Research status and prospects of the fractal analysis of metal material surfaces and interfaces

As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal materials at various scales and dimensions.Conventional methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and interfaces.However,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal materials.From the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear surfaces.The relationship between the fractal dimensions and properties of metal material surfaces and interfaces is summarized.Starting from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be developed.It is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.

Analysis of the joint detection capability of the SMILE satellite and EISCAT-3D radar

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.

Establishment and performance analysis of a new multiplex detection method for influenza an and B virus antigen

BACKGROUND Influenza A and B virus detection is pivotal in epidemiological surveillance and disease management.Rapid and accurate diagnostic techniques are crucial for timely clinical intervention and outbreak prevention.Quantum dot-encoded microspheres have been widely used in immunodetection.The integration of quantum dot-encoded microspheres with flow cytometry is a well-established technique that enables rapid analysis.Thus,establishing a multiplex detection method for influenza A and B virus antigens based on flow cytometry quantum dot microspheres will help in disease diagnosis.AIM To establish a codetection method of influenza A and B virus antigens based on flow cytometry quantum dot-encoded microsphere technology,which forms the foundation for the assays of multiple respiratory virus biomarkers.METHODS Different quantum dot-encoded microspheres were used to couple the monoclonal antibodies against influenza A and B.The known influenza A and B antigens were detected both separately and simultaneously on a flow cytometer,and the detection conditions were optimized to establish the influenza A and B antigen codetection method,which was utilized for their detection in clinical samples.The results were compared with the fluorescence quantitative polymerase chain reaction(PCR)method to validate the clinical performance of this method.RESULTS The limits of detection of this method were 26.1 and 10.7 pg/mL for influenza A and B antigens,respectively,which both ranged from 15.6 to 250000 pg/mL.In the clinical sample evaluation,the proposed method well correlated with the fluorescent quantitative PCR method,with positive,negative,and overall compliance rates of 57.4%,100%,and 71.6%,respectively.CONCLUSION A multiplex assay for quantitative detection of influenza A and B virus antigens has been established,which is characterized by high sensitivity,good specificity,and a wide detection range and is promising for clinical applications.

Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.

Single Photon Detection Technology in Underwater Wireless Optical Communication:Modulation Modes and Error Correction Coding Analysis

This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.

Handwriting Analysis Based on Belief of Targeted Individual Supporting Insider Threat Detection

The Unintentional Insider Threat (UIT) concept highlights that insider threats might not always stem from malicious intent and can occur across various domains. This research examines how individuals with medical or psychological issues might unintentionally become insider threats due to their perception of being targeted. Insights from the survey A Survey of Unintentional Medical Insider Threat Category indicate that such perceptions can be linked to underlying health conditions. The study Emotion Analysis Based on Belief of Targeted Individual Supporting Insider Threat Detection reveals that anger is a common emotion among these individuals. The findings suggest that UITs are often linked to medical or psychological issues, with anger being prevalent. To mitigate these risks, it is recommended that Insider Threat programs integrate expertise from medicine, psychology, and cybersecurity. Additionally, handwriting analysis is proposed as a potential tool for detecting insider threats, reflecting the evolving nature of threat assessment methodologies.

Analysis of Detection and Monitoring Technology in the Construction and Maintenance of Large Bridges

Currently,there is significant attention placed on the construction,management,and maintenance of large service bridges.Within the realm of bridge maintenance management,the utilization of detection and monitoring technology is indispensable.By employing these technologies,we can effectively identify any structural defects within the bridge,promptly uncover unknown risks,proactively establish maintenance strategies,and prevent the rapid deterioration of bridge conditions.This article aims to explore the advantages of applying bridge monitoring and testing technology and to discuss various methods for implementing detection and monitoring technology throughout the construction,management,and maintenance phases of large bridges.Ultimately,this will contribute to ensuring the safe operation of large bridges.

