Co-integration Analysis on the Relationship between Methane Energy Development and Economic Growth in the City of Huixian

Based on the statistical data of Huixian from 1992 to 2010, we analyze the long-term and short-term relationship between Huixian's methane energy development and GDP by using co-integration test and error correction model. The empirical results show that there is a long-term equilibrium relationship between methane energy and GDP in the city of Huixian, and which is the one-way Granger causality of methane and GDP. In conclusion, the paper puts forward some steps about spurring economic growth, methane development and utilization in Huixian.

Co-integration Analysis of the Relationship between Residents' Consumer Spending and GDP in Hubei Province

In accordance with the economic data from Statistical Communique on National Economy and Social Development in Hubei Province in the period 1980-2009, we use co-integration analysis method to research the impact of GDP growth on residents' consumer spending. Result shows that although there are differences between GDP and residents' consumer spending in the short term, the equilibrium relationship exists between them, namely, the co-integration relationship, showing consistency in trends.

Co-integration Analysis of the Relationship between New Product Output and R&D Investment in China’s Pharmaceutical Industry

Objective To study the possible relationship between the output of new products in China’s pharmaceutical industry and the investment in research and development(R&D),and to provide a theoretical basis for the decision-making of relevant enterprises and institutions.Methods The econometric software Stata 14 was used to perform unit root test on the relevant data.Then,a co-integration regression equation was established after stabilization,which was analyzed through co-integration test(E-G two-step method).Results and Conclusion There is a long-term equilibrium and short-term error correction relationship between the output of new products and the investment of R&D funds in China’s pharmaceutical industry.During the lagging periods from 1 to 6,R&D investment is the Granger reason for the output of new products.The investment of R&D funds has a positive effect on the output of new products and the effect is significant.Therefore,more investment should be made in R&D to enhance the output of new products.

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).

Social-ecological perspective on the suicidal behaviour factors of early adolescents in China:a network analysis

Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours(ie,suicidal ideation,plans and attempts)in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province,China',stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020.Network analysis was employed to examine the correlates of suicidal ideation,plans and attempts at four levels,namely individual(sex,academic performance,serious physical llness/disability,history of self-harm,depression,impulsivity,sleep problems,resilience),family(family economic status,relationship with mother,relationship with father,family violence,childhood abuse,parental mental illness),school(relationship with teachers,relationship with classmates,school-bullying victimisation and perpetration)and social(social support,satisfaction with society).Results In total,37.9%,19.0%and 5.5%of the students reported suicidal ideation,plans and attempts in the past 6 months,respectively.The estimated network revealed that suicidal ideation,plans and attempts were collectively associated with a history of self-harm,sleep problems,childhood abuse,school bullying and victimisation.Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse.Notably,the network also showed unique correlates of suicidal ideation(sex,weight=0.60;impulsivity,weight=0.24;family violence,weight=0.17;relationship with teachers,weight=-0.03;school-bullying perpetration,weight=0.22),suicidal plans(social support,weight=-0.15)and suicidal attempts(relationship with mother,weight=-0.10;parental mental llness,weight=0.61).Conclusions This study identified the correlates of suicidal ideation,plans and attempts,and provided practical implications for suicide prevention for young adolescents in China.Firstly,this study highlighted the importance of joint interventions across multiple departments.Secondly,the common risk factors of suicidal ideation,plans and attempts were elucidated.Thirdly,this study proposed target interventions to address the unique influencing factors of suicidal ideation,plans and attempts.

