A vector sum analysis method for stability evolution of expansive soil slope considering shear zone damage softening

Slope stability analysis is a classical mechanical problem in geotechnical engineering and engineering geology.It is of great significance to study the stability evolution of expansive soil slopes for engineering construction in expansive soil areas.Most of the existing studies evaluate the slope stability by analyzing the limit equilibrium state of the slope,and the analysis method for the stability evolution considering the damage softening of the shear zone is lacking.In this study,the large deformation shear mechanical behavior of expansive soil was investigated by ring shear test.The damage softening characteristic of expansive soil in the shear zone was analyzed,and a shear damage model reflecting the damage softening behavior of expansive soil was derived based on the damage theory.Finally,by skillfully combining the vector sum method and the shear damage model,an analysis method for the stability evolution of the expansive soil slope considering the shear zone damage softening was proposed.The results show that the shear zone subjected to large displacement shear deformation exhibits an obvious damage softening phenomenon.The damage variable equation based on the logistic function can be well used to describe the shear damage characteristics of expansive soil,and the proposed shear damage model is in good agreement with the ring shear test results.The vector sum method considering the damage softening behavior of the shear zone can be well applied to analyze the stability evolution characteristics of the expansive soil slope.The stability factor of the expansive soil slope decreases with the increase of shear displacement,showing an obvious progressive failure behavior.

A HEVC Video Steganalysis Method Using the Optimality of Motion Vector Prediction

Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in HEVC.Firstly,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of MVP.And then,we define the optimal rate of MVP as a steganalysis feature.Finally,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis methods.The experimental results demonstrate the effectiveness of the proposed feature set.Furthermore,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.

Performance Analysis of Support Vector Machine (SVM) on Challenging Datasets for Forest Fire Detection

This article delves into the analysis of performance and utilization of Support Vector Machines (SVMs) for the critical task of forest fire detection using image datasets. With the increasing threat of forest fires to ecosystems and human settlements, the need for rapid and accurate detection systems is of utmost importance. SVMs, renowned for their strong classification capabilities, exhibit proficiency in recognizing patterns associated with fire within images. By training on labeled data, SVMs acquire the ability to identify distinctive attributes associated with fire, such as flames, smoke, or alterations in the visual characteristics of the forest area. The document thoroughly examines the use of SVMs, covering crucial elements like data preprocessing, feature extraction, and model training. It rigorously evaluates parameters such as accuracy, efficiency, and practical applicability. The knowledge gained from this study aids in the development of efficient forest fire detection systems, enabling prompt responses and improving disaster management. Moreover, the correlation between SVM accuracy and the difficulties presented by high-dimensional datasets is carefully investigated, demonstrated through a revealing case study. The relationship between accuracy scores and the different resolutions used for resizing the training datasets has also been discussed in this article. These comprehensive studies result in a definitive overview of the difficulties faced and the potential sectors requiring further improvement and focus.

Predicting Turbidite Channel in Deep-Water Canyon Based on Grey Relational Analysis-Support Vector Machine Model:A Case Study of the Lingshui Depression in Qiongdongnan Basin,South China Sea

The turbidite channel of South China Sea has been highly concerned.Influenced by the complex fault and the rapid phase change of lithofacies,predicting the channel through conventional seismic attributes is not accurate enough.In response to this disadvantage,this study used a method combining grey relational analysis(GRA)and support vectormachine(SVM)and established a set of prediction technical procedures suitable for reservoirs with complex geological conditions.In the case study of the Huangliu Formation in Qiongdongnan Basin,South China Sea,this study first dimensionalized the conventional seismic attributes of Gas Layer Group I and then used the GRA method to obtain the main relational factors.A higher relational degree indicates a higher probability of responding to the attributes of the turbidite channel.This study then accumulated the optimized attributes with the highest relational factors to obtain a first-order accumulated sequence,which was used as the input training sample of the SVM model,thus successfully constructing the SVM turbidite channel model.Drilling results prove that the GRA-SVMmethod has a high drilling coincidence rate.Utilizing the core and logging data and taking full use of the advantages of seismic inversion in predicting the sand boundary of water channels,this study divides the sedimentary microfacies of the Huangliu Formation in the Lingshui 17-2 Gas Field.This comprehensive study has shown that the GRA-SVM method has high accuracy for predicting turbidite channels and can be used as a superior turbidite channel prediction method under complex geological conditions.

Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

Algorithms for steganography are methods of hiding data transfers in media files.Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image analysis.Images with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for classification.To address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of images.Support Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or cover.The Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the proposedmethod.Using WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.

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.

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).

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.

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.

