Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

Corrigendum to“Atomic-scale electromagnetic theory bridging optics in microscopic world and macroscopic world”

The signs of the electric field markers in Figs.2 and 4 of the paper[Chin.Phys.B 32104211(2023)]have been corrected.These modifications do not affect the results derived in the paper.

Single-cell manipulation by two-dimensional micropatterning

Cells are highly sensitive to their geometrical and mechanical microenvironment that directly regulate cell shape,cytoskeleton and organelle,as well as the nucleus morphology and genetic expression.The emerging two-dimensional micropatterning techniques offer powerful tools to construct controllable and well-organized microenvironment for single-cell level investigations with qualitative analysis,cellular standardization,and in vivo environment mimicking.Here,we provide an overview of the basic principle and characteristics of the two most widely-used micropatterning techniques,including photolithographic micropatterning and soft lithography micropatterning.Moreover,we summarize the application of micropatterning technique in controlling cytoskeleton,cell migration,nucleus and gene expression,as well as intercellular communication.

Altered expression of nuclear matrix proteins in etoposide induced apoptosis in HL-60 cells

The events of cell death and the expression of nuclear matrix protein (NMP) have been investigated in a promyelocytic leukemic cell line HL-60 induced with etoposide. By means of TUNEL assay, the nuclei displayed a characteristic morphology change, and the amount of apoptotic cells increased early and reached maximun about 39% after treatment with etoposide for 2 h. Nucleosomal DNA fragmentation was observed after treatment for 4 h. The morphological change of HL-60 cells, thus, occurred earlier than the appearance of DNA ladder. Total nuclear matrix proteins were analyzed by 2-dimensional gel electrophoresis. Differential expression of 59 nuclear matrix proteins was found in 4 h etoposide treated cells. Western blotting was then performed on three nuclear matrix acssociated proteins, PML, HSC70 and NuMA. The expression of the suppressor PML protein and heat shock protein HSC70 were significantly upregulated after etoposide treatment, while NuMA, a nuclear mitotic apparatus protein, was down regulated. These results demonstrate that significant biochemical alterations in nuclear matrix proteins take place during the apoptotic process.

CHANGES OF NUCLEAR MATRIX PROTEIN AND ITS RELATIONSHIP WITH c-erbB-2 IN HUMAN COLON ADENOCARCINOMA

Objective： Nuclear matrix protein is tissue, cell-type specific, and tumor-relative. It plays an important role in the regulation of intranuclear processes. Some researches also showed that a c-erbB-2 promoter-specific DNA-binding nuclear matrix protein is present only in malignant human breast tissues and induces mitogenesis and cell surface expression of the c-erbB-2 protein in resting NIH/3T3 cells. But it is not clear that how it in colon adenocarcinomas. Methods： Two-dimensional gel electrophoretic method was used for NMP identification and immunohistochemistry was used for c-erbB-2 detection in 12 cases of colon adenocarcinomas and matched adjacent normal colon tissues. Results： 5 different nuclear matrix proteins （named C1-C5） were identified in 12 colon adenocarcinoma specimens, but not in the matched adjacent normal colon tissues; 3 nuclear matrix proteins （named N1-N3） were identified in all 12 matched adjacent normal colon tissues, but not in colon adenocarcinoma specimens. A nuclear matrix protein （named N4） was detected in all of 9 moderated-well differentiated adenocarcinomas and all 12 matched adjacent normal colon tissues, but not in 3 poor-differentiated adenocarcinomas. All of the 10 colon adenocarcinomas which had the nuclear matrix protein C4 were c-erbB-2 expression positive. Conclusion： The data suggest that there are specific nuclear matrix proteins in colon adenocarcinomas and its subtypes, which maybe valuable to serve as markers of colon adenocarcinomas in future. Nuclear matrix protein C4 probably is a c-erbB-2 promotor-specific nuclear matrix protein in colon adenocarcinomas, and may induce the expression of c-erbB-2.

Eigenfunction expansion method of upper triangular operator matrixand application to two-dimensional elasticity problems based onstress formulation

This paper studies the eigenfunction expansion method to solve the two dimensional （2D） elasticity problems based on the stress formulation. The fundamental system of partial differential equations of the 2D problems is rewritten as an upper tri angular differential system based on the known results, and then the associated upper triangular operator matrix matrix is obtained. By further research, the two simpler com plete orthogonal systems of eigenfunctions in some space are obtained, which belong to the two block operators arising in the operator matrix. Then, a more simple and conve nient general solution to the 2D problem is given by the eigenfunction expansion method. Furthermore, the boundary conditions for the 2D problem, which can be solved by this method, are indicated. Finally, the validity of the obtained results is verified by a specific example.

