Generation of input spectrum for electrolysis stack degradation test applied to wind power PEM hydrogen production

Hydrogen production by proton exchange membrane electrolysis has good fluctuation adaptability,making it suitable for hydrogen production by electrolysis in fluctuating power sources such as wind power.However,current research on the durability of proton exchange membrane electrolyzers is insufficient.Studying the typical operating conditions of wind power electrolysis for hydrogen production can provide boundary conditions for performance and degradation tests of electrolysis stacks.In this study,the operating condition spectrum of an electrolysis stack degradation test cycle was proposed.Based on the rate of change of the wind farm output power and the time-averaged peak-valley difference,a fluctuation output power sample set was formed.The characteristic quantities that played an important role in the degradation of the electrolysis stack were selected.Dimensionality reduction of the operating data was performed using principal component analysis.Clustering analysis of the data segments was completed using an improved Gaussian mixture clustering algorithm.Taking the annual output power data of wind farms in Northwest China with a sampling rate of 1 min as an example,the cyclic operating condition spectrum of the proton-exchange membrane electrolysis stack degradation test was constructed.After preliminary simulation analysis,the typical operating condition proposed in this paper effectively reflects the impact of the original curve on the performance degradation of the electrolysis stack.This study provides a method for evaluating the degradation characteristics and system efficiency of an electrolysis stack due to fluctuations in renewable energy.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Advances in the treatment of autism spectrum disorder:Wharton jelly mesenchymal stem cell transplantation

BACKGROUND Autism spectrum disorder(ASD)is a complex neurodevelopmental disorder with multifaceted origins.In recent studies,neuroinflammation and immune dysregulation have come to the forefront in its pathogenesis.There are studies suggesting that stem cell therapy may be effective in the treatment of ASD.AIM To evolve the landscape of ASD treatment,focusing on the potential benefits and safety of stem cell transplantation.METHODS A detailed case report is presented,displaying the positive outcomes observed in a child who underwent intrathecal and intravenous Wharton’s jelly-derived mesenchymal stem cells(WJ-MSCs)transplantation combined with neurorehabilitation.RESULTS The study demonstrates a significant improvement in the child’s functional outcomes(Childhood Autism Rating Scale,Denver 2 Developmental Screening Test),especially in language and gross motor skills.No serious side effects were encountered during the 2-year follow-up.CONCLUSION The findings support the safety and effectiveness of WJ-MSC transplantation in managing ASD.

Autism spectrum disorder:difficulties in diagnosis and microRNA biomarkers

We performed a PubMed search for microRNAs in autism spectrum disorder that could serve as diagnostic biomarkers in patients and selected 17 articles published from January 2008 to December 2023,of which 4 studies were performed with whole blood,4 with blood plasma,5 with blood serum,1 with serum neural cell adhesion molecule L1-captured extracellular vesicles,1 with blood cells,and 2 with peripheral blood mononuclear cells.Most of the studies involved children and the study cohorts were largely males.Many of the studies had performed microRNA sequencing or quantitative polymerase chain reaction assays to measure microRNA expression.Only five studies had used real-time polymerase chain reaction assay to validate microRNA expression in autism spectrum disorder subjects compared to controls.The microRNAs that were validated in these studies may be considered as potential candidate biomarkers for autism spectrum disorder and include miR-500a-5p,-197-5p,-424-5p,-664a-3p,-365a-3p,-619-5p,-664a-3p,-3135a,-328-3p,and-500a-5p in blood plasma and miR-151a-3p,-181b-5p,-320a,-328,-433,-489,-572,-663a,-101-3p,-106b-5p,-19b-3p,-195-5p,and-130a-3p in blood serum of children,and miR-15b-5p and-6126 in whole blood of adults.Several important limitations were identified in the studies reviewed,and need to be taken into account in future studies.Further studies are warranted with children and adults having different levels of autism spectrum disorder severity and consideration should be given to using animal models of autism spectrum disorder to investigate the effects of suppressing or overexpressing specific microRNAs as a novel therapy.

