Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the coral microbiome at the scale of tissue-specific habitats within the coral meta-organism

As sequencing techniques have advanced and become cheaper in recent years, there has been a rapid increase in the number of studies conducted into the role of the microbiome in coral health, physiology, and response to environmental change. However, there is substantial variation in the methodological approaches applied. For example, DNA extraction protocols and the types of tissues sampled from the coral meta-organism are known to influence the downstream analyses of the amplified microbial communities and subsequently the interpretation of the microbiome diversity, stability and role. Studies have generally focused on whole organisms, in which the coral sampling steps homogenize the meta-organism microhabitats, however other studies targeting specific microhabitats have identified sources of variation specific to distinct compartments of the coral’s microbial landscape. Here we present a comparative analysis of methodologies optimized for the generation of coral microbiome data from the coral tissues and whole coral fragments of two commonly studied branching coral genera with distinct tissue structure. We investigate the microbiome of the imperforate Pocillopora, where the coral tissue does not penetrate through the calcium carbonate matrix, and the perforate Acropora, where the coral tissues and skeleton are interwoven throughout the coral branch. Through comparing data generated from different DNA extraction protocols using fixed coral tissues isolated from the coral skeletal structure with fixed whole coral fragments, we identify sources of variation inherent to microbial data generated from different sample types, species, and extraction protocols.
Commentary: Targeting the MRI-mapped psychopathology of major psychiatric disorders with neurostimulation

COPYRIGHT © 2022 Xie, Cui, Cao, Gu, Fan, Ren, Liu, Zhao, Shi, Yang, Jin, Li, Song, Yin, Cao, Li and Cui. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Commentary: Targeting the MRI-mapped psychopathology of major psychiatric disorders with neurostimulation
Psychological readiness to return to sports practice and risk of recurrence: Case studies

Returning to sport after the sports injury is a difficult decision because it’s multicausal and the fact that a rash decision can result in numerous negative consequences. Given the importance of psychological variables for the correct rehabilitation of the injured athlete and his or her optimal return to sports practice, there seems to be little information on this subject. In this sense, the objective is to determine the relationship between the subjective psychological disposition of the athlete in the process of Return to Play (RTP) with the type of mood profile and his mental health. This is based on the fact that each athlete evaluates his or her recovery differently and has different levels of anxiety, depression, and stress. For this purpose, four athletes participated in the study. Two males and two females from the sports of indoor soccer and soccer, who had just returned to sports after a moderate or severe injury. The average age was 24.25 years. Various measurements were taken after practices and after matches, to assess mood, psychological readiness, anxiety, stress, and depression. The results confirm Morgan’s iceberg profile and the influence that subjective psychological perceptions and assessed emotional states have on athletes’ incorporation into their sports practice with a guarantee of success.
Aperture synthesis observations of H II regions. I. A group of H II regions around l = 111

Aperture synthesis observations at 21 cm are presented of a group of H II regions situated in a 2 deg x 2 deg area around 1 = 111 deg in the Perseus Arm. The beamwidth used was 24" x 28". The group contains the well known objects NGC 7538, the Bubble Nebula NGC 7635, and S 157. Radial velocity data suggest that all regions are close together. All regions of the group seem to be younger than 10/sup 8/ yr, but their apparent ages vary considerably. In general a very good correlation is found between optical and radio features. Three small H II regions of size approx equal 0.5 pc appear to have emission measures in excess of 10/sup 6/ cm/sup -6/ pc; in this they resemble the Orion nebula. Two regions are of larger size (3 and 7 pc). In addition two optically invisible, point-like sources, that are obscured by local dark matter, are found. Very likely both sources are cocoon stars similar to W 3 OH. The total group of H II regions may be a loose OB association in statu nascendi. (auth)
Rethinking Energy Efficiency Models of Cellular Networks with Embodied Energy

scientists have suggested many approaches to reduce the energy consumption of BSs. In new sectors (e.g., mobile telephony), optimizing operating energy consumption usually precedes optimization including the embodied energy. Besides environmental concerns, the major objective for oper- ators is OPEX reduction. While operating energy consumption has a direct impact on cost, embodied energy only has an indirect one depending on the pricing policy of the manufacturer. Another important reason to start with optimizing oper- ating energy consumption is the risk of making operating energy consumption so high that it becomes difficult to supply all the energy required. Abstract The continuous increase in energy consumption by cellular networks requires rethinking their energy efficiency. Current research indicates that one third of operating energy could be saved by reducing the transmission power of base stations. However, this approach requires the introduction of a range of additional equipment containing more embodied energy — consumed by all processes associated with the production of equipment. This problem is addressed first in this article. Fur-thermore, a new cellular network energy efficiency model with embodied energy is proposed, and optimization between the number of cells and their coverage is investigated. Contrary to previous works, we have found that embodied energy accounts for a significant proportion of total energy consumption and cannot be neglected. The simulation results confirm an important trade-off between operating and embodied energies, which can provide some practical guidelines for design-ing energy-efficient cellular access networks. The new model considering embodied energy is not limited to just cellular networks, but to other telecommunications, such as wireless local area networks and wired networks.
Graph Expression for Various Software Documents As Unified Format

