3D electromagnetic simulation of the coupling characteristics and double-stub Ferrite tuners impedance matching for EAST ICRH four-strap antenna

A program developed with COMSOL software integrates EAST four-strap antenna coupling with the double-stub Ferrite tuners(FT)impedance matching,obtaining physical quantities crucial for predicting the overall performance of the ion cyclotron resonance heating(ICRH)antenna and matching system.These quantities encompass S-matrix,port complex impedance,reflection coefficients,electric field and voltage distribution,and optimal matching settings.In this study,we explore the relationship between S-matrix,reflection coefficients,port complex impedance,and frequency.Then,we analyze the impact of Faraday screens placement position and transparency,the distance from the Faraday screen(FS)to the current straps(CS),the relative distance between ports,and the characteristic impedance of the transmission line on the coupling characteristic impedance of the EAST ICRH system.Finally,we simulate the electric field distribution and voltage distribution of the EAST ICRH system for plasma heating with double-stub FT impedance matching.Using optimized parameters,the coupling power of the ICRH system can be approximately doubled.The results present herein may offer guidance for the design of high-power,long-pulse operation ICRH antenna systems.

CMMCAN:Lightweight Feature Extraction and Matching Network for Endoscopic Images Based on Adaptive Attention

In minimally invasive surgery,endoscopes or laparoscopes equipped with miniature cameras and tools are used to enter the human body for therapeutic purposes through small incisions or natural cavities.However,in clinical operating environments,endoscopic images often suffer from challenges such as low texture,uneven illumination,and non-rigid structures,which affect feature observation and extraction.This can severely impact surgical navigation or clinical diagnosis due to missing feature points in endoscopic images,leading to treatment and postoperative recovery issues for patients.To address these challenges,this paper introduces,for the first time,a Cross-Channel Multi-Modal Adaptive Spatial Feature Fusion(ASFF)module based on the lightweight architecture of EfficientViT.Additionally,a novel lightweight feature extraction and matching network based on attention mechanism is proposed.This network dynamically adjusts attention weights for cross-modal information from grayscale images and optical flow images through a dual-branch Siamese network.It extracts static and dynamic information features ranging from low-level to high-level,and from local to global,ensuring robust feature extraction across different widths,noise levels,and blur scenarios.Global and local matching are performed through a multi-level cascaded attention mechanism,with cross-channel attention introduced to simultaneously extract low-level and high-level features.Extensive ablation experiments and comparative studies are conducted on the HyperKvasir,EAD,M2caiSeg,CVC-ClinicDB,and UCL synthetic datasets.Experimental results demonstrate that the proposed network improves upon the baseline EfficientViT-B3 model by 75.4%in accuracy(Acc),while also enhancing runtime performance and storage efficiency.When compared with the complex DenseDescriptor feature extraction network,the difference in Acc is less than 7.22%,and IoU calculation results on specific datasets outperform complex dense models.Furthermore,this method increases the F1 score by 33.2%and accelerates runtime by 70.2%.It is noteworthy that the speed of CMMCAN surpasses that of comparative lightweight models,with feature extraction and matching performance comparable to existing complex models but with faster speed and higher cost-effectiveness.

Artificial Immune Detection for Network Intrusion Data Based on Quantitative Matching Method

Artificial immune detection can be used to detect network intrusions in an adaptive approach and proper matching methods can improve the accuracy of immune detection methods.This paper proposes an artificial immune detection model for network intrusion data based on a quantitative matching method.The proposed model defines the detection process by using network data and decimal values to express features and artificial immune mechanisms are simulated to define immune elements.Then,to improve the accuracy of similarity calculation,a quantitative matching method is proposed.The model uses mathematical methods to train and evolve immune elements,increasing the diversity of immune recognition and allowing for the successful detection of unknown intrusions.The proposed model’s objective is to accurately identify known intrusions and expand the identification of unknown intrusions through signature detection and immune detection,overcoming the disadvantages of traditional methods.The experiment results show that the proposed model can detect intrusions effectively.It has a detection rate of more than 99.6%on average and a false alarm rate of 0.0264%.It outperforms existing immune intrusion detection methods in terms of comprehensive detection performance.