Analysis and optimization of power spectrum on EBPSK modulation in throughput-efficient wireless system

In order to satisfy increasingly greater demand for the performance of communication systems, a throughput efficient wireless system based on the extended binary phase shift keying （EBPSK） modulation is presented. Simultaneously, corresponding analysis of power spectra is also given with a brief process. The optimal waveform is proposed without useful information loss, by removing linear spectra presenting periodic components. On this basis, the reasonable definition of bandwidth is discussed, which indicates that the EBPSK belongs to the category of the ultra narrow band （UNB） throughput-efficient communication. Meanwhile, the modulation parameters＇ effects on bandwidth, transmission rate and transmission performance are analyzed. Results illustrate the validity of theoretical analysis and spectrum optimization. Results also prove that this UNB system can obtain good bit error rate （BER） performance with high spectra efficiency.

AUTOREGRESSIVE MODEL AND POWER SPECTRUM CHARATERISTICS OF CURRENT SIGNAL IN HIGH FREQUENCY GROUP PULSE MICRO-ELECTROCHEMICAL MACHINING

The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining （HGPECM） is mainly discussed. The auto-regressive（AR） model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green＇s function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum（CPS）, to the current signals related to the different inter-electrode gap size in the range of 0～5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.

The power spectrum and correlation of flow noise for an axisymmetric body in water

Understanding the physical features of the flow noise for an axisymmetric body is important for improving the performance of a sonar mounted on an underwater platform. Analytical calculation and numerical analysis of the physical features of the flow noise for an axisymmetric body are presented and a simulation scheme for the noise correlation on the hydrophones is given. It is shown that the numerical values of the flow noise coincide well with the analytical values. The main physical features of flow noise are obtained. The flow noises of two different models are compared and a model with a rather optimal fore-body shape is given. The flow noise in horizontal symmetry profile of the axisymmetric body is non-uniform, but it is omni-directional and has little difference in the cross section of the body. The loss of noise diffraction has a great effect on the flow noise from boundary layer transition. Meanwhile, based on the simulation, the noise power level increases with velocity to approximately the fifth power at high frequencies, which is consistent with the experiment data reported in the literature. Furthermore, the flow noise received by the acoustic array has lower correlation at a designed central frequency, which is important for sonar system design.

ICU患者置入Power PICC导管特殊异位原因分析

目的:探讨ICU患者置入Power PICC导管后头端反折向上至同侧和对侧锁骨下静脉、头臂静脉等特殊异位的相关因素。方法:回顾性分析2021年9月至2022年9月某三甲医院ICU 520例PICC置管患者,通过胸部X线确定PICC导管头端反折向上至对侧和同侧锁骨下静脉、头臂静脉的患者,分析其特殊异位发生因素。结果:胸部X线结果显示25例患者PICC管头端反折向上异位至对侧和同侧锁骨下静脉、头臂静脉或颈内静脉,异位发生率4.8%,不同静脉置管反折异位发生率相比差异无统计学意义,P>0.05。结论:ICU患者PICC置入发生导管头端反折向上至同侧和对侧锁骨下静脉、头臂静脉等特殊异位的发生因素较多,包括同时留置CVC或血透管、正在滴注或泵入多种药物、PICC管头端异位的隐匿性、导管材质、自身疾病及机械通气等危险因素。

Earthquake accelerogram simulation with statistical law of evolutionary power spectrum

By using the technique for evolutionary power spectrum proposed by Nakayama and with reference to the Kameda formula, an evolutionary spectrum prediction model for given earthquake magnitude and distance is established based on the 80 near-source acceleration records at rock surface with large magnitude from the ground motion database of western U.S.. Then a new iteration method is developed for generation of random accelerograms non-stationary both in amplitude and frequency which are compatible with target evolutionary spectrum. The phase spectra of those simulated accelerograms are also non-stationary in time and frequency domains since the interaction between amplitude and phase angle has been considered during the generation. Furthermore, the sign of the phase spectrum increment is identified to accelerate the iteration. With the proposed statistical model for predicting evolutionary power spectra and the new method for generating compatible time history, the artificial random earthquake accelerograms non-stationary both in amplitude and frequency for certain magnitude and distance can be provided.

Matched Filter Based Spectrum Sensing When Primary User Has Multiple Power Levels

In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards,i.e.,IEEE 802.11 Series,GSM,LTE,LTE-A,etc.This new multiple primary transmit power(MPTP) scenario is specialized by two different targets:detecting the presence of PU and identifying the power level.Compared to the traditional binary sensing where only the presence of PU is checked,SU may attain more information about the primary network(making CR more "intelligent") and design the subsequent optimization strategy.The key technology is the multiple hypothesis testing as opposed to the traditional binary hypothesis testing.We discuss two situations under whether the channel phase is known or not,and we derive the closed form solutions for decision regions and several performance metrics,from which some interesting phenomenons are observed and the related discussions are presented.Numerical examples are provided to corroborate the proposed studies.