We are developing an educational environment system named VRale-SCM to foster IT engineers necessary for the recent information society. VRale-SCM allows students to deepen their understanding by viewing source code and class diagrams in a virtual space. In this paper, we examined the possibility of using graphs to represent not only source code and class diagrams but also various software documents generated during the software development lifecycle as a framework for viewing them in a virtual space. While there have been attempts to represent individual software documents using a graph, there have been no attempts to represent relationships among these software documents. It will become possible to trace their relationships by interconnecting them, which is expected to facilitate the understanding of the students. In this paper, we shall examine the composition of some of the software documents in each process and attempt to represent the source code and design patterns in the graphs. We shall also check them with visualization tools. Using the graph representation is expected to contribute to understanding by presenting various metrics by applying the analysis in existing studies.
Validation of selected models of the magnetization curve of ferrite cores

In the paper, selected models of the magnetization curve of ferrite cores were analyzed and compared. Such models are characterized by a small number of parameters and easy description that could be implemented in the SPICE. Among others, classic models such as the Rayleigh model, the Frolich model and their modifications were considered. Calculations with the use of selected models were carried out for the ferrite material F867. The obtained results were compared with the catalog data.
Poisson Game with Population Uncertainty for Mobile Edge Computing Networks

Mobile Edge Computing (MEC) networks are developing toward a large-scale, highly dynamic, distributed, and heterogeneous network. With the increasing scale of MEC, the types of devices accessing the MEC become more and more diverse, and the number of devices is uncertain. Meanwhile, for the lack of effective coordinated mechanisms among heterogeneous devices, severe network load imbalance issues will occur. To tackle this problem, this work proposes a cybertwin-enabled coordinated access strategy for heterogeneous devices with an uncertain number of devices. Specifically, the edge cloud access strategy problem is first modeled as a Poisson game, and the edge cloud network load balance is implemented by solving the equilibrium of this game. Then, the equilibrium conditions of this game are given, and the existence and uniqueness of the equilibrium are further proved. Moreover, a distributed iterative algorithm is proposed to seek the equilibrium efficiently. Finally, simulation results verify that the proposed strategy can reduce the average accessing queuing probability of edge cloud, and balance the load of the edge cloud network.
Image Quality SAR Refocus of Moving Targets undergoing Complicated Rolling Maneuvers

Moving targets typically appear smeared in synthetic aperture radar (SAR) imagery, often making the task of target recognition more difficult. Recently, research has yielded an ability to perform Arbitrary Rigid Object Motion Autofocus (AROMA) to generate automatically focused target images for cases of arbitrary target rotation and translation during the coherent processing interval of SAR collections. The current research analyzes the efficacy of AROMA processing for targets undergoing complicated rolling maneuvers against a background of measured Ku-band image clutter. The results of this analysis reveal that AROMA can yield focused target imagery that correlates well with the true structure of the target.
A Spatial Filtering Antenna based on Dielectric Resonator Loaded Spoof Surface Plasmon Polaritons Waveguide

With the rapid development of wireless communication technology, the channel environment of system is full of more and more noise and congestion. Spatial filtering antennas which allow the transmission of energy within a specified angular domain while inhibiting the transmission of energy outside the specified spatial range is beneficial to improve the stability of communication equipment. Flat-topped antennas with uniform illumination, fast roll-off and low sidelobe-levels (SLLs) can act as spatial filtering antennas. In this work, the spatial filtering antenna based on dielectric resonator (DR) loaded spoof surface plasmon polaritons (SSPP) waveguide operating at 5.7 GHz is designed. The DR is loaded on the surface of SSPP waveguide and fed by microstrip line. By exciting the leaky wave radiation of SSPP waveguide and $\text{HE}_{11\delta}$ radiation of DRA, flat-top pattern can be obtained based on the principle of patterns superposition. The comparison between the proposed antenna and relevant works implies that the compactness in structure of the proposed antenna.
Application of Bioinspired Antennas in the Monitoring of High Voltage Circuit Breakers