Integration of Electrical Properties and Polarization Loss Modulation on Atomic Fe–N‑RGO for Boosting Electromagnetic Wave Absorption

Developing effective strategies to regulate graphene’s conduction loss and polarization has become a key to expanding its application in the electromagnetic wave absorption(EMWA)field.Based on the unique energy band structure of graphene,regulating its bandgap and electrical properties by introducing heteroatoms is considered a feasible solution.Herein,metal-nitrogen doping reduced graphene oxide(M–N-RGO)was prepared by embedding a series of single metal atoms M–N_(4) sites(M=Mn,Fe,Co,Ni,Cu,Zn,Nb,Cd,and Sn)in RGO using an N-coordination atom-assisted strategy.These composites had adjustable conductivity and polarization to optimize dielectric loss and impedance matching for efficient EMWA performance.The results showed that the minimum reflection loss(RL_(min))of Fe–N-RGO reaches−74.05 dB(2.0 mm)and the maximum effective absorption bandwidth(EAB_(max))is 7.05 GHz(1.89 mm)even with a low filler loading of only 1 wt%.Combined with X-ray absorption spectra(XAFS),atomic force microscopy,and density functional theory calculation analysis,the Fe–N_(4) can be used as the polarization center to increase dipole polarization,interface polarization and defect-induced polarization due to d-p orbital hybridization and structural distortion.Moreover,electron migration within the Fe further leads to conduction loss,thereby synergistically promoting energy attenuation.This study demonstrates the effectiveness of metal-nitrogen doping in regulating the graphene′s dielectric properties,which provides an important basis for further investigation of the loss mechanism.

Laparoscopic hepatectomy using indocyanine green attenuates postoperative inflammatory response for hepatocellular carcinoma:A propensity score matching analysis

BACKGROUND Improving the intraoperative and postoperative performance of laparoscopic hepatectomy was quite a challenge for liver surgeons.AIM To determine the benefits of indocyanine green(ICG)fluorescence imaging in patients with hepatocellular carcinoma(HCC)who underwent laparoscopic hepatectomy during and after surgery.METHODS We retrospectively collected the clinicopathological data of 107 patients who successfully underwent laparoscopic hepatectomy at Zhongshan Hospital(Xiamen),Fudan University from June 2022 to June 2023.Whether using the ICG fluorescence imaging technique,we divided them into the ICG and non-ICG groups.To eliminate statistical bias,a 1:1 propensity score matching analysis was conducted.The comparison of perioperative outcomes,including inflammationrelated markers and progression-free survival,was analyzed statistically.RESULTS Intraoperatively,the ICG group exhibited lower blood loss,a shorter surgical time,lower hepatic inflow occlusion(HIO)frequency,and a shorter total HIO time.Postoperatively,the participation of ICG resulted in a shorter duration of hospitalization(6.5 vs 7.6 days,P=0.03)and postoperative inflammatory response attenuation(lower neutrophil-lymphocyte ratio on the first day after surgery and platelet-lymphocyte ratio on the third day,P<0.05).Although the differences were not significant,the levels of all inflammation-related markers were lower in the ICG group.The rates of postoperative complications and the survival analyses,including progression-free and overall survivals showed no significant difference between the groups.CONCLUSION The involvement of ICG fluorescence imaging may lead to improved perioperative outcomes,especially postoperative inflammatory response attenuation,and ultimately improve HCC patients’recovery after surgery.

Efficacy-cost analysis of endoscopic mucosal resection and cold snare polypectomy:A propensity score matching analysis