Universal form of the power spectrum of the aero-optical aberration caused by the supersonic turbulent boundary layer

Based on the measurement of one-dimensional （1D） optical path difference （OPD） of the supersonic turbulent bound- ary layer, an analytical form for the power spectrum of the two-dimensional （2D） OPD is obtained with its structure function and under the locally homogeneous isotropic assumption. The universality of this spectrum is argued, and its validity is checked by the comparison with experimental result. The potential applications of this model in theoretical and numerical studies are emphasized. Another contribution of this work is around the application of correlation function to analyzing the statistics of OPD. Based on our results and other results published elsewhere, we show that the OPD is often not stationary, and one should be cautious about using this tool.

Joint Power Control and Spectrum Allocation for Cognitive Radio with QoS Constraint

Spectrum sharing with quality of service (QoS) requirement and power constraint on cognitive users is studied. The objective is to maximize the system throughput. This problem is modeled as a mixed integer nonlinear programming problem and then transformed to a continuous nonlinear programming problem through eliminating integer variables. We propose the joint power control and spectrum allocation algorithm based on particle swarm optimization to obtain the global optimal solution. Simulation results show that the proposed method can achieve higher system throughput and spectrum utilization under the constraints of transmit power and QoS requirement.

Research and Implementation of Text Similarity System Based on Power Spectrum Analysis

The paper proposed the research and implement of text similarity system based on power spectrum analysis. It is not difficult to imagine that the signals of brain are closely linked with writing process. So we build text modeling and set pulse signal function to get the power spectrum of the text. The specific detail is getting power spectrum from economic field to build spectral library, and then using the method of power spectrum matching algorithm to judge whether the test text belonged to the economic field. The method made text similarity system finish the function of text intelligent classification efficiently and accurately.

Spectrum Efficiency Maximization for Cooperative Power Beacon-Enabled Wireless Powered Communication Networks

We consider a spectrum efficiency(SE)maximization problem for cooperative power beacon-enabled wireless powered communication networks(CPB-WPCNs),where each transmitter harvests en-ergy from multi-antenna power beacons(PBs)and transmits data to the corresponding receiver.For data transmission,both orthogonal transmission,i.e.,the time splitting(TS)mode,and non-orthogonal trans-mission,i.e.,the interference channel(IC)mode,are considered.Aiming to improve the system SE,the energy beamformers of PBs,the transmit power,and the transmit time duration of transmitters are jointly optimized.For the TS mode,the original non-convex problem is transformed into a convex opti-mization problem by means of variable substitution and semidefinite relaxation(SDR).The rank-one na-ture of this SDR is proved,and then a Lagrange-dual based fast algorithm is proposed to obtain the opti-mal solution with much lower complexity.For the IC mode,to conquer the strong non-convexity of the problem,a branch-reduce-and-bound(BRB)mono-tonic optimization algorithm is designed as a bench-mark.Furthermore,a low-complexity distributed suc-cessive convex approximation(SCA)algorithm is pre-sented.Finally,simulation results validate the perfor-mance of the proposed algorithms,achieving optimal-ity within only 1%∼2%computation time compared to the CVX solver in the TS mode and achieving 98%of the optimal performance in the IC mode.

Joint power and spectrum allocation algorithm in cognitive radio networks

The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-filling theorem, a novel one-user water-filling algorithm is proposed, and then the corresponding simulation results are given to analyze the feasibility and validity. After that this algorithm is used to solve the communication utility optimization problem subject to the power constraints in cognitive radio network. First, through the gain to noise ratio for cognitive users, a subcarrier and power allocation algorithm based on the optimal frequency partition is proposed for two cognitive users. Then the spectrum sharing algorithm is extended to multiuser conditions such that the greedy and parallel algorithms are proposed for spectrum sharing. Theory and simulation analysis show that the subcarrier and power allocation algorithms can not only protect the primary users but also effectively solve the spectrum and power allocation problem for cognitive users.