Correlation analysis of human papillomavirus E6/E7 mRNA detection with diagnosis,prognosis and recurrence risk in patients with cervical epithelioma

BACKGROUND Cervical intraepithelial neoplasia(CIN)is an important precursor of cervical cancer.Early detection and treatment can reduce the incidence of cervical cancer.AIM To investigate the detection rate of human papillomavirus(HPV)E6/E7 mRNA in cervical tissue of patients with different types of epithelial cell neoplasia(CIN)and its relationship with CIN progression and diagnosis.METHODS One hundred women with HPV infection detected by cervical exfoliation cytology between January 2022 and January 2023 were retrospectively selected.These patients were graded CIN based on colposcopy and cervical pathology.The positive expression rates of HPV E6/E7 mRNA and HPV[polymerase chain reaction(PCR)-reverse dot crossing]were compared among all groups.Patients with HPV E6/E7 mRNA expression in the grade 1 CIN group were followed up for 1 yr.The relationship between atypical squamous epithelium and high malignant epithelial neoplasia was investigated by univariate and multivariate analysis.RESULTS The diagnostic sensitivity,specificity,and sensitivity of PCR-reverse point hybrid ization technology for secondary CIN were 70.41%,70.66%,and 0.714,respectively.Sensitivity and specificity for secondary CIN were 752%and 7853%,respectively,the area under the curve value was 0.789.Logistic Multifactorial model analysis revealed that the HPV positive rates and the HPV E6/E7 mRNA positive rates were independent risk factors of CIN grade I(P<0.05).In CIN grade I patients with positive for HPV E6/E7 mRNA,in its orientation to grade CIN patients,in its orientation to grade CIN patients,at 69.2%,compared with patients negative for HPV E6/E7 mRNA(30.8%),significant difference(P<0.05).CONCLUSION HPV E6/E7 mRNA and HPV(PCR-reverse dot hybrid)positive expression have a close relationship with CINgrade disease progression and is an independent risk factor for high-grade CIN lesions.

Analysis of Bridge-Bearing Capacity Detection and Evaluation Technology

A bridge project is taken as an example to analyze the application of bearing capacity detection and evaluation.This article provides a basic overview of the project,the application of bearing capacity detection technology,and the bearing capacity assessment analysis.It is hoped that this analysis can provide a scientific reference for the load-bearing capacity detection and evaluation work in bridge engineering projects,thereby achieving a scientific assessment of the overall load-bearing capacity of the bridge engineering structure.

Signal-to-noise ratio application to seismic marker analysis and fracture detection

Seismic data with high signal-to-noise ratios(SNRs) are useful in reservoir exploration. To obtain high SNR seismic data, significant effort is required to achieve noise attenuation in seismic data processing, which is costly in materials, and human and financial resources. We introduce a method for improving the SNR of seismic data. The SNR is calculated by using the frequency domain method. Furthermore, we optimize and discuss the critical parameters and calculation procedure. We applied the proposed method on real data and found that the SNR is high in the seismic marker and low in the fracture zone. Consequently, this can be used to extract detailed information about fracture zones that are inferred by structural analysis but not observed in conventional seismic data.

Design and analysis of traffic incident detection based on random forest

In order to avoid the noise and over fitting and further improve the limited classification performance of the real decision tree, a traffic incident detection method based on the random forest algorithm is presented. From the perspective of classification strength and correlation, three experiments are performed to investigate the potential application of random forest to traffic incident detection： comparison with a different number of decision trees; comparison with different decision trees; comparison with the neural network. The real traffic data of the 1-880 database is used in the experiments. The detection performance is evaluated by the common criteria including the detection rate, the false alarm rate, the mean time to detection, the classification rate and the area under the curve of the receiver operating characteristic （ROC）. The experimental results indicate that the model based on random forest can improve the decision rate, reduce the testing time, and obtain a higher classification rate. Meanwhile, it is competitive compared with multi-layer feed forward neural networks （MLF）.

Genetic Variation Analysis of 3D Gene and Molecular Detection of Porcine Kobuvirus in 2013-2014

[Objective] This study aimed to investigate the prevalence and variation of porcine kobuvirus （PKV） in suckling piglets in China. [Method] In 2013-2014, 224 feces samples from suckling piglets with diarrhea in 27 pig farms of five provinces in China were collected to detect 3D genes of PKV with RT-PCR method; the sequences and genetic variation of 29 PKV 3D genes were analyzed. [Result] Total positive rate of PKV in feces samples from suckling piglets with diarrhea was 65.18% （146/224）; total positive rate of PKV in pig farms was 85,2% （23/27）; nucleotide sequences and the deduced amino acid sequences of 29 PKV 3D genes shared 87.0%-100% and 92.7%-100% homologies with six PKV-related 3D sequences, respectively. [Conclusion] PKV infection is prevalent in suckling piglets in China; PKV 3D genes exhibit high diversity.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).