Advances in microfluidic-based DNA methylation analysis

DNA methylation has been extensively investigated in recent years,not least because of its known relationship with various diseases.Progress in analytical methods can greatly increase the relevance of DNA methylation studies to both clinical medicine and scientific research.Microflu-idic chips are excellent carriers for molecular analysis,and their use can provide improvements from multiple aspects.On-chip molecular analysis has received extensive attention owing to its advantages of portability,high throughput,low cost,and high efficiency.In recent years,the use of novel microfluidic chips for DNA methylation analysis has been widely reported and has shown obvious superiority to conventional methods.In this review,wefirst focus on DNA methylation and its applications.Then,we discuss advanced microfluidic-based methods for DNA methylation analysis and describe the great progress that has been made in recent years.Finally,we summarize the advantages that microfluidic technology brings to DNA methylation analysis and describe several challenges and perspectives for on-chip DNA methylation analysis.This review should help researchers improve their understanding and make progress in developing microfluidic-based methods for DNA methylation analysis.

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.

Lagrangian coherent structure analysis on transport of Acetes chinensis along coast of Lianyungang,China

Spatial heterogeneity or“patchiness”of plankton distributions in the ocean has always been an attractive and challenging scientific issue to oceanographers.We focused on the accumulation and dynamic mechanism of the Acetes chinensis in the Lianyungang nearshore licensed fishing area.The Lagrangian frame approaches including the Lagrangian coherent structures theory,Lagrangian residual current,and Lagrangian particle-tracking model were applied to find the transport pathways and aggregation characteristics of Acetes chinensis.There exist some material transport pathways for Acetes chinensis passing through the licensed fishing area,and Acetes chinensis is easy to accumulate in the licensed fishing area.The main mechanism forming this distribution pattern is the local circulation induced by the nonlinear interaction of topography and tidal flow.Both the Lagrangian coherent structure analysis and the particle trajectory tracking indicate that Acetes chinensis in the licensed fishing area come from the nearshore estuary.This work contributed to the adjustment of licensed fishing area and the efficient utilization of fishery resources.

Iron and ferritin effects on intensive care unit mortality:A metaanalysis

BACKGROUND The effect of serum iron or ferritin parameters on mortality among critically ill patients is not well characterized.AIM To determine the association between serum iron or ferritin parameters and mortality among critically ill patients.METHODS Web of Science,Embase,PubMed,and Cochrane Library databases were searched for studies on serum iron or ferritin parameters and mortality among critically ill patients.Two reviewers independently assessed,selected,and abstracted data from studies reporting on serum iron or ferritin parameters and mortality among critically ill patients.Data on serum iron or ferritin levels,mortality,and demographics were extracted.RESULTS Nineteen studies comprising 125490 patients were eligible for inclusion.We observed a slight negative effect of serum ferritin on mortality in the United States population[relative risk(RR)1.002;95%CI:1.002-1.004].In patients with sepsis,serum iron had a significant negative effect on mortality(RR=1.567;95%CI:1.208-1.925).CONCLUSION This systematic review presents evidence of a negative correlation between serum iron levels and mortality among patients with sepsis.Furthermore,it reveals a minor yet adverse impact of serum ferritin on mortality among the United States population.

Telomerase-related advances in hepatocellular carcinoma:A bibliometric and visual analysis