Atomic-scale electromagnetic theory bridging optics in microscopic world and macroscopic world

Atoms in the microscopic world are the basic building blocks of the macroscopic world. In this work, we construct an atomic-scale electromagnetic theory that bridges optics in the microscopic and macroscopic worlds. As the building block of the theory, we use the microscopic polarizability to describe the optical response of a single atom, solve the transport of electromagnetic wave through a single atomic layer under arbitrary incident angle and polarization of the light beam, construct the single atomic layer transfer matrix for light transport across the atomic layer. Based on this transfer matrix, we get the analytical form of the dispersion relation, refractive index, and transmission/reflection coefficient of the macroscopic medium. The developed theory can handle single-layer and few-layers of homogeneous and heterogeneous 2D materials, investigate homogeneous 2D materials with various vacancies or insertion atomic-layer defects, study compound 2D materials with a unit cell composed of several elements in both the lateral and parallel directions with respect to the light transport.

An LMI Method to Robust Iterative Learning Fault-tolerant Guaranteed Cost Control for Batch Processes

Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller (ILRGCC). A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities (LMIs), and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.

Identification of differentially expressed proteins in poplar leaves in-duced by Marssonina brunnea f. sp. Multigermtubi

Black spot disease in poplar is a disease of the leaf caused by fungus. The major pathogen is Marssonina brunnea f. sp. multigermtubi. To date, little is known about the molecular mechanism of poplar （M. brunnea） interaction. In order to identify the proteins related to disease resistance and understand its molecular basis, the clone ＂NL895＂ （P. euramericana CL＂NL895＂）, which is highly resistant to M. brunnea f. sp. multigermtubi, was used in this study. We used two-dimensional gel electrophoresis （2-DE） and mass spectrometry （MS） to identify the proteins in poplar leaves that were differentially expressed in response to black spot disease pathogen, M. brunnea f. sp. multigermtubi. Proteins extracted from poplar leaves at 0, 12, 24, 48, and 72 h after pathogen-inoculation were separated by 2-DE, About 500 reproducible protein spots were detected, of which 40 protein spots displayed differential expression in levels and were subjected to Matrix assisted laser desorption/ionization time of flight mass spectrometry （MALDI-TOF MS） followed by database searching. According to the function, the identified proteins were sorted into five categories, that is, protein synthesis, metabolism, defense response and unclassified proteins.

Design of Discrete-time Repetitive Control System Based on Two-dimensional Model

This paper presents a novel design method for discrete-time repetitive control systems （RCS） based on two-dimensional （2D） discrete-time model. Firstly, the 2D model of an RCS is established by considering both the control action and the learning action in RCS. Then, through constructing a 2D state feedback controller, the design problem of the RCS is converted to the design problem of a 2D system. Then, using 2D system theory and linear matrix inequality （LMI） method, stability criterion is derived for the system without and with uncertainties, respectively. Parameters of the system can be determined by solving the LMI of the stability criterion. Finally, numerical simulations validate the effectiveness of the proposed method.

Establishment and Preliminary Application of Two dimensional Electrophoresis and Mass Spectrometry in Ovary Study

Objective To apply two-dimensional electrophoresis and mass spectrometry in the ovary proteome researchMethods Protein extractions from mouse ovaries were run in IPGphor isoelectric focus system with 11 cm and 24 cm IPG strips respectively (pH 3～10, 0.3 mm thick), then the protein spots were identified by mass spectrometry.Results The ovary protein exactions separated by two-dimensional electrophoresis have got high resolution, and identifing protein by mass spectrometry was highly efficient and facilitly. These two techniques should facilitate further investigation of female reproduction proteome research.Conclusion These two rapid high resolutions and efficient techniques have a variety of applications foreground in female reproduction proteome pattern research.

Fast forward modeling of gravity anomalies for two-dimensional bodies of arbitrary shape and density distribution

A fast and high precision spatial domain algorithm is presented for forward modeling of two-dimensional(2D)body gravity anomalies of arbitrary shape and density distribution.The new algorithm takes advantage of the convolution properties of the expression for 2D gravity anomalies,uses a rectangular cell as a grid subdivision unit,and then 2D bodies with irregular cross-sections are approximated by a combination of 2D bodies with a rectangular cross section.The closed-form expression is used to calculate the gravitational anomalies of the combination of 2D bodies with a rectangular cross section.To improve computing effi ciency,the new algorithm uses a fast algorithm for the implementation of the Toeplitz matrix and vector multiplication.The synthetic 2D models with rectangular and circular cross-sections and constant and variable densities are designed to evaluate the computational accuracy and speed of the new algorithm.The experiment results show that the computation costs less than 6 s for a grid subdivision with 10000×10000 elements.Compared to the traditional forward modeling methods,the proposed method significantly improved computational effi ciency while guaranteeing computational accuracy.