A Hybrid Intrusion Detection Method Based on Convolutional Neural Network and AdaBoost

To solve the problem of poor detection and limited application range of current intrusion detection methods,this paper attempts to use deep learning neural network technology to study a new type of intrusion detection method.Hence,we proposed an intrusion detection algorithm based on convolutional neural network(CNN)and AdaBoost algorithm.This algorithm uses CNN to extract the characteristics of network traffic data,which is particularly suitable for the analysis of continuous and classified attack data.The AdaBoost algorithm is used to classify network attack data that improved the detection effect of unbalanced data classification.We adopt the UNSW-NB15 dataset to test of this algorithm in the PyCharm environment.The results show that the detection rate of algorithm is99.27%and the false positive rate is lower than 0.98%.Comparative analysis shows that this algorithm has advantages over existing methods in terms of detection rate and false positive rate for small proportion of attack data.

Detection and Analysis of Routine Blood Indexes in Guike Pig

[Objectives] In this study,routine blood indexes of Guike pig were detected to clarify quantity variation and morphology distribution of different functional cells（ red blood cells,white blood cells and platelets）,thus providing reference data for immunological evaluation and disease resistance research of Guike pig. [Methods] Blood samples were collected from forty-four 49-day-old healthy Guike pigs（ 22 males and 22 females） once a week for seven consecutive weeks to detect routine blood indexes,and the results were compared with routine blood indexes of Landrace pig and Enshi black pig. [Results]Among red blood cell indexes of Guike pig at different day ages,red blood cell count（ RBC） and hemoglobin count（ HGB） both reached the lowest levels（ 6. 85 × 10^12/L and 97. 1 g/L）at 70 days of age,which were significantly lower than the corresponding indexes at 49,56,63,84 and 91 days of age（ P 〈 0. 05,similarly hereinafter）; mean corpuscular hemoglobin（ MCH） and mean corpuscular hemoglobin concentration（ MCHC） demonstrated basically the same variation pattern,which both reached the lowest levels（ 15. 11 pg and 275. 70 g/L） at 70 days of age and reached the highest levels（ 16. 40 pg and 314. 30 g/L） at 91 days of age; hematocrit（ HCT）,mean corpuscular volume（ MCV） and red blood cell distribution width（ RDW） exhibited relatively stable changes with no significant differences among different day ages（ P 〉 0. 05,similarly hereinafter）. Among white blood cell indexes of Guike pig at different day ages,white blood cell count（ WBC） reached the lowest level（ 13. 71 × 10^9/L） at 63 days of age and reached the highest level（ 17. 52 × 10^9/L） at 84 days of age,with significant differences; neutrophil count（ NEUT）reached the lowest level（ 3. 61 × 10^9/L） at 70 days of age,which was significantly lower than that at 49,56 and 77 days of age; lymphocyte count（ LYMPH） exhibited relatively stable changes and was not significantly affected by the increase in day age. Among platelet indexes of Guike pig at different day ages,platelet count（ PLT）,thrombocytocrit（ PCT） and platelet volume distribution width（ PDW） exhibited relatively stable changes among different day ages,which were not significantly affected by the increase in day age. Compared to 35-day-old Landrace pig and 5-month-old Enshi black pig,most routine blood indexes of Guike pig were similar to or ranged between those of Landrace pig and Enshi black pig except HCT,mean platelet volume（ MPV）,PCT and PDW. [Conclusions]Guike pig has a certain uniqueness in routine blood indexes,which has developed a stable immune system at 49-91 days of age.

