Effect of trigger system on experimental dispersion characteristics of active surface wave testing

A trigger system is typically employed in active seismic testing to trigger and synchronize multichannel surface wave data acquisition.The effect of the trigger system on the dispersion image of surface waves is empirically known to be negligible,however,theoretical explanation regarding the effect of the trigger system is insufficient.This study systematically examines the theory for surface wave dispersion analysis and proves that the effect of the trigger system on a dispersion image is negligible via a solid theoretical explanation.Subsequently,based on the new theoretical explanation,an alternative method that uses only the relative phase difference between sensors to extract dispersion characteristics with better conceptual clarity is proposed.Two active surface wave testing cases are considered to validate the theory and method.The results indicate that(1)an accurate trigger system is not necessary for surface wave data acquisition,and(2)it is unnecessary to assume that the impact point is the generation point of the surface waves for the experimental dispersion analysis.

Distributed IRS-Aided DF Relaying Systems:Performance Analysis and Optimization

Intelligent reflecting surface(IRS)is a newly emerged and promising paradigm to substantially improve the performance of wireless communications by constructing favorable communication channels via properly tuning massive reflecting elements.This paper considers a distributed IRS aided decode-and-forward(DF)relaying system over Nakagami-m fading channels.Based on a tight approximation for the distribution of the received signalto-noise ratio(SNR),we first derive exact closed-form expressions of the outage probability,ergodic capacity,and energy efficiency for the considered system.Moreover,we propose the optimal IRS configuration considering the energy efficiency and pilot overhead.Finally,we compare the performance between the distributed IRS-aided DF relaying and multi-IRS-only systems,and verify the analytical results by using monte carlo simulations.

Channel Estimation for Reconfigurable Intelligent Surface Aided Multiuser Millimeter-Wave/THz Systems

It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.

Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each year.For this purpose,a proper condition monitoring system is essential to avoid accidents and heavy losses.Generally,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment.Therefore,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway track.The proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition process.The contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy regions.It works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black color.We have used the multiprocessing technique to overcome the massive processing and memory issues.This embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/h.The functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faults.An unhealthy frame’s onsite detection processing time was recorded at approximately 25.6ms.The proposed system can synchronize the acceleration data on specific railway track deformation.The proposed novel embedded system may be beneficial for detecting faults to overcome the conventional manual railway track condition monitoring,which is still being practiced in various developing or underdeveloped countries.

A testing system to understand rock fracturing processes induced by different dynamic disturbances under true triaxial compression

In this context,a testing system to understand rock fracturing processes induced by different dynamic disturbances under true triaxial compression was developed.The system is mainly composed of a static loading subsystem,a dynamic loading subsystem,a specimen box subsystem,and a data measurement subsystem.The static loading subsystem uses low stiffness loss frame structure technology,which greatly improves the frame stiffness in the three principal stress directions(up to 20 GN/m)and ensures the demand of the disturbance experiment in both the prepeak and postpeak stages.The disturbance loads with frequency of 0e20 Hz and stress level of 0e30 MPa were applied using large flow parallel oil source technology characterized with high heat dissipation efficiency.For the disturbance loads with frequency of 100e500 Hz and stress level of 0e30 MPa,they were realized by using high-frequency and centimeter-per-second-scale low-speed disturbance rod technology.Three rigid self-stabilizing specimen boxes were utilized to provide support for the specimen and deformation sensors,ensuring the stability and accuracy of the data obtained.To verify the performance of the true triaxial test system,disturbance experiments were conducted on granite specimens.The results show that the experimental device satisfies the requirements of original design,with an excellent repeatability and reliable testing results.

Recent progress in microbial cell surface display systems and their application on biosensors

Microbial cell surface display technology is a recombinant technology to express target proteins on the cell membrane,which can be used to redesign the cell surface with functional proteins and peptides.Bacterial and yeast surface display systems are the most common cell surface display systems of prokaryotic and eukaryotic proteins,that are widely applied as the core elements in the field of biosensors due to their advantages,including enhanced stability,high yield,good safety,expression of larger and more complex proteins.To further promote the performance of biosensors,the biomineralized microbial surface display technology was proposed.This review summarized the different microbial surface display systems and the biomineralized surface display systems,where the mechanisms of surface display and biomineralization were introduced.Then we described the recent progress of their applications on biosensors for different types of detection targets.Finally,the outlooks and tendencies were discussed and forecasted with the expectation to provide some general functions and enlightenments to this aspect of research.