Proactive Spectrum Monitoring for Suspicious Wireless Powered Communications in Dynamic Spectrum Sharing Networks

This paper studies the proactive spec-trum monitoring with one half-duplex spectrum moni-tor(SM)to cope with the potential suspicious wireless powered communications(SWPC)in dynamic spec-trum sharing networks.The jamming-assisted spec-trum monitoring scheme via spectrum monitoring data(SMD)transmission is proposed to maximize the sum ergodic monitoring rate at SM.In SWPC,the suspi-cious communications of each data block occupy mul-tiple independent blocks,with a block dedicated to the wireless energy transfer by the energy-constrained suspicious nodes with locations in a same cluster(symmetric scene)or randomly distributed(asymmet-ric scene)and the remaining blocks used for the in-formation transmission from suspicious transmitters(STs)to suspicious destination(SD).For the sym-metric scene,with a given number of blocks for SMD transmission,namely the jamming operation,we first reveal that SM should transmit SMD signal(jam the SD)with tolerable maximum power in the given blocks.The perceived suspicious signal power at SM could be maximized,and thus so does the correspond-ing sum ergodic monitoring rate.Then,we further reveal one fundamental trade-off in deciding the op-timal number of given blocks for SMD transmission.For the asymmetric scene,a low-complexity greedy block selection scheme is proposed to guarantee the optimal performance.Simulation results show that the jamming-assisted spectrum monitoring schemes via SMD transmission achieve much better perfor-mance than conventional passive spectrum monitor-ing,since the proposed schemes can obtain more accu-rate and effective spectrum characteristic parameters,which provide basic support for fine-grained spectrum management and a solution for spectrum security in dynamic spectrum sharing network.

BP-Neural-Network-Based Tool Wear Monitoring by Using Wav elet Decomposition of the Power Spectrum

In a drilling process, the power spectrum of the drilling force is related tothe tool wear and is widely applied in the monitoring of tool wear. But the feature extraction andidentification of the power spectrum have always been an unresolved difficult problem. This papersolves it through decomposition of the power spectrum in multilayers using wavelet transform andextraction of the low frequency decomposition coefficient as the envelope information of the powerspectrum. Intelligent identification of the tool wear status is achieved in the drilling processthrough fusing the wavelet decomposition coefficient of the power spectrum by using a BP (BackPropagation) neural network. The experimental results show that the features of the power spectrumcan be extracted efficiently through this method, and the trained neural networks show highidentification precision and the ability of extension.

Effect of focused ultrasound stimulation at different ultrasonic power levels on the local field potential power spectrum

Local field potential(LFP) signals of the rat hippocampus were recorded under noninvasive focused ultrasound stimulation(FUS) with different ultrasonic powers. The LFP mean absolute power was calculated with the Welch algorithm at the delta, theta, alpha, beta, and gamma frequency bands. The experimental results demonstrate that the LFP mean absolute power at different frequency bands increases as the ultrasound power increases.

Fourier Power Spectrum Analysis of Exons for the Period-3 Behavior

The period-3 behaviors of 105 exons from 20 genes in human were studied by Fourier power spectrum. The results indicated that not all exons show the period-3 behavior. The exons were adjusted in order to make them accord with the order of the protein translated, and we found that the period-3 character is relation to the length of exons and the bases distribution in the three codon position. Furthermore, as long as the exons with period-3 behavior accord with the order of protein translated, they would exhibit the synonymous codons usage preference, and the codons with g/c at the third position are used in higher frequency. The results are significant to the gene prediction and the research on the introns.

Texture Feature Extraction Method for Ground Nephogram Based on Contourlet and the Power Spectrum Analysis Algorithm

It is important to extract texture feature from the ground-base cloud image for cloud type automatic detection.In this paper,a new method is presented to capture the contour edge,texture and geometric structure of cloud images by using Contourlet and the power spectrum analysis algorithm.More abundant texture information is extracted.Cloud images can be obtained a multiscale and multidirection decomposition.The coefficient matrix from Contourlet transform of ground nephogram is calculated.The energy,mean and variance characteristics calculated from coefficient matrix are composed of the feature information.The frequency information of the data series from the feature vector values is obtained by the power spectrum analysis.Then Support Vector Machines(SVM)classifier is used to classify according to the frequency information of the trend graph of data series.It is shown that altocumulus and stratus with different texture frequencies can be effectively recognized and further subdivided the types of clouds.