Consistent and Specific Multi-View Functional Brain Networks Fusion for Autism Spectrum Disorder Diagnosis

Functional brain networks (FBN) based on resting-state functional magnetic resonance imaging (rs-fMRI) have become an important tool for exploring underlying organization patterns in the brain, which can provide an objective basis for brain disorders such as autistic spectrum disorder (ASD). Due to its importance, researchers have proposed a number of FBN estimation methods. However, most existing methods only model a type of functional connection relationship between brain regions-of-interest (ROIs), such as partial correlation or full correlation, which is difficult to fully capture the subtle connections among ROIs since these connections are extremely complex. Motivated by the multi-view learning, in this study we propose a novel Consistent and Specific Multi-view FBNs Fusion (CSMF) approach. Concretely, we first construct multi-view FBNs (i.e., multiple types of FBNs modelling various relationships among ROIs), and then these FBNs are decomposed into a consistent representation matrix and their own specific matrices which capture their common and unique information, respectively. Lastly, to obtain a better brain representation, it is fusing the consistent and specific representation matrices in the latent representation spaces of FBNs, but not directly fusing the original FBNs. This potentially makes it more easily to find the comprehensively brain connections. The experimental results of ASD identification on the ABIDE datasets validate the effectiveness of our proposed method compared to several state-of-the-art methods. Our proposed CSMF method achieved 72.8% and 76.67% classification performance on the ABIDE dataset.

Spectrum and energy efficient multi-antenna spectrum sensing for green UAV communication

Unmanned Aerial Vehicle(UAV)communication is a promising technology that provides swift and flexible ondemand wireless connectivity for devices without infrastructure support.With recent developments in UAVs,spectrum and energy efficient green UAV communication has become crucial.To deal with this issue,Spectrum Sharing Policy(SSP)is introduced to support green UAV communication.Spectrum sensing in SSP must be carefully formulated to control interference to the primary users and ground communications.In this paper,we propose spectrum sensing for opportunistic spectrum access in green UAV communication to improve the spectrum utilization efficiency.Different from most existing works,we focus on the problem of spectrum sensing of randomly arriving primary signals in the presence of non-Gaussian noise/interference.We propose a novel and improved p-norm-based spectrum sensing scheme to improve the spectrum utilization efficiency in green UAV communication.Firstly,we construct the p-norm decision statistic based on the assumption that the random arrivals of signals follow a Poisson process.Then,we analyze and derive the approximate analytical expressions of the false-alarm and detection probabilities by utilizing the central limit theorem.Simulation results illustrate the validity and superiority of the proposed scheme when the primary signals are corrupted by additive non-Gaussian noise and arrive randomly during spectrum sensing in the green UAV communication.

Dynamic Update Scheme of Spectrum Information Based on Spectrum Opportunity Incentive in the Database-Assisted Dynamic Spectrum Management

To solve the problem of delayed update of spectrum information(SI) in the database assisted dynamic spectrum management(DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution(IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers(VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. The-oretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.

Correction:Brillouin scattering spectrum for liquid detection and applications in oceanography

After publication of this article1,it was brought to our at-tention that the mathematical expressions‘‰’were mis-takenly replaced by‘%’for salinities.Details are listed below.1.In the last sentence in abstract,“approximately 0.1℃and 0.5%”should be“approximately 0.1℃and 0.5‰”.

Construction of a Cu@hollow TS-1 nanoreactor based on a hierarchical full-spectrum solar light utilization strategy for photothermal synergistic artificial photosynthesis

The artificial photosynthesis technology has been recognized as a promising solution for CO_(2) utilization.Photothermal catalysis has been proposed as a novel strategy to promote the efficiency of artificial photosynthesis by coupling both photochemistry and thermochemistry.However,strategies for maximizing the use of solar spectra with different frequencies in photothermal catalysis are urgently needed.Here,a hierarchical full-spectrum solar light utilization strategy is proposed.Based on this strategy,a Cu@hollow titanium silicalite-1 zeolite(TS-1)nanoreactor with spatially separated photo/thermal catalytic sites is designed to realize high-efficiency photothermal catalytic artificial photosynthesis.The space-time yield of alcohol products over the optimal catalyst reached 64.4μmol g−1 h−1,with the selectivity of CH3CH2OH of 69.5%.This rationally designed hierarchical utilization strategy for solar light can be summarized as follows:(1)high-energy ultraviolet light is utilized to drive the initial and difficult CO_(2) activation step on the TS-1 shell;(2)visible light can induce the localized surface plasmon resonance effect on plasmonic Cu to generate hot electrons for H2O dissociation and subsequent reaction steps;and(3)low-energy near-infrared light is converted into heat by the simulated greenhouse effect by cavities to accelerate the carrier dynamics.This work provides some scientific and experimental bases for research on novel,highly efficient photothermal catalysts for artificial photosynthesis.