Deep Reinforcement Learning Based Power Minimization for RIS-Assisted MISO-OFDM Systems

In this paper,we investigate the downlink orthogonal frequency division multiplexing(OFDM)transmission system assisted by reconfigurable intelligent surfaces(RISs).Considering multiple antennas at the base station(BS)and multiple single-antenna users,the joint optimization of precoder at the BS and the phase shift design at the RIS is studied to minimize the transmit power under the constraint of the certain quality-of-service.A deep reinforcement learning(DRL)based algorithm is proposed,in which maximum ratio transmission(MRT)precoding is utilized at the BS and the twin delayed deep deterministic policy gradient(TD3)method is utilized for RIS phase shift optimization.Numerical results demonstrate that the proposed DRL based algorithm can achieve a transmit power almost the same with the lower bound achieved by manifold optimization(MO)algorithm while has much less computation delay.

Combination of a reaction cell and an ultra-high vacuum system for the in situ preparation and characterization of a model catalyst

An in-depth understanding of the structure-activity relationship between the surface structure,chemical composition,adsorption and desorption of molecules,and their reaction activity and selectivity is necessary for the rational design of high-performance catalysts.Herein,we present a method for studying catalytic mechanisms using a combination of in situ reaction cells and surface science techniques.The proposed system consists of four parts:preparation chamber,temperatureprogrammed desorption(TPD)chamber,quick load-lock chamber,and in situ reaction cell.The preparation chamber was equipped with setups based on the surface science techniques used for standard sample preparation and characterization,including an Ar+sputter gun,Auger electron spectrometer,and a low-energy electron diffractometer.After a well-defined model catalyst was prepared,the sample was transferred to a TPD chamber to investigate the adsorption and desorption of the probe molecule,or to the reaction cell,to measure the catalytic activity.A thermal desorption experiment for methanol on a clean Cu(111)surface was conducted to demonstrate the functionality of the preparation and TPD chambers.Moreover,the repeatability of the in situ reaction cell experiment was verified by CO_(2) hydrogenation on the Ni(110)surface.At a reaction pressure of 800 Torr at 673 K,turnover frequencies for the methanation reaction and reverse water-gas shift reaction were 0.15 and 7.55 Ni atom^(-1) s^(-1),respectively.

Discrete Phase Shifts Control and Beam Selection in RIS-Aided MISO System via Deep Reinforcement Learning

Reconfigurable intelligent surface(RIS)for wireless networks have drawn lots of attention in both academic and industry communities.RIS can dynamically control the phases of the reflection elements to send the signal in the desired direction,thus it provides supplementary links for wireless networks.Most of prior works on RIS-aided wireless communication systems consider continuous phase shifts,but phase shifts of RIS are discrete in practical hardware.Thus we focus on the actual discrete phase shifts on RIS in this paper.Using the advanced deep reinforcement learning(DRL),we jointly optimize the transmit beamforming matrix from the discrete Fourier transform(DFT)codebook at the base station(BS)and the discrete phase shifts at the RIS to maximize the received signal-to-interference plus noise ratio(SINR).Unlike the traditional schemes usually using alternate optimization methods to solve the transmit beamforming and phase shifts,the DRL algorithm proposed in the paper can jointly design the transmit beamforming and phase shifts as the output of the DRL neural network.Numerical results indicate that the DRL proposed can dispose the complicated optimization problem with low computational complexity.

Performance Analysis of Intelligent Reflecting Surface Assisted Wireless Communication System

In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication systems.We consider a system in which an IRS is deployed on a uniform planar array(UPA)configuration,including a large number of reflecting elements,where the transmitters and receivers are only equipped with a single antenna.Our objective is to analytically obtain the achievable ergodic rate,outage probability,and bit error rate(BER)of the system.Furthermore,to maximize the system’s signal-to-noise ratio(SNR),we design the phase shift of each reflecting element and derive the optimal reflection phase of the IRS based on the channel state information(CSI).We also derive the exact expression of the SNR probability density function(p.d.f.)and show that it follows a non-central Chi-square distribution.Using the p.d.f.,we then derive the theoretical results of the achievable rate,outage probability,and BER.The accuracy of the obtained theoretical results is also verified through numerical simulation.Itwas shown that the achievable rate,outage probability,and BER could be improved by increasing the number of reflecting elements and choosing an appropriate SNR regime.Furthermore,we also find that the IRS-assisted communication system achieves better performance than the existing end-to-end wireless communication.