BACKGROUND Although substantial evidence supports the advantages of cold snare polypectomy(CSP)in terms of polypectomy efficacy and reduced postoperative adverse events,few studies have examined the cost differences between CSP and traditional endoscopic mucosal resection(EMR)for the treatment of intestinal polyps.AIM To compare the efficacy-cost of EMR and CSP in the treatment of intestinal polyps.METHODS A total of 100 patients with intestinal polyps were included in the retrospective data of our hospital from April 2022 to May 2023.According to the treatment methods,they were divided into EMR(n=46)group and CSP(n=54)group.The baseline data of the two groups were balanced by 1:1 propensity score matching(PSM),and the cost-effectiveness analysis was performed on the two groups after matching.The recurrence rate of the two groups of patients was followed up for 1 year,and they were divided into recurrence group and non-recurrence group according to whether they recurred.Multivariate logistic regression analysis was used to screen out the influencing factors affecting the recurrence of intestinal polyps after endoscopic resection.RESULTS Significant disparities were observed in the number of polyps and smoking background between the two groups before PSM(P<0.05).Following PSM,the number of polyps and smoking history were well balanced between the EMR and CSP groups.The direct cost incurred by the CSP group was markedly higher than that incurred by the EMR group.Concurrently,the cost-effectiveness ratio in the CSP group was substantially reduced when juxtaposed with that in the EMR group(P<0.05).Upon completion of the 1-year follow-up,the rate of recurrence after endoscopic intestinal polypectomy was 38.00%.Multivariate methods revealed that age≥60 years,male sex,number of polyps≥3,and pathological type of adenoma were risk factors for recurrence after endoscopic intestinal polypectomy(all P<0.05).CONCLUSION CSP was more cost-effective for the treatment of intestinal polyps.An age≥60 years,male sex,having a number of polyps≥3,and pathological type of adenoma are independent influencing factors for recurrence.

Design of a distributed power amplifier based on T-type matching networks

The impedance characteristics of distributed amplifiers are analyzed based on T-type matching networks, and a distributed power amplifier consisting of three gain cells is proposed. Non-uniform T-type matching networks are adopted to make the impedance of artificial transmission lines connected to the gate and drain change stage by stage gradually, which provides good impedance matching and improves the output power and efficiency. The measurement results show that the amplifier gives an average forward gain of 6 dB from 3 to 16. 5 GHz. In the desired band, the input return loss is typically less than - 9. 5 dB, and the output return loss is better than -8.5 dB. The output power at 1-dB gain compression point is from 3.6 to 10. 6 dBm in the band of 2 to 16 GHz while the power added efficiency （PAE） is from 2% to 12. 5% . The power consumption of the amplifier is 81 mW with a supply of 1.8 V, and the chip area is 0.91 mm × 0.45 mm.

OPTIMIZATION DESIGN METHOD FOR INPUT IMPEDANCE MATCHING NETWORK OF LOW NOISE AMPLIFIER

According to the theories of optimal noise match and optimal power match, a method for calculating the optimal source impedance of low noise amplifier （LNA） is proposed based on the input reflection coefficient S11. Moreover.with the help of Smith chart, the calculation process is detailed, and the trade-off between the lowest noise figure and the maximum power gain is obtained during the design of LNA input impedance matching network. Based on the Chart 0. 35-μm CMOS process, a traditional cascode LNA circuit is designed and manufactured. Simulation and experimental results have a good agreement with the theoretical analysis, thus proving the correctness of theoretical analysis and the feasibility of the method.

An 8GHz Internally Matched AlGaN/GaN HEMT Power Amplifier with RC Stability Network

8GHz 20W internally matched A1GaN/GaN HEMTs have been developed. The input and output matching net- works are realised with microstrip lines on a 0. 381mm thick alumina substrate. To improve the stability factor K of the device, a lossy RC network is used at the input of the device. The developed internally matched power amplifier module exhibits 43dBm （20W） power output with a 7.3dB linear gain,38.1% PAIE,and combined power efficiency of 70.6% at 8GHz.

A New Method to Calculate the Degree of Electromagnetic Impedance Matching in One-Layer Microwave Absorbers

A delta-function method is proposed to quantitatively evaluate the electromagnetic impedance matching degree.Measured electromagnetic parameters ofα-Fe/Fe_(3)B/Y_(2)O_(3)nanocomposites are applied to calculate the matching degree by the method.Compared with reflection loss and quarter-wave principle theory,the method accurately reveals the intrinsic mechanism of microwave transmission and reflection properties.A possible honeycomb structure with promising high-performance microwave absorption,devised according to the method,is also proposed.

A Fast Multi-Pattern Matching Algorithm for Mining Big Network Data

The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource allocation and provide customized services to users. The first step of analyzing user behaviors is to extract information of user actions from HTTP traffic data by multi-pattern URL matching. However, the efficiency is a huge problem when performing this work on massive network traffic data. To solve this problem, we propose a novel and accurate algorithm named Multi-Pattern Parallel Matching(MPPM) that takes advantage of HashMap in data searching for extracting user behaviors from big network data more effectively. Extensive experiments based on real-world traffic data prove the ability of MPPM algorithm to deal with massive HTTP traffic with better performance on accuracy, concurrency and efficiency. We expect the proposed algorithm and it parallelized implementation would be a solid base to build a high-performance analysis engine of user behavior based on massive HTTP traffic data processing.