Floquet spectrum and universal dynamics of a periodically driven two-atom system

We investigate the Floquet spectrum and excitation properties of a two-ultracold-atom system with periodically driven interaction in a three-dimensional harmonic trap.The interaction between the atoms is changed by varying the s-wave scattering length in two ways,the cosine and the square-wave modulations.It is found that as the driving frequency increases,the Floquet spectrum exhibits two main features for both modulations,the accumulating and the spreading of the quasienergy levels,which further lead to different dynamical behaviors.The accumulation is associated with collective excitations and the persistent growth of the energy,while the spread indicates that the energy is bounded at all times.The initial scattering length,the driving frequency and amplitude can all significantly change the Floquet spectrum as well as the dynamics.However,the corresponding relation between them is valid universally.Finally,we propose a mechanism for selectively exciting the system to one specific state by using the avoided crossing of two quasienergy levels,which could guide preparation of a desired state in experiments.

Comparison of inebilizumab or rituximab in addition to glucocorticoid therapy for neuromyelitis optica spectrum disorders

AIM:To investigate the short-term efficacy and safety of inebilizumab for neuromyelitis optica spectrum disorders(NMOSD).METHODS:A total of 33 patients with NMOSD treated with inebilizumab(Group INB,n=15)or rituximab(Group RTX,n=18)in addition to high-dose glucocorticoids were included.Both groups underwent hormone shock therapy during the acute phase.Subsequently,Group INB received inebilizumab injections during the remission phase,while Group RTX received rituximab injections.A comparison of aquaporins 4(AQP4)titer values,peripheral blood B lymphocyte counts,and visual function recovery was conducted before and 8wk after treatment.Additionally,adverse reactions and patient tolerability were analyzed after using inebilizumab treatment regimes.RESULTS:Following inebilizumab treatment,there was a significantly improvement in the visual acuity of NMOSD patients(P<0.05),accompanied by a notable decrease in AQP4 titer values and B lymphocyte ratio(P<0.05).Moreover,inebilizumab treatment showed a partial effect in preventing optic nerve atrophy(P<0.05).However,there were no significant differences in other therapeutic effects compared to rituximab,which has previously demonstrated substantial therapeutic efficacy(P>0.05).Furthermore,inebilizumab exhibited higher safety levels than that of rituximab injections.CONCLUSION:The combination of inebilizumab and high-dose glucocorticoids proves to be effective.In comparison to rituximab injections,inebilizumab displays better tolerance and safety.Moreover,it demonstrates a partial effect in preventing optic nerve atrophy.Thus,it stands as an effective method to reduce the disability rates and improve the daily living ability of patients with NMOSD.

Blockchain-Based MCS Detection Framework of Abnormal Spectrum Usage for Satellite Spectrum Sharing Scenario

In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit satellites, and the directional nature of their signals, traditional monitoring methods are no longer suitable, especially in the case of multiple power level. Mobile crowdsensing(MCS), as a new technology, can make full use of idle resources to complete a variety of perceptual tasks. However, traditional MCS heavily relies on a centralized server and is vulnerable to single point of failure attacks. Therefore, we replace the original centralized server with a blockchain-based distributed service provider to enable its security. Therefore, in this work, we propose a blockchain-based MCS framework, in which we explain in detail how this framework can achieve abnormal frequency behavior monitoring in an inter-satellite spectrum sharing system. Then, under certain false alarm probability, we propose an abnormal spectrum detection algorithm based on mixed hypothesis test to maximize detection probability in single power level and multiple power level scenarios, respectively. Finally, a Bad out of Good(BooG) detector is proposed to ease the computational pressure on the blockchain nodes. Simulation results show the effectiveness of the proposed framework.

Periodic signal extraction of GNSS height time series based on adaptive singular spectrum analysis

Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites.

Occurrence of K1 and K2 serotypes and genotypic characteristics of extended spectrumβ-lactamases-producing Klebsiella pneumoniae isolated from selected hospitals in Malaysia

Objective:To determine the distribution,phenotypic and genetic background of extended spectrumβ-lactamases(ESBL)-producing Klebsiella(K.)pneumoniae clinical isolates associated with K1 and K2 serotypes in two selected hospitals in Malaysia.Methods:A total of 192 K.pneumoniae isolates were collected and subjected to antibiotic susceptibility,hypermucoviscosity test and multiplex PCR to detect the presence of K1-and K2-serotype associated genes.Multilocus sequence typing(MLST)was performed on ESBL-producing K.pneumoniae isolates presented with K1 and K2 serotypes,followed by phylogenetic analysis.Results:A total of 87 out of 192(45.3%)of the K.pneumoniae isolates collected were ESBL producers.However,only 8.3%(16/192)and 10.9%(21/192)of the total isolates were detected to carry K1-and K2-serotype associated genes,respectively.Statistical analysis showed that K1 and K2 capsular serotypes were not significantly associated with ESBL phenotype(P=0.196).However,they were significantly associated with hypervirulent,as demonstrated by the positive string test(P<0.001).MLST analysis revealed that ST23 as the predominant sequence type(ST)in the K1 serotype,while the ST in the K2 serotype is more diverse.Conclusions:Although the occurrence of ESBL-producing isolates among the hypervirulent strains was low,their coexistence warrants the need for continuous surveillance.MLST showed that these isolates were genetically heterogeneous.