Differential Scheme for Reconfigurable Intelligent Surface-Based Spatial Modulation System

In this paper,a differential scheme is proposed for reconfigurable intelligent surface(RIS)assisted spatial modulation,which is referred to as RISDSM,to eliminate the need for channel state information(CSI)at the receiver.The proposed scheme is an improvement over the current differential modulation scheme used in RIS-based systems,as it avoids the high-order matrix calculation and improves the spectral efficiency.A mathematical framework is developed to determine the theoretical average bit error probability(ABEP)of the system using RIS-DSM.The detection complexity of the proposed RIS-DSM scheme is extremely low through the simplification.Finally,simulations results demonstrate that the proposed RIS-DSM scheme can deliver satisfactory error performance even in low signal-to-noise ratio environments.

Mathematical Modeling and Design of RIS Deployment in a RIS-Assisted Metal Cuboid for WAIC Systems

Wireless avionics intra-communications(WAIC)is an emergent research topic,since it can improve fuel efficiency and enhance aircraft safety significantly.However,there are numerous baffles in an aircraft,e.g.,seats and cabin bulkheads,resulting in serious blockage and even destroying wireless communications.Thus,this paper focuses on the reconfigurable intelligent surface(RIS)deployment issue of RIS-assisted WAIC systems,to solve the blockage problem caused by baffles.We first propose the mirror-symmetric imaging principle for mathematically analyzing electromagnetic(EM)wave propagation in a metal cuboid,which is a typical structure of WAIC systems.Based on the mirror-symmetric imaging principle,the mathematical channel model in a metal cuboid is deduced in detail.In addition,we develop an objective function of RIS's location and deduce the optimal RIS deployment location based on the geometric center optimization lemma.A two-dimensional gravity center search algorithm is then presented.Simulation results show that the designed RIS deployment can greatly increase the received power and efficiently solve the blockage problem in the aircraft.

Dynamics along the epithelial-cancer biointerface:Hidden system complexities

The biointerface dynamics influence any cancer spreading through the epithelium since it is documented in the early stages some malignancies(like epithelial cancer).The altered rearrangement of epithelial cells has an impact on the development of cancer.Therefore,it is necessary to comprehend the underlying biological and physical mechanisms of this biointerface dynamics for early suppression of cancer.While the biological mechanisms include cell signaling and gene expression,the physical mechanisms are several physical parameters such as the epithelial-cancer interfacial tension,epithelial surface tension,and compressive stress accumulated within the epithelium.Although the segregation of epithelia-cancer co-cultured systems was widely investigated,the role of these physical parameters in cell reorganization is still not fully recognized.Hence,this review is focused on clarifying the role that some physical parameters have during cell reorganization within the epithelial cell clusters and cancer spread within co-cultured spheroids.We have applied the developed biophysical model to point out the inter-relations among physical parameters that influence cell reorganization within epithelial-cancer co-cultured systems.The main results of this theoretical consideration have been assessed by integrating the biophysical model with biological and bio-mechanical experiments from the available literature.The epithelial-cancer interfacial tension leads to the reduction of the biointerface area,which leads to an increase in the compressive residual stress within the epithelial clusters depending on the viscoelasticity of the epithelial subpopulation.This stress impacts epithelial rearrangement and the dynamics along the biointerface by influencing the epithelial surface tension and epithelial-cancer interfacial tension.Further,the interrelation between the epithelial surface tension and epithelial-cancer interfacial tension influences the spread of cancer cells.

MUTS-Based Cooperative Target Stalking for A Multi-USV System

This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)system.Based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalking(MUTS)algorithm is proposed.Firstly,a V-type probabilistic data extraction method is proposed for the first time to overcome shortcomings of the MADDPG algorithm.The advantages of the proposed method are twofold:1)it can reduce the amount of data and shorten training time;2)it can filter out more important data in the experience buffer for training.Secondly,in order to avoid the collisions of USVs during the stalking process,an action constraint method called Safe DDPG is introduced.Finally,the MUTS algorithm and some existing algorithms are compared in cooperative target stalking scenarios.In order to demonstrate the effectiveness of the proposed MUTS algorithm in stalking tasks,mission operating scenarios and reward functions are well designed in this paper.The proposed MUTS algorithm can help the multi-USV system avoid internal collisions during the mission execution.Moreover,compared with some existing algorithms,the newly proposed one can provide a higher convergence speed and a narrower convergence domain.

Intelligent reflecting surface-assisted cognitive radio-inspired rate-splitting multiple access systems

Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a cognitive radio-inspired rate-splitting multiple access(CR-RSMA)system in which a primary user's(PU's)quality of service(QoS)requirements must be guaranteed.Without introducing intolerable interference to deteriorate the PU's outage performance,the SU conducts rate-splitting to transmit its signal to the base-station through the direct link and IRS reflecting channels.For the IRS-assisted CR-RSMA(IRS-CR-RSMA)scheme,we derive the optimal transmit power allocation,target rate allocation,and successive interference cancellation decoding order to enhance the outage performance of the SU.The closed-form expression for the SU's outage probability achieved by the IRS-CR-RSMA scheme is derived.Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed IRS-CR-RSMA scheme over the CR-RSMA scheme.

