THE BOUNDEDNESS OF OPERATORS ON WEIGHTED MULTI-PARAMETER LOCAL HARDY SPACES

Though atomic decomposition is a very useful tool for studying the boundedness on Hardy spaces for some sublinear operators,untill now,the boundedness of operators on weighted Hardy spaces in a multi-parameter setting has been established only by almost orthogonality estimates.In this paper,we mainly establish the boundedness on weighted multi-parameter local Hardy spaces via atomic decomposition.

Multi-Parameter Influence Analysis of Interaction Between Internal Solitary Wave and Fixed Submerged Body

To obtain the interaction characteristics between Internal solitary waves(ISWs)and submerged bodies,a three-dimensional numerical model for simulating ISWs was established in the present study based on the RANS equation.The velocity entrance method was adopted to generate the ISWs.First,the reliability of this numerical model was validated by comparing it with theoretical and literature results.Then,the influence of environmental and navigation parameters on interactions between ISWs and a fixed SUBOFF-submerged body was studied.According to research,the hydrodynamic performance of the submerged body has been significantly impacted by the ISWs when the body is nearing the central region of the wave.Besides,the pitching moment(y')will predominate when the body encounters the ISWs at a certain angle between 0°and 180°,and the lateral force is larger than the horizontal force.Additionally,the magnitude of the force acting on the body is mostly affected by the wave amplitude.The variation of the vertical force is the main way that ISWs affect the hydrodynamic performance of the bodies.The investigations and findings discussed above can serve as a guide to forecast how ISWs will interact with submerged bodies.

Feedback control and quantum error correction assisted quantum multi-parameter estimation

Quantum metrology provides a fundamental limit on the precision of multi-parameter estimation,called the Heisenberg limit,which has been achieved in noiseless quantum systems.However,for systems subject to noises,it is hard to achieve this limit since noises are inclined to destroy quantum coherence and entanglement.In this paper,a combined control scheme with feedback and quantum error correction(QEC)is proposed to achieve the Heisenberg limit in the presence of spontaneous emission,where the feedback control is used to protect a stabilizer code space containing an optimal probe state and an additional control is applied to eliminate the measurement incompatibility among three parameters.Although an ancilla system is necessary for the preparation of the optimal probe state,our scheme does not require the ancilla system to be noiseless.In addition,the control scheme in this paper has a low-dimensional code space.For the three components of a magnetic field,it can achieve the highest estimation precision with only a 2-dimensional code space,while at least a4-dimensional code space is required in the common optimal error correction protocols.

Investigation multi-target synergistic mechanism of Choerospondias axillaris in the treat of cerebral ischemia based on systems pharmacology and experimental verification

Background:Choerospondias axillaris(CA)is a traditional Mongolian medicine that has been proven to have a good therapeutic effect on cerebrovascular disease.Cerebral Ischemia(CI)is a severe and life-threatening cerebrovascular disease.However,the specific mechanism of action of CA in the treatment of CI is still unclear.Methods:In this study,the related targets and pathways of CA in the treatment of CI were first predicted by system pharmacology and then verified by relevant experiments.Results:The results showed that 12 active ingredients and 208 targets were selected.Further validation through protein-protein interaction(PPI)network analysis and active ingredients-target-pathway(A-T-P)network analysis has confirmed the pivotal roles of the main bioactive constituents,including quercetin,kaempferol,naringin,β-sitosterol,and gallic acid.These components exert their anti-ischemic effects by modulating key targets such as IL6,TNF,MAPK3,and CASP3,thereby regulating the PI3K-Akt,HIF-1,and MAPK signaling pathways,which are integral to processes like inflammation,apoptosis,and oxidative stress.More importantly,through experimental verification,this study confirmed our prediction that CAE significantly reduced neurological function scores,infarct volume,and the percentage of apoptosis neurons.Conclusion:This indicates that CA acts on CI through multi-target synergistic mechanism,and this study provides theoretical basis for the clinical application of CA.

Research on Rotating Machinery Fault Diagnosis Based on Improved Multi-target Domain Adversarial Network

Aiming at the problems of low efficiency,poor anti-noise and robustness of transfer learning model in intelligent fault diagnosis of rotating machinery,a new method of intelligent fault diagnosis of rotating machinery based on single source and multi-target domain adversarial network model(WDMACN)and Gram Angle Product field(GAPF)was proposed.Firstly,the original one-dimensional vibration signal is preprocessed using GAPF to generate the image data including all time series.Secondly,the residual network is used to extract data features,and the features of the target domain without labels are pseudo-labeled,and the transferable features among the feature extractors are shared through the depth parameter,and the feature extractors of the multi-target domain are updated anatomically to generate the features that the discriminator cannot distinguish.The modelt through adversarial domain adaptation,thus achieving fault classification.Finally,a large number of validations were carried out on the bearing data set of Case Western Reserve University(CWRU)and the gear data.The results show that the proposed method can greatly improve the diagnostic efficiency of the model,and has good noise resistance and generalization.

Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices

Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.

Multi-parameter gene expression profiling of peripheral blood for early detection of hepatocellular carcinoma

AIM In our previous study, we have built a nine-gene(GPC3, HGF, ANXA1, FOS, SPAG9, HSPA1 B, CXCR4, PFN1, and CALR) expression detection system based on the Ge XP system. Based on peripheral blood and Ge XP, we aimed to analyze the results of genes expression by different multi-parameter analysis methods and build a diagnostic model to classify hepatocellular carcinoma(HCC) patients and healthy people.METHODS Logistic regression analysis, discriminant analysis, classification tree analysis, and artificial neural network were used for the multi-parameter gene expression analysis method. One hundred and three patients with early HCC and 54 age-matched healthy normal controls were used to build a diagnostic model. Fiftytwo patients with early HCC and 34 healthy people were used for validation. The area under the curve, sensitivity, and specificity were used as diagnostic indicators.RESULTS Artificial neural network of the total nine genes had the best diagnostic value, and the AUC, sensitivity, and specificity were 0.943, 98%, and 85%, respectively. At last, 52 HCC patients and 34 healthy normal controls were used for validation. The sensitivity and specificity were 96% and 86%, respectively.CONCLUSION Multi-parameter analysis methods may increase the diagnostic value compared to single factor analysis and they may be a trend of the clinical diagnosis in the future.

Highly maneuvering target tracking using multi-parameter fusion Singer model

An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.

Study on Environmental Multi-parameter Sensor Based on MEMS

A new membrane type Al_2O_3 micromachining material is used.We develop an environmental multi-parameter detection micro-system,which implements the detection to temperature,humidity,wind speed,and CO.The test results illustrate that the heat-release unit in micro-system intercross greatly affects other sensing units on the temperature.We study the method of etching process,which formed cavity to reduce the heat exchange efficiency and decrease temperature intercross effect.

Multi-parameters of Thermal Infrared Remote Sensing Anomalies of the Earthquake

Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.

Design and Realization of Signal Processing Platform of Multi-Parameter Wearable Medical Devices

This paper presents a design of new type of multi-parameter wearable medical devices signal processing platform. The signal processing algorithm has a QRS-wave detection algorithm based on LADT, wavelet transformation and threshold detection with TMS320VC5509 DSP system. The DSP can greatly increase the speed of QRS-wave detection, and the results can be practical used for multi-parameter wearable device detection of abnormal ECG.

Existence and joint continuity of local time of multi-parameter fractional Lévy processes

In this paper, we introduce the definition of a multi-parameter fractional Lévy process and its local time, and show its decomposition. Using the decomposition, we prove existence and joint continuity of its local time.

Case Retrieval Method of Multi-parameter for Customized Product

The CBR (Case-Based Reasoning) usually is been used to accomplish customized products by variant design or reusable design.In the CBR,retrieve is very important.A simple case retrieval method is been brought forward to retrieve a opti- mal prototype based on using inputted multi-parameters,it can be programmed easily.An example has been proved this method can find optimal prototype for new design task efficiently.

MULTI-PARAMETER ACCELERATED MODIFIED NEWTON-RAPHSON METHODS FOR RIGIDPLASTIC FE ANALYSIS

Applications of certain multi-parameter acceleration techniques used with themodified New-ton-Raphson (mN-R) methods to solve the nonlinear equations arising from rigid-plasticfinite element analysis are investigated. New modified multi-parameter techniques, developed fromCrisfield's multi-parameter methods, are utilized to solve these nonlinear equations. The numericalperformance of these techniques is compared with the standard Newton-Raphson method (sN-R),Crisfield's single parameter method (C1), Crisfield's two parameter method (C2) and Crisfield'sthree parameter method (C3). The new techniques do not involve additional residual force calculationand require little extra computational effort. In addition, they are more robust and efficient thanother existing acceleration techniques.