This paper presents a technique for circuit breaker radiometric monitoring using broadband plana monopole antennas (PMA). Considering that this work represents the continuity of a previous research, the antenna has been miniaturized using a bioinspired geometry based on the Acer Macrophyllum leaf. The monitoring system consists in measuring the signal radiated by electric arcs in circuit breaker poles during its switching operations. By analyzing these signals, it is possible to evaluate, non-intrusively, the equipment electric and mechanical status, providing important information to maintenance crews regarding the need for interventions. By performing laboratory tests, it was confirmed that the developed bioinspired PMA has adequate gain values, radiation pattern and frequency range to circuit breaker monitoring applications. Moreover, field tests on a 230 kV SF6 circuit breaker were carried out, from which the proposed technique applicability was confirmed. The proposed monitoring technique can be considered a continuous and non-invasive solution, since the antennas can be placed at a safe distance from the equipment under analysis, without compromising the insulation. In the substation, the technique has the potential to detect problems of electrical and mechanical nature, since important operational parameters can be detected, such as opening time and pole synchronicity.
An Iterative Receiver With Orthogonal AMP-Based Equalization for Doubly Selective Fading Channels

The emerging need for high-mobility and broadband communications has brought intensive research interest to doubly selective fading channels. To improve the transmission efficiency and reliability over the doubly selective fading channels, we propose an iterative receiver design, and consider the information exchange between different receiver modules, i.e. the channel estimator, the equalizer, and the channel decoder. Specifically, we first quantify the noise level from the output of the channel estimator for the data detection at the equalizer. Then, we employ the orthogonal approximate message passing (OAMP) algorithm for equalization, which could break the limits of IID measurement matrix for the existing AMP algorithm, and therefore works better for multi-path channel matrix with correlated entries. Next, we propose the channel interpolation and decoding feedback strategies to alleviate the impacts of the time-varying channels, which facilitates efficient transmission with short pilot sequences. Finally, simulations are provided to show the benefits of our proposed strategies, as well as the superior performances of the proposed iterative receiver design.
Multi-Carrier Differential Chaos Shift Keying Modulation with Permutation Index

This paper proposes a multi-carrier differential chaos shift keying modulation using permutation index (PI-MC-DCSK) over multipath fading and additive white Gaussian noise (AWGN) channels, by exploiting the advantages of permutation index and multi-carrier modulations. In the proposed PI-MC-DCSK, the predefined subcarriers, can carry multiple bits associated with the order of permutation index, which can achieve high energy efficiency as compared to the one bit carried by each subcarrier in the conventional MC-DCSK. At the transmitter, the first predefined subcarrier stores reference data, while the rest carry data signal. Then, the transmission energy of the system can be significantly saved. At the receiver, received data passes through the multi-carrier demodulator, and the mapped bits are estimated by the correlators. Simulation results show that the proposed PI-MC-DCSK has excellent error performance and provides a much higher data rate than the conventional MC-DCSK.
Joint Computing, Caching and Communication Resource Allocation in the Satellite-Terrestrial Integrated Network with UE Cooperation

The future satellite-terrestrial integrated network (STIN) will provide continuous and reliable high-quality services for user equipment (UE). In order to support diverse computing-intensive mobile applications, it is necessary to jointly optimize the allocation of communication, computing, and caching (3C) resources to improve resource utilization in the STIN. However, heterogeneous nodes have differences in performance, resources, and locations. It increases the complexity of 3C resource allocation and makes the existing algorithms for the terrestrial network no longer applicable. This paper considers the multiple coverages and resource heterogeneity of the STIN to investigate the 3C resource allocation problem for offloading computing-intensive services. In the modeling, we consider the service caching environment and overhead of various computing services on edge nodes. Then the strategy that the executive codes of computing services are transmitted by UE cooperation is proposed to reduce the average delay of tasks. The 3C resource allocation problem is formulated as a mixed-integer nonlinear programming problem to minimize the average delay of tasks and improve the utilization of 3C resources. By introducing the non-dominated sorting genetic algorithm II (NSGAII) to solve the above problems, the approximate optimal solution is obtained by searching for feasible solutions with limited iterations, and the balance between optimization target and time complexity is achieved. Simulation results show that the proposed resource allocation algorithm can reduce the computing resources required to execute the tasks and the average delay of tasks.
UAV Millimeter-Wave Beam Training Based on Adaptive Sensing