Adaptive impedance matching using quantum genetic algorithm

An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is Moreover, the proposed method can be useful for software wireless bands. also given, which shows that the QGA tuning algorithm is much faster. defined radio systems using a single antenna for multiple mobile and

Dynamic Matching-Based Spectrum Detection in Cognitive Radio Networks

Cognitive Radio Network provides an opportunity to reduce the spectrum resource crisis by allowing secondary users to access the idle spectrum allocated to primary users. The precondition of spectrum sharing is to obtain the Spectrum Availability Information(SAI). Energy detection is a typical technology to get SAI. With the mobility of primary users, the energy received by secondary users varies greatly with the distance from the target primary users. Most of the existing energy detection algorithms that use fixed thresholds are not suitable. We propose a Dynamic Matching-Based Spectrum Detection(DMBSD) scheme which can detect sensing data, reduce the impact of malicious data and make final sensing results more accurate with dynamic threshold setting and data matching. Simulation results show that the proposed scheme can detect tempered data, and increase detection probability by decreasing false alarm probability and missed detection probability.

Iterative learning-based many-objective history matching using deep neural network with stacked autoencoder

This paper presents an innovative data-integration that uses an iterative-learning method,a deep neural network(DNN)coupled with a stacked autoencoder(SAE)to solve issues encountered with many-objective history matching.The proposed method consists of a DNN-based inverse model with SAE-encoded static data and iterative updates of supervised-learning data are based on distance-based clustering schemes.DNN functions as an inverse model and results in encoded flattened data,while SAE,as a pre-trained neural network,successfully reduces dimensionality and reliably reconstructs geomodels.The iterative-learning method can improve the training data for DNN by showing the error reduction achieved with each iteration step.The proposed workflow shows the small mean absolute percentage error below 4%for all objective functions,while a typical multi-objective evolutionary algorithm fails to significantly reduce the initial population uncertainty.Iterative learning-based manyobjective history matching estimates the trends in water cuts that are not reliably included in dynamicdata matching.This confirms the proposed workflow constructs more plausible geo-models.The workflow would be a reliable alternative to overcome the less-convergent Pareto-based multi-objective evolutionary algorithm in the presence of geological uncertainty and varying objective functions.

Multi-source information fused generative adversarial network model and data assimilation based history matching for reservoir with complex geologies

For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for the ensemble-based data assimilation methods.In this paper,we propose a multi-source information fused generative adversarial network(MSIGAN)model,which is used for parameterization of the complex geologies.In MSIGAN,various information such as facies distribution,microseismic,and inter-well connectivity,can be integrated to learn the geological features.And two major generative models in deep learning,variational autoencoder(VAE)and generative adversarial network(GAN)are combined in our model.Then the proposed MSIGAN model is integrated into the ensemble smoother with multiple data assimilation(ESMDA)method to conduct history matching.We tested the proposed method on two reservoir models with fluvial facies.The experimental results show that the proposed MSIGAN model can effectively learn the complex geological features,which can promote the accuracy of history matching.

Optimal Matching of Magnetic Pulse Compressor

Energy transmission efficiency in the magnetic pulse generators varies with saturated time of magnetic switch. An optimal matching time exists and depends on the compression ratio, under which, the energy transmission efficiency can reach approximate 100%. The equation of required magnetic core volume is obtained by taken into account the optimal matching mode. It indicates that a great reduction on the volume is feasible under the optimal matching mode. The circuit simulation code-PSPICE is also introduced to simulate a 3-stage magnetic pulse compressor, and the results are in accordance with those of equivalent circuit analyses.