Further studies on stability analysis of nonlinear Roesser-type two-dimensional systems

This paper is concerned with further relaxations of the stability analysis of nonlinear Roesser-type two-dimensional （2D） systems in the Takagi-Sugeno fuzzy form. To achieve the goal, a novel slack matrix variable technique, which is homogenous polynomially parameter-dependent on the normalized fuzzy weighting functions with arbitrary degree, is developed and the algebraic properties of the normalized fuzzy weighting functions are collected into a set of augmented matrices. Consequently, more information about the normalized fuzzy weighting functions is involved and the relaxation quality of the stability analysis is significantly improved. Moreover, the obtained result is formulated in the form of linear matrix inequalities, which can be easily solved via standard numerical software. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed result.

Design of observer-based discrete repetitive-control system based on 2D model

A discrete observer-based repetitive control(RC) design method for a linear system with uncertainties was presented based on two-dimensional(2D) system theory. Firstly, a 2D discrete model was established to describe both the control behavior within a repetition period and the learning process taking place between periods. Next, by converting the designing problem of repetitive controller into one of the feedback gains of reconstructed variables, the stable condition was obtained through linear matrix inequality(LMI) and also the gain coefficient of repetitive system. Numerical simulation shows an exceptional feasibility of this proposal with remarkable robustness and tracking speed.

RF-PSSM:A Combination of Rotation Forest Algorithm and Position-Specific Scoring Matrix for Improved Prediction of Protein-Protein Interactions Between Hepatitis C Virus and Human

The identification of hepatitis C virus(HCV)virus-human protein interactions will not only help us understand the molecular mechanisms of related diseases but also be conductive to discovering new drug targets.An increasing number of clinically and experimentally validated interactions between HCV and human proteins have been documented in public databases,facilitating studies based on computational methods.In this study,we proposed a new computational approach,rotation forest position-specific scoring matrix(RF-PSSM),to predict the interactions among HCV and human proteins.In particular,PSSM was used to characterize each protein,two-dimensional principal component analysis(2DPCA)was then adopted for feature extraction of PSSM.Finally,rotation forest(RF)was used to implement classification.The results of various ablation experiments show that on independent datasets,the accuracy and area under curve(AUC)value of RF-PSSM can reach 93.74% and 94.29%,respectively,outperforming almost all cutting-edge research.In addition,we used RF-PSSM to predict 9 human proteins that may interact with HCV protein E1,which can provide theoretical guidance for future experimental studies.

Investigation on surface roughness,residual stress and fatigue property of milling in-situ TiB_2/7050Al metal matrix composites

For higher efficiency and precision manufacturing,more and more attentions are focused on the surface roughness and residual stress of machined parts to obtain a good fatigue life.At present,the in-situ TiB_2/7050 Al metal matrix composites are widely researched due to its attractive properties such as low density,good wear resistance and improved strength.It is of great significance to investigate the machined surface roughness,residual stress and fatigue life for higher efficiency and precision manufacturing of this new kind material.In this study,the surface roughness including two-dimensional and three-dimensional roughness,residual stress and fatigue life of milling in-situ TiB_2/7050 Al metal matrix composites were analyzed.It was found from comparative investigation that the three-dimensional surface roughness would be more appropriate to represent the machined surface profile of milling particle reinforced metal matrix composites.The cutting temperature played a great role on the residual stress.However,the effect of increasing cutting force could slow down the transformation from compressive stress to tensile stress under 270°C.An exponential relationship between three-dimensional roughness and fatigue life was established and the main fracture mechanism was brittle fracture with observation of obvious shellfish veins,river pattern veins and wave shaped veins in fracture surface.

Two-dimensional van der Waals thin film transistors as active matrix for spatially resolved pressure sensing

The development of pressure sensor arrays capable of distinguishing the shape and texture details of objects is of considerable interest in the emerging fields of smart robots,prostheses,human-machine interfaces,and artificial intelligence(AI).Here we report an integrated pressure sensor array,by combining solution-processed two-dimensional(2D)MoS2 van der Waals(vdW)thin film transistor(TFT)active matrix and conductive micropyramidal pressure-sensitive rubber(PSR)electrodes made of polydimethylsiloxane/carbon nanotube composites,to achieve spatially revolved pressure mapping with excellent contrast and low power consumption.We demonstrate a 10×10 active matrix by using the 2D MoS2 vdW-TFTs with high on-off ratio>10^(6),minimal hysteresis,and excellent device-to-device uniformity.The combination of the vdW-TFT active matrix with the highly uniform micropyramidal PSR electrodes creates an integrated pressure sensing array for spatially resolved pressure mapping.This study demonstrates that the solution-processed 2D vdW-TFTs offer a solution for active-matrix control of pressure sensor arrays,and could be extended for other active-matrix arrays of electronic or optoelectronic devices.