BACKGROUND As a critical early event in hepatocellular carcinogenesis,telomerase activation might be a promising and critical biomarker for hepatocellular carcinoma(HCC)patients,and its function in the genesis and treatment of HCC has gained much attention over the past two decades.AIM To perform a bibliometric analysis to systematically assess the current state of research on HCC-related telomerase.METHODS The Web of Science Core Collection and PubMed were systematically searched to retrieve publications pertaining to HCC/telomerase limited to“articles”and“reviews”published in English.A total of 873 relevant publications related to HCC and telomerase were identified.We employed the Bibliometrix package in R to extract and analyze the fundamental information of the publications,such as the trends in the publications,citation counts,most prolific or influential writers,and most popular journals;to screen for keywords occurring at high frequency;and to draw collaboration and cluster analysis charts on the basis of coauthorship and co-occurrences.VOSviewer was utilized to compile and visualize the bibliometric data.RESULTS A surge of 51 publications on HCC/telomerase research occurred in 2016,the most productive year from 1996 to 2023,accompanied by the peak citation count recorded in 2016.Up to December 2023,35226 citations were made to all publications,an average of 46.6 citations to each paper.The United States received the most citations(n=13531),followed by China(n=7427)and Japan(n=5754).In terms of national cooperation,China presented the highest centrality,its strongest bonds being to the United States and Japan.Among the 20 academic institutions with the most publications,ten came from China and the rest of Asia,though the University of Paris Cité,Public Assistance-Hospitals of Paris,and the National Institute of Health and Medical Research(INSERM)were the most prolific.As for individual contributions,Hisatomi H,Kaneko S,and Ide T were the three most prolific authors.Kaneko S ranked first by H-index,G-index,and overall publication count,while Zucman-Rossi J ranked first in citation count.The five most popular journals were the World Journal of Gastroenterology,Hepatology,Journal of Hepatology,Oncotarget,and Oncogene,while Nature Genetics,Hepatology,and Nature Reviews Disease Primers had the most citations.We extracted 2293 keywords from the publications,120 of which appeared more than ten times.The most frequent were HCC,telomerase and human telomerase reverse transcriptase(hTERT).Keywords such as mutational landscape,TERT promoter mutations,landscape,risk,and prognosis were among the most common issues in this field in the last three years and may be topics for research in the coming years.CONCLUSION Our bibliometric analysis provides a comprehensive overview of HCC/telomerase research and insights into promising upcoming research.

Micro segment analysis of supercritical methane thermal-hydraulic performance and pseudo-boiling in a PCHE straight channel

The printed circuit heat exchanger(PCHE) is receiving wide attention as a new kind of compact heat exchanger and is considered as a promising vaporizer in the LNG process. In this paper, a PCHE straight channel in the length of 500 mm is established, with a semicircular cross section in a diameter of 1.2 mm.Numerical simulation is employed to investigate the flow and heat transfer performance of supercritical methane in the channel. The pseudo-boiling theory is adopted and the liquid-like, two-phase-like, and vapor-like regimes are divided for supercritical methane to analyze the heat transfer and flow features.The results are presented in micro segment to show the local convective heat transfer coefficient and pressure drop. It shows that the convective heat transfer coefficient in segments along the channel has a significant peak feature near the pseudo-critical point and a heat transfer deterioration when the average fluid temperature in the segment is higher than the pseudo-critical point. The reason is explained with the generation of vapor-like film near the channel wall that the peak feature related to a nucleateboiling-like state and heat transfer deterioration related to a film-boiling-like state. The effects of parameters, including mass flow rate, pressure, and wall heat flux on flow and heat transfer were analyzed.In calculating of the averaged heat transfer coefficient of the whole channel, the traditional method shows significant deviation and the micro segment weighted average method is adopted. The pressure drop can mainly be affected by the mass flux and pressure and little affected by the wall heat flux. The peak of the convective heat transfer coefficient can only form at high mass flux, low wall heat flux, and near critical pressure, in which condition the nucleate-boiling-like state is easier to appear. Moreover,heat transfer deterioration will always appear, since the supercritical flow will finally develop into a filmboiling-like state. So heat transfer deterioration should be taken seriously in the design and safe operation of vaporizer PCHE. The study of this work clarified the local heat transfer and flow feature of supercritical methane in microchannel and contributed to the deep understanding of supercritical methane flow of the vaporization process in PCHE.

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

Metagenomic analysis revealing the metabolic role of microbial communities in the free amino acid biosynthesis of Monascus rice vinegar during fermentation

Free amino acid(FAA)is the important component of vinegar that infl uences quality perception and consumer acceptance.FAA is one of the major metabolites produced by microorganisms;however,the microbial metabolic network on FAA biosynthesis remains unclear.Through metagenomic analysis,this work aimed to elucidate the roles of microbes in FAA biosynthesis during Monascus rice vinegar fermentation.Taxonomic profiles from functional analyses showed 14 dominant genera with high contributions to the metabolism pathways.The metabolic network for FAA biosynthesis was then constructed,and the microbial distribution in different metabolic pathways was illuminated.The results revealed that 5 functional genera were closely involved in FAA biosynthesis.This study illuminated the metabolic roles of microorganisms in FAA biosynthesis and provided crucial insights into the functional attributes of microbiota in vinegar fermentation.