Simulation Analysis and Experimental Study of Defect Detection Underwater by ACFM Probe

This article studies the application of the alternating current field measurement （ACFM） method in defect detection for underwater structures. Numerical model of the ACFM system is built for structure surface defect detection in seawater environment. Finite element simulation is performed to investigate rules and characteristics of the electromagnetic signal distribution in the defected area. In respect of the simulation results, underwater artificial crack detection experiments are designed and conducted for the ACFM system. The experiment results show that the ACFM system can detect cracks in underwater structures and the detection accuracy is higher than 85%. This can meet the engineering requirement of underwater structure defect detection. The results in this article can be applied to establish technical foundation for the optimization and development of ACFM based underwater structure defects detection system.

Esophageal cancer screening,early detection and treatment:Current insights and future directions

Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately 604000 new cases of esophageal cancer,resulting in 544000 deaths.The 5-year survival rate hovers around a mere 15%-25%.Notably,distinct variations exist in the risk factors associated with the two primary histological types,influencing their worldwide incidence and distribution.Squamous cell carcinoma displays a high incidence in specific regions,such as certain areas in China,where it meets the cost-effect-iveness criteria for widespread endoscopy-based early diagnosis within the local population.Conversely,adenocarcinoma(EAC)represents the most common histological subtype of esophageal cancer in Europe and the United States.The role of early diagnosis in cases of EAC originating from Barrett's esophagus(BE)remains a subject of controversy.The effectiveness of early detection for EAC,particularly those arising from BE,continues to be a debated topic.The variations in how early-stage esophageal carcinoma is treated in different regions are largely due to the differing rates of early-stage cancer diagnoses.In areas with higher incidences,such as China and Japan,early diagnosis is more common,which has led to the advancement of endoscopic methods as definitive treatments.These techniques have demonstrated remarkable efficacy with minimal complications while preserving esophageal functionality.Early screening,prompt diagnosis,and timely treatment are key strategies that can significantly lower both the occurrence and death rates associated with esophageal cancer.

Detection and Analysis of Ebola Virus in Sierra Leone-China Friendship Biosafety Laboratory from March 11 to April 20, 2015

Ebola virus disease reemerged in Western Africa in 2014.Chinese Center for Disease Control and Prevention dispatched the first Ebola virus（EBOV）detection team to run newly established Sierra Leone-China Friendship Biological Safety Laboratory.The aims of study were to understand epidemiology,clinical manifestations and survival time of EBOV in patient＇s blood.A total of 913specimens were tested between March 11 and April20, 2015. EBOV positivity occurred in 7.37% of the blood and 0.53% in throat swabs.

Capillary electrophoresis with electrochemiluminescence detection for the analysis of quinolone drugs and pharmacokinetics study

A novel method for the determination of two quinolone drugs norfloxacin （NOR） and levofloxacin （LVX） was described by capillary electrophoresis with electrochemiluminescence detection. The good relationship （r ≥ 0.9991） between peak area and concentration of analytes was established over two orders of magnitude. The limits of detection （LOD, S/N = 3） in standard solution are 4.8 × 10^-7 mol/L for NOR and 6.4 × 10^-7 mol/L for LVX, respectively. The limits of quantitation （LOQ, S/N = 10） in real human urine samples are 1.2 × 10^-6 mol/L for NOR and 1.4 × 10^-6 mol/L for LVX, respectively. The present method was successfully applied to the determination of NOR and LVX in human urine and the studv of oharmacokinetics of NOR.

A Review on Sources,Extractions and Analysis Methods of a Sustainable Biomaterial:Tannins

Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly to substitute petroleum-based products.They are a definite class of sustainable materials of the forestry industry.They have been in operation for hundreds of years to manufacture leather and now for a growing number of applications in a variety of other industries,such as wood adhesives,metal coating,pharmaceutical/medical applications and several others.This review presents the main sources,either already or potentially commercial of this forestry by-materials,their industrial and laboratory extraction systems,their systems of analysis with their advantages and drawbacks,be these methods so simple to even appear primitive but nonetheless of proven effectiveness,or very modern and instrumental.It constitutes a basic but essential summary of what is necessary to know of these sustainable materials.In doing so,the review highlights some of the main challenges that remain to be addressed to deliver the quality and economics of tannin supply necessary to fulfill the industrial production requirements for some materials-based uses.