Real-time SERS monitoring anticancer drug release along with SERS/MR imaging for pH-sensitive chemo-phototherapy

In situ and real-time monitoring of responsive drug release is critical for the assessment of pharmacodynamics in chemotherapy.In this study,a novel pH-responsive nanosystem is proposed for real-time monitoring of drug release and chemo-phototherapy by surface-enhanced Raman spectroscopy(SERS).The Fe3O4@Au@Ag nanoparticles(NPs)deposited graphene oxide(GO)nanocomposites with a high SERS activity and stability are synthesized and labeled with a Raman reporter 4-mercaptophenylboronic acid(4-MPBA)to form SERS probes(GO-Fe3O4@Au@Ag-MPBA).Furthermore,doxorubicin(DOX)is attached to SERS probes through a pH-responsive linker boronic ester(GO-Fe3O4@Au@Ag-MPBA-DOX),accompanying the 4-MPBA signal change in SERS.After the entry into tumor,the breakage of boronic ester in the acidic environment gives rise to the release of DOX and the recovery of 4-MPBA SERS signal.Thus,the DOX dynamic release can be monitored by the real-time changes of 4-MPBA SERS spectra.Additionally,the strong T2 magnetic resonance(MR)signal and NIR photothermal transduction efficiency of the nanocomposites make it available for MR imaging and photothermal therapy(PTT).Altogether,this GO-Fe3O4@Au@Ag-MPBA-DOX can simultaneously fulfill the synergistic combination of cancer cell targeting,pH-sensitive drug release,SERS-traceable detection and MR imaging,endowing it great potential for SERS/MR imaging-guided efficient chemo-phototherapy on cancer treatment.

Hurricane eye morphology extraction from SAR images by texture analysis

Tropical hurricanes are among the most devastating hazards on Earth.Knowledge about its intense inner-core structure and dynamics will improve hurricane forecasts and advisories.The precise morphological parameters extracted from high-resolution spaceborne Synthetic Aperture Radar(SAR)images,can play an essential role in further exploring and monitoring hurricane dynamics,especially when hurricanes undergo amplification,shearing,eyewall replacements and so forth.Moreover,these parameters can help to build guidelines for wind calibration of the more abundant,but lower resolution scatterometer wind data,thus better linking scatterometer wind fields to hurricane categories.In this paper,we develop a new method for automatically extracting the hurricane eyes from C-band SAR data by constructing Gray Level-Gradient Co-occurrence Matrices(GLGCMs).The hurricane eyewall is determined with a two-dimensional vector,generated by maximizing the class entropy of the hurricane eye region in GLGCM.The results indicate that when the hurricane is weak,or the eyewall is not closed,the hurricane eye extracted with this automatic method still agrees with what is observed visually,and it preserves the texture characteristics of the original image.As compared to Du’s wavelet analysis method and other morphological analysis methods,the approach developed here has reduced artefacts due to factors like hurricane size and has lower programming complexity.In summary,the proposed method provides a new and elegant choice for hurricane eye morphology extraction.

Gene Expression Profile Changes in Germinating Rice

Water absorption is a prerequisite for seed germination. During imbibition, water influx causes the resumption of many physiological and metabolic processes in growing seed. In order to obtain more complete knowledge about the mechanism of seed germination, two-dimensional gel electrophoresis was applied to investigate the protein profile changes of rice seed during the first 48 h of imbibition. Thirty- nine differentially expressed proteins were identified, including 19 down-regulated and 20 up-regulated proteins. Storage proteins and some seed development- and desiccation-associated proteins were down regulated. The changed patterns of these proteins indicated extensive mobilization of seed reserves. By contrast, catabolism-associated proteins were up regulated upon imbibition. Semi-quantitative real time polymerase chain reaction analysis showed that most of the genes encoding the down- or up- regulated proteins were also down or up regulated at mRNA level. The expression of these genes was largely consistent at mRNA and protein levels. In providing additional information concerning gene regulation in early plant life, this study will facilitate understanding of the molecular mechanisms of seed germination.