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

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.

THE ABSENCE OF SINGULAR CONTINUOUS SPECTRUM FOR PERTURBED JACOBI OPERATORS

This paper is mainly about the spectral properties of a class of Jacobi operators(H_(c,b)u)(n)=c_(n)u(n+1)+c_(n-1)u(n-1)+b_(n)u(n),.where∣c_(n)−1∣=O(n^(−α))and b_(n)=O(n^(−1)).We will show that,forα≥1,the singular continuous spectrum of the operator is empty.

Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.

Joint Optimization for on-Demand Deployment of UAVs and Spectrum Allocation in UAVs-Assisted Communication

To improve the efficiency and fairness of the spectrum allocation for ground communication assisted by unmanned aerial vehicles(UAVs),a joint optimization method for on-demand deployment and spectrum allocation of UAVs is proposed,which is modeled as a mixed-integer non-convex optimization problem(MINCOP).An algorithm to estimate the minimum number of required UAVs is firstly proposed based on the pre-estimation and simulated annealing.The MINCOP is then decomposed into three sub-problems based on the block coordinate descent method,including the spectrum allocation of UAVs,the association between UAVs and ground users,and the deployment of UAVs.Specifically,the optimal spectrum allocation is derived based on the interference mitigation and channel reuse.The association between UAVs and ground users is optimized based on local iterated optimization.A particle-based optimization algorithm is proposed to resolve the subproblem of the UAVs deployment.Simulation results show that the proposed method could effectively improve the minimum transmission rate of UAVs as well as user fairness of spectrum allocation.

A research on the effect of plasma spectrum collection device on LIBS spectral intensity

Only a small amount of spectral information is collected because the collection solid angle of the optical fiber probe and lens is very limited when collecting spectral information.To overcome this limitation,this study presents a novel method for acquiring plasma spectral information from various spatial directions.A parabolic-shaped plasma spectral collection device(PSCD)is employed to effectively collect more spectral information into the spectrometer,thereby enhancing the overall spectral intensity.The research objects in this study were soil samples containing different concentrations of heavy metals Pb,Cr,and Cd.The results indicate that the PSCD significantly enhances the spectral signal,with an enhancement rate of up to 45%.Moreover,the signal-to-noise ratio also increases by as much as 36%.Simultaneously,when compared to the absence of a device,it is found that there is no significant variation in plasma temperature when the PSCD is utilized.This observation eliminates the impact of the spatial effect caused by the PSCD on the spectral intensity.Consequently,a concentrationspectral intensity relationship curve is established under the PSCD.The results revealed that the linear fitting R^(2)for Pb,Cr,and Cd increased by 0.011,0.001,and 0.054,respectively.Additionally,the limit of detection(LOD)decreased by 0.361 ppm,0.901 ppm,and 0.602 ppm,respectively.These findings indicate that the spectral enhancement rate elevates with the increase in heavy metal concentration.Hence,the PSCD can effectively enhance the spectral intensity and reduce the detection limit of heavy metals in soil.

Unraveling the mechanism of malancao in treating ulcerative colitis:A multi-omics approach

BACKGROUND Malancao(MLC)is a traditional Chinese medicine with a long history of utilization in treating ulcerative colitis(UC).Nevertheless,the precise molecular mechanisms underlying its efficacy remain elusive.This study leveraged ultrahigh-performance liquid chromatography coupled with exactive mass spectrometry(UHPLC-QE-MS),network pharmacology,molecular docking(MD),and gene microarray analysis to discern the bioactive constituents and the potential mechanism of action of MLC in UC management.AIM To determine the ingredients related to MLC for treatment of UC using multiple databases to obtain potential targets for fishing.METHODS This research employs UHPLC-QE-MS for the identification of bioactive compounds present in MLC plant samples.Furthermore,the study integrates the identified MLC compound-related targets with publicly available databases to elucidate common drug disease targets.Additionally,the R programming language is utilized to predict the central targets and molecular pathways that MLC may impact in the treatment of UC.Finally,MD are conducted using AutoDock Vina software to assess the affinity of bioactive components to the main targets and confirm their therapeutic potential.RESULTS Firstly,through a comprehensive analysis of UHPLC-QE-MS data and public database resources,we identified 146 drug-disease cross targets related to 11 bioactive components.The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis highlighted that common disease drug targets are primarily involved in oxidative stress management,lipid metabolism,atherosclerosis,and other processes.They also affect AGE-RAGE and apoptosis signaling pathways.Secondly,by analyzing the differences in diseases,we identified key research targets.These core targets are related to 11 active substances,including active ingredients such as quercetin and luteolin.Finally,MD analysis revealed the stability of compound-protein binding,particularly between JUNLuteolin,JUN-Quercetin,HSP90AA1-Wogonin,and HSP90AA1-Rhein.Therefore,this suggests that MLC may help alleviate intestinal inflammation in UC,restore abnormal lipid accumulation,and regulate the expression levels of core proteins in the intestine.CONCLUSION The utilization of MLC has demonstrated notable therapeutic efficacy in the management of UC by means of the compound target interaction pathway.The amalgamation of botanical resources,metabolomics,natural products,MD,and gene chip technology presents a propitious methodology for investigating therapeutic targets of herbal medicines and discerning novel bioactive constituents.