Sustainable Lignin-Derived Carbon as Capacity-Kinetics Matched Cathode and Anode towards 4.5 V High-Performance Lithium-Ion Capacitors

The Li-ion capacitors(LICs)develop rapidly due to their double-high features of high-energy density and high-power density.However,the relative low capacity of cathode and sluggish kinetics of anode seriously impede the development of LICs.Herein,the precisely pore-engineered and heteroatomtailored defective hierarchical porous carbons(DHPCs)as large-capacity cathode and high-rate anode to construct high-performance dual-carbon LICs have been developed.The DHPCs are prepared based on triple-activation mechanisms by direct pyrolysis of sustainable lignin with urea to generate the interconnected hierarchical porous structure and plentiful heteroatominduced defects.Benefiting from these advanced merits,DHPCs show the well-matched high capacity and fast kinetics of both cathode and anode,exhibiting large capacities,superior rate capability and long-term lifespan.Both experimental and computational results demonstrate the strong synergistic effect of pore and dopants for Li storage.Consequently,the assembled dual-carbon LIC exhibits high voltage of 4.5 V,high-energy density of 208 Wh kg^(−1),ultrahigh power density of 53.4 kW kg^(−1)and almost zerodecrement cycling lifetime.Impressively,the full device with high mass loading of 9.4 mg cm^(−2)on cathode still outputs high-energy density of 187 Wh kg^(−1),demonstrative of their potential as electrode materials for high-performance electrochemical devices.

Stereo Matching Method Based on Space-Aware Network Model

The stereo matching method based on a space-aware network is proposed, which divides the network into threesections: Basic layer, scale layer, and decision layer. This division is beneficial to integrate residue network and densenetwork into the space-aware network model. The vertical splitting method for computing matching cost by usingthe space-aware network is proposed for solving the limitation of GPU RAM. Moreover, a hybrid loss is broughtforward to boost the performance of the proposed deep network. In the proposed stereo matching method, thespace-aware network is used to calculate the matching cost and then cross-based cost aggregation and semi-globalmatching are employed to compute a disparity map. Finally, a disparity-post processing method is utilized suchas subpixel interpolation, median filter, and bilateral filter. The experimental results show this method has a goodperformance on running time and accuracy, with a percentage of erroneous pixels of 1.23% on KITTI 2012 and1.94% on KITTI 2015.

Synthesis of carbon-coated cobalt ferrite core-shell structure composite:A method for enhancing electromagnetic wave absorption properties by adjusting impedance matching

Cobalt ferrite has problems such as poor impedance matching and high density,which results in unsatisfactory electromagnetic wave(EMW)absorption performance.In this study,the CoFe_(2)O_(4)@C core-shell structure composite was synthesized by a two-step hydrothermal method.X-ray diffraction,transmission electron microscopy,Fourier transform infrared spectroscopy,thermogravimetric analysis,and vector network analysis et al.were used to test the structure and EMW absorption properties of CoFe_(2)O_(4)@C composite.The results show that the reflection loss(RL)of the CoFe_(2)O_(4)@C composite reaches the maximum value of25.66 dB at 13.92 GHz,and the effective absorbing band(EAB)is 4.59 GHz(11.20-15.79 GHz)when the carbon mass content is 6.01%.The RL and EAB of CoFe_(2)O_(4)@C composite are increased by 219.55%and 4.59 GHz respectively,and the density is decreased by 20.78%compared with the cobalt ferrite.Such enhanced EMW absorption properties of CoFe_(2)O_(4)@C composite are attributed to the attenuation caused by the strong natural resonance of the cobalt ferrite,moreover,the carbon coating layer adjusts the impedance matching of the composite,and the introduced dipole polarization and interface polarization can cause multiple Debye relaxation processes.

Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks

The traditional orthogonal multiple access(OMA)is unable to satisfy the needs of large number of smart devices.To increase the transmission rate in the limited spectrum resource,implementation of both non-orthogonal multiple access(NOMA)and successive interference cancelation(SIC)is essential.In this paper,an optimal resource allocation algorithm in NOMA is proposed to maximize the total system rate in a multi-sector multi-subcarrier relay-assisted communication network.Since the original problem is a non-convex problem with mixed integer programming which is non-deterministic polynomial-time(NP)-hard,a three-step solution is proposed to solve the primal problem.Firstly,we determine the optimal power allocation of the outer users by using the approach of monotonic discrimination,and then the optimal user pairing is determined.Secondly,the successive convex approximation(SCA)method is introduced to transform the non-convex problem involving central users into convex one,and the Lagrangian dual method is used to determine the optimal solution.Finally,the standard Hungarian algorithm is utilized to determine the optimal subcarrier matching.The simulation results show that resource allocation algorithm is able to meet the user performance requirements with NOMA,and the total system rate is improved compared to the existing algorithms.