Non-Contact System for Global Reporting Format (GRF) Automation: Contaminant Body Detection and Depth Estimation in the Case of Rainy Weather

The paper designed a non-contact system in order to perform the application (on a runway) of the Global Reporting Format (GRF) developed by International Civil Aviation Organization (ICAO). The system involves devices that film the surface (a runway in our case) from the air and displays the contaminant (water) body and measures the depth of the water automatically during the inspection. While measuring, data are sent to a computer used as a receiver. The developed devices are automatic devices implemented specially to use during rainy weather or even for some other cases. The aerial system uses a raspberry pi 4 model B, a camera, a laser sensor, an ultrasonic module, a Virtual Network Computing (VNC) and python codes developed by the authors. Results obtained show that using these devices to retrieve the Runway Condition Report (RCR) is very fast and human presence on the runway is not needed. The results obtained using these devices show that the method used herein is a proper solution to the GRF issues in the rainy areas, where the contaminant body detection and the accurate depth measurement were not well estimated because of the lack of a suitable method.

Structural properties of residual carbon in coal gasification fine slag and their influence on flotation separation and resource utilization:A review

Coal gasification fine slag(FS)is a typical solid waste generated in coal gasification.Its current disposal methods of stockpil-ing and landfilling have caused serious soil and ecological hazards.Separation recovery and the high-value utilization of residual carbon(RC)in FS are the keys to realizing the win-win situation of the coal chemical industry in terms of economic and environmental benefits.The structural properties,such as pore,surface functional group,and microcrystalline structures,of RC in FS(FS-RC)not only affect the flotation recovery efficiency of FS-RC but also form the basis for the high-value utilization of FS-RC.In this paper,the characteristics of FS-RC in terms of pore structure,surface functional groups,and microcrystalline structure are sorted out in accordance with gasification type and FS particle size.The reasons for the formation of the special structural properties of FS-RC are analyzed,and their influence on the flotation separation and high-value utilization of FS-RC is summarized.Separation methods based on the pore structural characterist-ics of FS-RC,such as ultrasonic pretreatment-pore-blocking flotation and pore breaking-flocculation flotation,are proposed to be the key development technologies for improving FS-RC recovery in the future.The design of low-cost,low-dose collectors containing polar bonds based on the surface and microcrystalline structures of FS-RC is proposed to be an important breakthrough point for strengthening the flotation efficiency of FS-RC in the future.The high-value utilization of FS should be based on the physicochemical structural proper-ties of FS-RC and should focus on the environmental impact of hazardous elements and the recyclability of chemical waste liquid to es-tablish an environmentally friendly utilization method.This review is of great theoretical importance for the comprehensive understand-ing of the unique structural properties of FS-RC,the breakthrough of the technological bottleneck in the efficient flotation separation of FS,and the expansion of the field of the high value-added utilization of FS-RC.

Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of Vehicles

High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.

Surface-modified Ag@Ru-P25 for photocatalytic CO_(2) conversion with high selectivity over CH_(4) formation at the solid–gas interface

Systematic optimization of the photocatalyst and investigation of the role of each component is important to maximizing catalytic activity and comprehending the photocatalytic conversion of CO_(2) reduction to solar fuels.A surface-modified Ag@Ru-P25 photocatalyst with H_(2)O_(2) treatment was designed in this study to convert CO_(2) and H_(2)O vapor into highly selective CH4.Ru doping followed by Ag nanoparticles(NPs)cocatalyst deposition on P25(TiO_(2))enhances visible light absorption and charge separation,whereas H_(2)O_(2) treatment modifies the surface of the photocatalyst with hydroxyl(–OH)groups and promotes CO_(2) adsorption.High-resonance transmission electron microscopy,X-ray photoelectron spectroscopy,X-ray absorption near-edge structure,and extended X-ray absorption fine structure techniques were used to analyze the surface and chemical composition of the photocatalyst,while thermogravimetric analysis,CO_(2) adsorption isotherm,and temperature programmed desorption study were performed to examine the significance of H_(2)O_(2) treatment in increasing CO_(2) reduction activity.The optimized Ag1.0@Ru1.0-P25 photocatalyst performed excellent CO_(2) reduction activity into CO,CH4,and C2H6 with a~95%selectivity of CH4,where the activity was~135 times higher than that of pristine TiO_(2)(P25).For the first time,this work explored the effect of H_(2)O_(2) treatment on the photocatalyst that dramatically increases CO_(2) reduction activity.

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.