Application of Isogeometric Analysis Method in Three-Dimensional Gear Contact Analysis

Gears are pivotal in mechanical drives,and gear contact analysis is a typically difficult problem to solve.Emerging isogeometric analysis(IGA)methods have developed new ideas to solve this problem.In this paper,a threedimensional body parametric gear model of IGA is established,and a theoretical formula is derived to realize single-tooth contact analysis.Results were benchmarked against those obtained from commercial software utilizing the finite element analysis(FEA)method to validate the accuracy of our approach.Our findings indicate that the IGA-based contact algorithmsuccessfullymet theHertz contact test.When juxtaposed with the FEA approach,the IGAmethod demonstrated fewer node degrees of freedomand reduced computational units,all whilemaintaining comparable accuracy.Notably,the IGA method appeared to exhibit consistency in analysis accuracy irrespective of computational unit density,and also significantlymitigated non-physical oscillations in contact stress across the tooth width.This underscores the prowess of IGA in contact analysis.In conclusion,IGA emerges as a potent tool for addressing contact analysis challenges and holds significant promise for 3D gear modeling,simulation,and optimization of various mechanical components.

Preliminary electromagnetic analysis of the COOL blanket for CFETR

The supercritical CO_(2)cOoled Lithium-Lead(COOL)blanket has been designed as one advanced blanket candidate for the Chinese Fusion Engineering Test Reactor(CFETR).This work focuses on the electromagnetic(EM)loads(Maxwell force and Lorentz force)acting on the COOL blanket,which are important mechanical loads in further structural analysis of the COOL blanket.A 3D electromagnetic analysis is performed using the ANSYS finite element method to obtain EM loads on the COOL blanket in this study.At first,the magnetic scalar potential(MSP)method is used to obtain the magnetic field and the Maxwell force on the COOL blanket.Then,the magnetic vector potential(MVP)method is performed during a plasma disruption event to get the eddy current distribution.At last,a multi-step method is adopted for the calculation of the Lorentz force and the torque.The maximum Lorentz forces of inboard and outboard blanket structural components are 5624 kN and 2360 kN respectively.

SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

Geometric prior guided hybrid deep neural network for facial beauty analysis

Facial beauty analysis is an important topic in human society.It may be used as a guidance for face beautification applications such as cosmetic surgery.Deep neural networks(DNNs)have recently been adopted for facial beauty analysis and have achieved remarkable performance.However,most existing DNN-based models regard facial beauty analysis as a normal classification task.They ignore important prior knowledge in traditional machine learning models which illustrate the significant contribution of the geometric features in facial beauty analysis.To be specific,landmarks of the whole face and facial organs are introduced to extract geometric features to make the decision.Inspired by this,we introduce a novel dual-branch network for facial beauty analysis:one branch takes the Swin Transformer as the backbone to model the full face and global patterns,and another branch focuses on the masked facial organs with the residual network to model the local patterns of certain facial parts.Additionally,the designed multi-scale feature fusion module can further facilitate our network to learn complementary semantic information between the two branches.In model optimisation,we propose a hybrid loss function,where especially geometric regulation is introduced by regressing the facial landmarks and it can force the extracted features to convey facial geometric features.Experiments performed on the SCUT-FBP5500 dataset and the SCUT-FBP dataset demonstrate that our model outperforms the state-of-the-art convolutional neural networks models,which proves the effectiveness of the proposed geometric regularisation and dual-branch structure with the hybrid network.To the best of our knowledge,this is the first study to introduce a Vision Transformer into the facial beauty analysis task.

Automatic area estimation of algal blooms in water bodies from UAV images using texture analysis

Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and monitoring.Unmanned aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal resolutions.This study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using UAVs.As a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of HABs.Statistical features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence matrix.The results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.