Unmanned aerial vehicle (UAV) millimeter wave (mmWave) communication with narrow beam has faced challenge lead by UAV high speed mobility and jittering. In this paper, we design an adaptive sensing matrix for UAV beam training based on compressed sensing (CS) to overcome the misalignment problem, and propose a noise average measurement scheme to suppress the noise. First, we model AoA/AoD estimation as a sparse signal recovery problem, where the attitude variations are taken into account in channel model. Particularly, we narrow down the range of sensing matrix adaptively with historical navigation information at UAV side to improve the quality of CS reconstruction. Then, measured by the same sensing matrix, we adopt the gradient descent search algorithm to refine the AoA/AoD with the average of measured signals. Numerical results show the superiority of our proposed sensing matrix and verify the performance gain brought by average noise measurement.
Spectral Graph Theory-Based Recovery Method for Missing Harmonic Data

In large-scale applications, parts of harmonic data are inevitably lost during transmission. This study presents an approach for the recovery of missing harmonic data based on the spectral graph theory. The proposed methodology involves graph theory for constructing a Laplacian matrix and a graph signal reconstruction function, the merging K-means algorithm for building a priori information model, and the accelerated segmentation Bregman iterative algorithm for solving the reconstruction function. Compared with existing methods on data recovery in power systems, the method maintains a good recovery accuracy when the data correlation of measurement units is low and the prior information is little. The proposed method has good anti-noise performances and low computational complexity. The feasibility and accuracy of the proposed method are verified through simulation and field recorded data.
Analysis of Demand Response Scenarios by Industrial Consumers Using Artificial Electric Power Market Simulations

This study analyzed the effect of demand response (DR) on the electric power market using a multi-agent simulation. Firstly, we built a multi-agent simulation for the electric power market based on the data of the Japan electric power exchange market (JEPX) and a factory. Using the multi-agent simulation, we tested possible DR scenarios. We then compared these scenarios in terms of the two metrics, which are newly defined in this study: cost and CO2 emission reduction efficiencies. The findings of this study are as follows: working time shift in the summer showed the best performance in the reduction in cost and CO2. However, the best performance in the winter was achieved by peak-shift of the factory demand based on indices. Through this study, we considered the electric power features of both the seasons and time of the day in the simulation and investigated the effects of complex DR scenarios using multi-agent simulation.
Single Eigenmode Excited Low Profile Ultra-wideband Vertically Polarized Omnidirectional Antenna

An ultra-wideband vertically polarized omnidirectional antenna is proposed. The intrinsic properties of the patch are analyzed by characteristic mode analysis, and the omnidirectional mode radiation is found. The ultra-wideband vertical polarization omnidirectional antenna is realized by using a single probe feed structure to excite. The simulation results show that the impedance bandwidth of the antenna can reach 56.3% (8.48-15.13GHz) and the profile height is 0.11 $\lambda_{0}(\lambda_{0}$ is the wavelength of 8.48GHz).
Solution adaptive cartesian grid methods for aerodynamic flows with complex geometries

Cartesian methods for computational fluid dynamics are considered to offer an accurate and robust approach for the simulation of aerodynamic flows around geometrically complex bodies. A part of the ongoing research in this domain is reviewed with the aim of providing insight into the fundamental challenges faced by the practitioners of this approach, and a guide to further research. The integration schemes used in Cartesian solvers are similar to those used in other approaches. The emphasis is on the geometric algorithms, surface modeling and boundary conditions required to design a successful Cartesian mesh scheme.
Trade-off between Secrecy Rate and Energy Consumption in a Secure UAV- MEC System

Unmanned aerial vehicles (UAV) used as the mobile edge computing (MEC) platform is capable of providing flexible offloading tasks, but is also facing the risk of being wiretapped by nearby eavesdroppers (Eves). In this paper, we investigate a full-duplex UAV to interfere with Eves by sending jamming signals while simultaneously processing the offloading tasks, which saves more resources overhead compared with introducing an extra jamming UAV. To trade off between the secrecy rate and energy consumption of the secure UAV-enabled MEC system, we formulate a multi-objective optimization problem aiming to maximize the average secrecy rate of the system while consuming the minimum energy of users. With the constraints of task latency requirement, the energy consumption of the legitimate UAV and the maximum capacity of self-executed tasks, the proposed multi-objective problem is also non-convex. To solve this issue, an alternating algorithm based on the successive convex approximating (SCA) method is proposed to optimize the parameters iteratively. The simulation results demonstrate that the significant performance improvement can be achieved by our proposed algorithm over the baseline schemes.