these facts, this paper
studies the throughput of UAV Network with scale-free topology. Introducing the
hybrid network structure combining both ad hoc transmission mode and cellular
transmission mode into UAV Network, the throughput of UAV Network is improved
compared with that of pure ad hoc UAV network. Furthermore, this work also
investigates the optimal setting of the hop threshold for the selection of ad
hoc or cellular transmission mode. It is discovered that the optimal hop
threshold is related with the number of UAVs and the parameters of scale-free
topology. This paper may motivate the application of hybrid network structure
into UAV Network.Comment: 15 pages, 7 figure
Optimization of Protein-Protein Interaction Measurements for Drug Discovery Using AFM Force Spectroscopy
Increasingly targeted in drug discovery, protein-protein interactions challenge current high throughput screening technologies in the pharmaceutical industry. Developing an effective and efficient method for screening small molecules or compounds is critical to accelerate the discovery of ligands for enzymes, receptors and other pharmaceutical targets. Here, we report developments of methods to increase the signal-to-noise ratio (SNR) for screening protein-protein interactions using atomic force microscopy (AFM) force spectroscopy. We have demonstrated the effectiveness of these developments on detecting the binding process between focal adhesion kinases (FAK) with protein kinase B (Akt1), which is a target for potential cancer drugs. These developments include optimized probe and substrate functionalization processes and redesigned probe-substrate contact regimes. Furthermore, a statistical-based data processing method was developed to enhance the contrast of the experimental data. Collectively, these results demonstrate the potential of the AFM force spectroscopy in automating drug screening with high throughput
Symbol-level Integrated Sensing and Communication enabled Multiple Base Stations Cooperative Sensing
With the support of integrated sensing and communication (ISAC) technology,
mobile communication system will integrate the function of wireless sensing,
thereby facilitating new intelligent applications such as smart city and
intelligent transportation. Due to the limited sensing accuracy and sensing
range of single base station (BS), multi-BS cooperative sensing can be applied
to realize high-accurate, long-range and continuous sensing, exploiting the
specific advantages of large-scale networked mobile communication system. This
paper proposes a cooperative sensing method suitable to mobile communication
systems, which applies symbol-level sensing information fusion to estimate the
location and velocity of target. With the demodulation symbols obtained from
the echo signals of multiple BSs, the phase features contained in the
demodulation symbols are used in the fusion procedure, which realizes
cooperative sensing with the synchronization level of mobile communication
system. Compared with the signal-level fusion in the area of distributed
aperture coherence-synthetic radars, the requirement of synchronization is much
lower. When signal-to-noise ratio (SNR) is -5 dB, it is evaluated that
symbol-level multi-BS cooperative sensing effectively improves the accuracy of
distance and velocity estimation of target. Compared with single-BS sensing,
the accuracy of distance and velocity estimation is improved by 40% and 72%,
respectively. Compared with data-level multi-BS cooperative sensing based on
maximum likelihood (ML) estimation, the accuracy of location and velocity
estimation is improved by 12% and 63%, respectively. This work may provide a
guideline for the design of multi-BS cooperative sensing system to exploit the
widely deployed networked mobile communication system.Comment: 15 pages, 17 figures, 2 table
Lightweight Structure-aware Transformer Network for VHR Remote Sensing Image Change Detection
Popular Transformer networks have been successfully applied to remote sensing
(RS) image change detection (CD) identifications and achieve better results
than most convolutional neural networks (CNNs), but they still suffer from two
main problems. First, the computational complexity of the Transformer grows
quadratically with the increase of image spatial resolution, which is
unfavorable to very high-resolution (VHR) RS images. Second, these popular
Transformer networks tend to ignore the importance of fine-grained features,
which results in poor edge integrity and internal tightness for largely changed
objects and leads to the loss of small changed objects. To address the above
issues, this Letter proposes a Lightweight Structure-aware Transformer (LSAT)
network for RS image CD. The proposed LSAT has two advantages. First, a
Cross-dimension Interactive Self-attention (CISA) module with linear complexity
is designed to replace the vanilla self-attention in visual Transformer, which
effectively reduces the computational complexity while improving the feature
representation ability of the proposed LSAT. Second, a Structure-aware
Enhancement Module (SAEM) is designed to enhance difference features and edge
detail information, which can achieve double enhancement by difference
refinement and detail aggregation so as to obtain fine-grained features of
bi-temporal RS images. Experimental results show that the proposed LSAT
achieves significant improvement in detection accuracy and offers a better
tradeoff between accuracy and computational costs than most state-of-the-art CD
methods for VHR RS images
Suspension and Measurement of Graphene and Bi2Se3 Atomic Membranes
Coupling high quality, suspended atomic membranes to specialized electrodes
enables investigation of many novel phenomena, such as spin or Cooper pair
transport in these two dimensional systems. However, many electrode materials
are not stable in acids that are used to dissolve underlying substrates. Here
we present a versatile and powerful multi-level lithographical technique to
suspend atomic membranes, which can be applied to the vast majority of
substrate, membrane and electrode materials. Using this technique, we
fabricated suspended graphene devices with Al electrodes and mobility of 5500
cm^2/Vs. We also demonstrate, for the first time, fabrication and measurement
of a free-standing thin Bi2Se3 membrane, which has low contact resistance to
electrodes and a mobility of >~500 cm^2/Vs
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