Fecal microbial biomarkers combined with multi-target stool DNA test improve diagnostic accuracy for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a major global health burden.The current diagnostic tests have shortcomings of being invasive and low accuracy.AIM To explore the combination of intestinal microbiome composition and multi-target stool DNA(MT-sDNA)test in the diagnosis of CRC.METHODS We assessed the performance of the MT-sDNA test based on a hospital clinical trial.The intestinal microbiota was tested using 16S rRNA gene sequencing.This case-control study enrolled 54 CRC patients and 51 healthy controls.We identified biomarkers of bacterial structure,analyzed the relationship between different tumor markers and the relative abundance of related flora components,and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size,redundancy analysis,and random forest analysis.RESULTS MT-sDNA was associated with Bacteroides.MT-sDNA and carcinoembryonic antigen(CEA)were positively correlated with the existence of Parabacteroides,and alpha-fetoprotein(AFP)was positively associated with Faecalibacterium and Megamonas.In the random forest model,the existence of Streptococcus,Escherichia,Chitinophaga,Parasutterella,Lachnospira,and Romboutsia can distinguish CRC from health controls.The diagnostic accuracy of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC was 97.1%,with a sensitivity and specificity of 98.1%and 92.3%,respectively.CONCLUSION There is a positive correlation of MT-sDNA,CEA,and AFP with intestinal microbiome.Eight biomarkers including six genera of gut microbiota,MT-sDNA,and CEA showed a prominent sensitivity and specificity for CRC prediction,which could be used as a non-invasive method for improving the diagnostic accuracy for this malignancy.

Joint target assignment and power allocation in the netted C-MIMO radar when tracking multi-targets in the presence of self-defense blanket jamming

The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.

THE MULTI-PARAMETER INVERSION OF ELASTIC WAVE IN HALF-SPACE

The multi-parameter inverse scattering problem of elastic waveequation with single fre- quency is investigated within Bornapproximation. By use of a wideband measuring scheme in which bothtransmitters and receivers scan over the half-space surface, theformula of the scattering field of elastic wave is derived. Fourtypes of mode conversion of elastic wave(P→P, P→S, S→P, S→S)areseparated from the scattering field. These components containsufficient information for usto recon- struct the configuration ofthe density and Lame parameters of the medium.

Non-relativistic scattering amplitude for a new multi-parameter exponential-type potential

In this paper, we study the scattering properties of s-wave Schrdinger equation for the multi-parameter potential,which can be reduced into four special cases for different values of potential parameters, i.e., Hulthn, Manning–Rosen,and Eckart potentials. We also obtain and investigate the scattering amplitudes of these special cases. Some numerical results are also obtained and reported.

Elastic direct envelope inversion based on wave mode decomposition for multi-parameter reconstruction of strong-scattering media

The parameter reconstruction of strong-scattering media is a challenge for conventional full waveform inversion(FWI).Direct envelope inversion(DEI)is an effective method for large-scale and strongscattering structures imaging without the need of low-frequency seismic data.However,the current DEI methods are all based on the acoustic approximation.Whereas,in real cases,seismic records are the combined effects of the subsurface multi-parameters.Therefore,the study of DEI in elastic media is necessary for the accurate inversion of strong-scattering structures,such as salt domes.In this paper,we propose an elastic direct envelope inversion(EDEI)method based on wave mode decomposition.We define the objective function of EDEI using multi-component seismic data and derive its gradient formulation.To reduce the coupling effects of multi-parameters,we introduce the wave mode decomposition method into the gradient calculation of EDEI.The update of Vp is primarily the contributions of decomposed P-waves.Two approaches on Vs gradient calculation are proposed,i.e.using the petrophysical relation and wave mode decomposition method.Finally,we test the proposed method on a layered salt model and the SEG/EAGE salt model.The results show that the proposed EDEI method can reconstruct reliable large-scale Vp and Vs models of strong-scattering salt structures.The successive elastic FWI can obtain high-precision inversion results of the strong-scattering salt model.The proposed method also has a good anti-noise performance in the moderate noise level.

Effect of Multi-parameter Environmental Factors on Cucumber Leaf Surface Wetness

In this study, artificial leaf resistance was used to simulate leaf wetness. Specific to the solar greenhouse environment in Tianjin, microclimate monitoring equipment was installed for the collection of temperature group and humidity group data, as well as solar radiation and leaf wetness in the greenhouse. In order to reduce the complexity of multivariate factor prediction and ensure the richness of selected data types, correlation analysis was made to the 2 groups of data, screening 5 000 groups of data, including the humidity group data RH, RH_(20), RH_(40), temperature group data T, T_(20), T_(40), and solar radiation W. The data were then analyzed by principal component analysis, screening out 4 groups of principal components to show the leaf wetness index.