3,576 research outputs found
Energy-Efficient Design of STAR-RIS Aided MIMO-NOMA Networks
Simultaneous transmission and reflection-reconfigurable intelligent surface
(STAR-RIS) can provide expanded coverage compared with the conventional
reflection-only RIS. This paper exploits the energy efficient potential of
STAR-RIS in a multiple-input and multiple-output (MIMO) enabled non-orthogonal
multiple access (NOMA) system. Specifically, we mainly focus on
energy-efficient resource allocation with MIMO technology in the STAR-RIS
assisted NOMA network. To maximize the system energy efficiency, we propose an
algorithm to optimize the transmit beamforming and the phases of the low-cost
passive elements on the STAR-RIS alternatively until the convergence.
Specifically, we first decompose the formulated energy efficiency problem into
beamforming and phase shift optimization problems. To efficiently address the
non-convex beamforming optimization problem, we exploit signal alignment and
zero-forcing precoding methods in each user pair to decompose MIMO-NOMA
channels into single-antenna NOMA channels. Then, the Dinkelbach approach and
dual decomposition are utilized to optimize the beamforming vectors. In order
to solve non-convex phase shift optimization problem, we propose a successive
convex approximation (SCA) based method to efficiently obtain the optimized
phase shift of STAR-RIS. Simulation results demonstrate that the proposed
algorithm with NOMA technology can yield superior energy efficiency performance
over the orthogonal multiple access (OMA) scheme and the random phase shift
scheme
Solving Variational Inequalities Defined on A Domain with Infinitely Many Linear Constraints
We study a variational inequality problem whose domain
is defined by infinitely many linear inequalities. A
discretization method and an analytic center based
inexact cutting plane method are proposed. Under proper
assumptions, the convergence results for both methods are
given. We also provide numerical examples for the
proposed methods
Modeling, Analysis, and Optimization of Grant-Free NOMA in Massive MTC via Stochastic Geometry
Massive machine-type communications (mMTC) is a crucial scenario to support
booming Internet of Things (IoTs) applications. In mMTC, although a large
number of devices are registered to an access point (AP), very few of them are
active with uplink short packet transmission at the same time, which requires
novel design of protocols and receivers to enable efficient data transmission
and accurate multi-user detection (MUD). Aiming at this problem, grant-free
non-orthogonal multiple access (GF-NOMA) protocol is proposed. In GF-NOMA,
active devices can directly transmit their preambles and data symbols
altogether within one time frame, without grant from the AP. Compressive
sensing (CS)-based receivers are adopted for non-orthogonal preambles
(NOP)-based MUD, and successive interference cancellation is exploited to
decode the superimposed data signals. In this paper, we model, analyze, and
optimize the CS-based GF-MONA mMTC system via stochastic geometry (SG), from an
aspect of network deployment. Based on the SG network model, we first analyze
the success probability as well as the channel estimation error of the CS-based
MUD in the preamble phase and then analyze the average aggregate data rate in
the data phase. As IoT applications highly demands low energy consumption, low
infrastructure cost, and flexible deployment, we optimize the energy efficiency
and AP coverage efficiency of GF-NOMA via numerical methods. The validity of
our analysis is verified via Monte Carlo simulations. Simulation results also
show that CS-based GF-NOMA with NOP yields better MUD and data rate
performances than contention-based GF-NOMA with orthogonal preambles and
CS-based grant-free orthogonal multiple access.Comment: This paper is submitted to IEEE Internet Of Things Journa
Salvia miltiorrhiza aqueous root extract plays an important role in improving locomotor activity in rats with spinal cord injury
Purpose: To investigate the activity of the aqueous root extract of Salvia miltiorrhiza (S. miltiorrhiza) (Lamiaceae), collected from Anhui Province, China, for the treatment of spinal cord injury (SCI) in Sprague-Dawley (SD) rats.Methods: In total, 30 adult rats were selected and divided into three groups; normal control, untreated and treated. Aqueous root extract of S. miltiorrhiza was introduced intraperitoneally to the treated group. Basso, Beattie and Bresnahan rating scale (BBB) was used to evaluate improvement in locomotor activity after SCI. Total RNA was extracted from tissue sections using Sepasol (NacalaiTesque) and RNA samples were reverse-transcribed using M-MLV reverse transcriptase. BioSense SC-810 Gel Documentation System and Gel-Pro 3.1 software were employed for the analysis of band intensity.Results: A significant reduction in SCI cavity area was observed in the S. miltiorrhiza extract-treated group, relative to the untreated group, after 11 days (0.10 ± 0.05 mm2 treated vs. 0.30 ± 0.01 mm2 untreated). Treatment with root extract also improved the BBB scores; the treated group scored 15, compared to a score of 8 for the untreated group. In addition, the degradation of neurons at the site of injury in the spinal cord was reduced in the treated group compared to the untreated group. Treatment with S. miltiorrhiza aqueous root extract also significantly increased the expression of platelet-derived growth factor-B (PDGF-B) mRNA (p < 0.01).Conclusion: These data suggest that, in addition to other pharmacological activities, S. miltiorrhiza extract has therapeutic potential for the treatment of neuronal degeneration following SCI.Keywords: Salvia Miltiorrhiza, Neurons, Spinal cord injury, Locomotor capacity, Platelet-derived growth factor-B, Basso, Beattie and Bresnahan rating scal
Localized Langerhans cell histiocytosis masquerading as Brodie s abscess in a 2-year-old child: a case report