Wideband spectrum sensing using step-sampling based on the multipath nyquist folding receiver

Wideband spectrum sensing with a high-speed analog-digital converter(ADC) presents a challenge for practical systems.The Nyquist folding receiver(NYFR) is a promising scheme for achieving cost-effective real-time spectrum sensing,which is subject to the complexity of processing the modulated outputs.In this case,a multipath NYFR architecture with a step-sampling rate for the different paths is proposed.The different numbers of digital channels for each path are designed based on the Chinese remainder theorem(CRT).Then,the detectable frequency range is divided into multiple frequency grids,and the Nyquist zone(NZ) of the input can be obtained by sensing these grids.Thus,high-precision parameter estimation is performed by utilizing the NYFR characteristics.Compared with the existing methods,the scheme proposed in this paper overcomes the challenge of NZ estimation,information damage,many computations,low accuracy,and high false alarm probability.Comparative simulation experiments verify the effectiveness of the proposed architecture in this paper.

Uphill or downhill?Cropland use change and its drivers from the perspective of slope spectrum

The continuous decrease of low-slope cropland resources caused by construction land crowding poses huge threat to regional sustainable development and food security.Slope spectrum analysis of topographic and geomorphic features is considered as a digital terrain analysis method which reflects the macro-topographic features by using micro-topographic factors.However,pieces of studies have extended the concept of slope spectrum in the field of geoscience to construction land to explore its expansion law,while research on the slope trend of cropland from that perspective remains rare.To address the gap,in virtue of spatial analysis and geographically weighted regression(GWR)model,the cropland use change in the Yangtze River Basin(YRB)from 2000 to 2020 was analyzed and the driving factors were explored from the perspective of slope spectrum.Results showed that the slope spectrum curves of cropland area-frequency in the YRB showed a first upward then a downward trend.The change curve of the slope spectrum of cropland in each province(municipality)exhibited various distribution patterns.Quantitative analysis of morphological parameters of cropland slope spectrum revealed that the further down the YRB,the stronger the flattening characteristics,the more obvious the concentration.The province experienced the greatest downhill cropland climbing(CLC)was Shannxi,while province experienced the highest uphill CLC was Zhejiang.The most common cropland use change type in the YRB was horizontal expansion type.The factors affecting average cropland climbing index(ACCI)were quite stable in different periods,while population density(POP)changed from negative to positive during the study period.This research is of practical significance for the rational utilization of cropland at the watershed scale.

Robust Space-Time Adaptive Track-Before-Detect Algorithm Based on Persymmetry and Symmetric Spectrum

Underwater monopulse space-time adaptive track-before-detect method,which combines space-time adaptive detector(STAD)and the track-before-detect algorithm based on dynamic programming(DP-TBD),denoted as STAD-DP-TBD,can effectively detect low-speed weak targets.However,due to the complexity and variability of the underwater environment,it is difficult to obtain sufficient secondary data,resulting in a serious decline in the detection and tracking performance,and leading to poor robustness of the algorithm.In this paper,based on the adaptive matched filter(AMF)test and the RAO test,underwater monopulse AMF-DP-TBD algorithm and RAO-DP-TBD algorithm which incorporate persymmetry and symmetric spectrum,denoted as PSAMF-DP-TBD and PS-RAO-DP-TBD,are proposed and compared with the AMF-DP-TBD algorithm and RAO-DP-TBD algorithm based on persymmetry array,denoted as P-AMF-DP-TBD and P-RAO-DP-TBD.The simulation results show that the four methods can work normally with sufficient secondary data and slightly insufficient secondary data,but when the secondary data is severely insufficient,the P-AMF-DP-TBD and P-RAO-DP-TBD algorithms has failed while the PSAMF-DP-TBD and PS-RAO-DP-TBD algorithms still have good detection and tracking capabilities.