Langerhans cell histiocytosis (LCH), formerly known as histiocytosis X, refers to a spectrum of diseases characterized by idiopathic proliferation of histiocytes that produce either focal (localized LCH) or systemic manifestations (Hand–Schüller–Christian disease and Letterer–Siwe disease). Localized LCH accounts for approximately 60–70 % of all LCH cases. Osseous involvement is the most common manifestation and typically involves the flat bones, along with lesions of the skull, pelvis, and ribs. Localized LCH in bone shows a wide spectrum of clinical manifestations and radiologic features that may mimic those of infections as well as benign and malignant tumors. The diagnostic imaging findings of localized LCH are also diverse and challenging. The penumbra sign is a common and characteristic magnetic resonance imaging (MRI) feature of Brodie’s abscess, but is rarely seen in localized LCH. In this report, we describe a case of localized LCH misdiagnosed as Brodie’s abscess in a 2-year-old child based on clinical symptoms, laboratory findings, and pre-diagnostic MRI findings (penumbra sign). Therefore, the penumbra sign is not sufficient to clearly establish the diagnosis of Brodie’s abscess, and the differential diagnosis of localized LCH should be considered when a child with an osteolytic lesion presents with a penumbra sign
Microblog Rumor Detection Method Based on Propagation Path Tree Kernel Learning
The rapid development of online social platforms such as microblog promotes the widespread propagation of various rumors information,thereby posing potential threats to social order.Rumor detection on microblog can effectively curb the spread of rumors and is of great significance for purifying the network environment and maintaining social stability.In view of the fact that the traditional rumor detection model only considers the characteristics of users,contents and communication statistics,and ignores the structural problem that the characteristics of users′ influence and emotional feedback increase with the forwarding and comment relationship in the process of rumor communication,a path tree kernel rumor automatic detection model based on the microblog information propagation tree is proposed in this paper.It embeds users’ influence,emotional feedback,contents into the nodes ofpropagation tree.By calculating the path similarity from the root node to the leaf node in propagation tree,the similarity between the microblog information propagation tree structure is obtained.Furthermore,the model uses the support vector machine classifier based on the propagation path tree kernel todetect microblog rumors.Experimental results show that the accuracy of the proposed model reaches 93.5%,which is better than that of the rumor detection models without considering the structure of propagation path
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Determining surface structure and stability of ε-Fe2C, χ-Fe5C2, θ-Fe3C and Fe4C phases under carburization environment from combined DFT and atomistic thermodynamic studies
The chemical–physical environment around iron based FTS catalysts under working conditions is used to estimate the influences of carbon containing gases on the surface structures and stability of ε-Fe2C, χ-Fe5C2, θ-Fe3C and Fe4C from combined density functional theory and atomistic–thermodynamic studies. Higher carbon content gas has higher carburization ability; while higher temperature and lower pressure as well as higher H2/CO ratio can suppress carburization ability. Under wide ranging gas environment, ε-Fe2C, χ-Fe5C2 and θ-Fe3C have different morphologies, and the most stable non-stoichiometric termination changes from carbon-poor to carbon-rich (varying surface Fe/C ratio) upon the increase in ΔμC. The most stable surfaces of these carbides have similar surface bonding pattern, and their surface properties are related to some common phenomena of iron based catalysts. For these facets, χ-Fe5C2-(100)-2.25 is most favored for CO adsorption and CH4 formation, followed by θ-Fe3C-(010)-2.33, ε-Fe2C-(121)-2.00 and Fe4C-(100)-3.00, in line with surface work function and the charge of the surface carbon atoms
ATRW: A Benchmark for Amur Tiger Re-identification in the Wild
Monitoring the population and movements of endangered species is an important
task to wildlife conversation. Traditional tagging methods do not scale to
large populations, while applying computer vision methods to camera sensor data
requires re-identification (re-ID) algorithms to obtain accurate counts and
moving trajectory of wildlife. However, existing re-ID methods are largely
targeted at persons and cars, which have limited pose variations and
constrained capture environments. This paper tries to fill the gap by
introducing a novel large-scale dataset, the Amur Tiger Re-identification in
the Wild (ATRW) dataset. ATRW contains over 8,000 video clips from 92 Amur
tigers, with bounding box, pose keypoint, and tiger identity annotations. In
contrast to typical re-ID datasets, the tigers are captured in a diverse set of
unconstrained poses and lighting conditions. We demonstrate with a set of
baseline algorithms that ATRW is a challenging dataset for re-ID. Lastly, we
propose a novel method for tiger re-identification, which introduces precise
pose parts modeling in deep neural networks to handle large pose variation of
tigers, and reaches notable performance improvement over existing re-ID
methods. The dataset is public available at https://cvwc2019.github.io/ .Comment: ACM Multimedia (MM) 202
A Practical Guide for X-Ray Diffraction Characterization of Ga(Al, In)N Alloys
Ga(In, Al)N alloys are used as an active layer or cladding layer in light
emitting diodes and laser diodes. x-ray diffraction is extensively used to
evaluate the crystalline quality, the chemical composition and the residual
strain in Ga(Al,In)N thin films, which directly determine the emission
wavelength and the device performance. Due to the minor mismatch in lattice
parameters between Ga(Al, In)N alloy and a GaN virtual substrate, x-ray
diffraction comes to a problem to separate the signal from Ga(Al,In)N alloy and
GaN. We give a detailed comparison on different diffraction planes. In order to
balance the intensity and peak separation between Ga(Al,In)N alloy and GaN,
(0004) and (1015) planes make the best choice for symmetric scan and asymmetric
scan, respectively.Comment: 9 pages, 5 figure
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