Causal Analysis Between Rice Growth and Cadmium Accumulation and Transfer under Arbuscular Mycorrhizal Inoculation

Cadmium(Cd)contamination in rice has been a serious threat to human health.To investigate the effects of arbuscular mycorrhizal fungi(AMF)on the Cd translocation in rice,a controlled pot experiment was conducted.The results indicated that AMF significantly increased rice biomass,with an increase of up to 40.0%,particularly in root biomass by up to 68.4%.Notably,the number of prominent rice individuals also increased,and their plasticity was enhanced following AMF inoculation.AMF led to an increase in the net photosynthetic rate and antioxidant enzyme activity of rice.In the AMF treatment group,the Cd concentration in the rice roots was significantly higher(19.1%‒68.0%)compared with that in the control group.Conversely,the Cd concentration in the rice seeds was lower in the AMF treatment group,indicating that AMF facilitated the sequestration of Cd in rice roots and reduced Cd accumulation in the seeds.Path coefficients varied across different treatments,suggesting that AMF inoculation reduced the direct impact of soil Cd concentration on the total Cd accumulation in seeds.The translocation of Cd was consistently associated with simultaneous growth dilution and compensatory accumulation as a result of mycorrhizal effects.Our study quantitatively analyzed this process through path analysis and clarified the causal relationship between rice growth and Cd transfer under the influence of AMF.

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.

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

Identification of an Aux/IAA regulator for flesh firmness using combined GWAS and bulked segregant RNA-Seq analysis in watermelon

Watermelon is a highly cultivated fruit crop renowned for its quality properties of fruit flesh.Among various quality factors,fruit flesh firmness is a crucial quality parameter influencing the fruit texture,shelf life and its commercial value.The auxin/indole-3-acetic acid(Aux/IAA)plays a significant role in fruit development and ripening of non-climacteric fruits.However,the regulatory mechanism of Aux/IAA in controlling fruit flesh firmness and ripening in watermelon remains unknown.In this study,we employed an integrative approach combining genome-wide association study(GWAS)and bulked segregant RNA-Seq analysis(BSR-Seq)to identify an overlapping candidate region between 12776310 and 12968331 bp on chromosome 6,underlying an auxin-responsive gene(Aux/IAA)associated with flesh firmness in watermelon.Transcriptome analysis,followed by real-time quantitative reverse transcription PCR(qRT-PCR),confirmed that the expression of Aux/IAA was consistently higher in fruits with high flesh firmness.The sequence alignment revealed a single base mutation in the coding region of Aux/IAA.Furthermore,the concomitant Kompetitive/Competitive allele-specific PCR(KASP)genotyping data sets for F2 population and germplasm accessions identified Aux/IAA as a strong candidate gene associated with flesh firmness.Aux/IAA was enriched in the plant hormone signal transduction pathway,involving cell enlargement and leading to low flesh firmness.We determined the higher accumulation of abscisic acid(ABA)in fruits with low flesh firmness than hard flesh.Moreover,overexpression of Aux/IAA induced higher flesh firmness with an increased number of fruit flesh cells while reducing ABA content and flesh cell sizes.Additionally,the allelic variation in Aux/IAA for soft flesh firmness was found to exist in Citrullus mucosospermus and gradually fixed into Citrullus lanatus during domestication,indicating that soft flesh firmness was a domesticated trait.These findings significantly enhanced our understanding of watermelon fruit flesh firmness and consequently the watermelon fruit quality.

Coupling Analysis of Multiple Machine Learning Models for Human Activity Recognition

Artificial intelligence(AI)technology has become integral in the realm of medicine and healthcare,particularly in human activity recognition(HAR)applications such as fitness and rehabilitation tracking.This study introduces a robust coupling analysis framework that integrates four AI-enabled models,combining both machine learning(ML)and deep learning(DL)approaches to evaluate their effectiveness in HAR.The analytical dataset comprises 561 features sourced from the UCI-HAR database,forming the foundation for training the models.Additionally,the MHEALTH database is employed to replicate the modeling process for comparative purposes,while inclusion of the WISDM database,renowned for its challenging features,supports the framework’s resilience and adaptability.The ML-based models employ the methodologies including adaptive neuro-fuzzy inference system(ANFIS),support vector machine(SVM),and random forest(RF),for data training.In contrast,a DL-based model utilizes one-dimensional convolution neural network(1dCNN)to automate feature extraction.Furthermore,the recursive feature elimination(RFE)algorithm,which drives an ML-based estimator to eliminate low-participation features,helps identify the optimal features for enhancing model performance.The best accuracies of the ANFIS,SVM,RF,and 1dCNN models with meticulous featuring process achieve around 90%,96%,91%,and 93%,respectively.Comparative analysis using the MHEALTH dataset showcases the 1dCNN model’s remarkable perfect accuracy(100%),while the RF,SVM,and ANFIS models equipped with selected features achieve accuracies of 99.8%,99.7%,and 96.5%,respectively.Finally,when applied to the WISDM dataset,the DL-based and ML-based models attain accuracies of 91.4%and 87.3%,respectively,aligning with prior research findings.In conclusion,the proposed framework yields HAR models with commendable performance metrics,exhibiting its suitability for integration into the healthcare services system through AI-driven applications.

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.

Perception of dental appearance and aesthetic analysis among patients,laypersons and dentists

BACKGROUND Current concepts of beauty are increasingly subjective,influenced by the viewpoints of others.The aim of the study was to evaluate divergences in the perception of dental appearance and smile esthetics among patients,laypersons and dental practitioners.The study goals were to evaluate the influence of age,sex,education and dental specialty on the participants’judgment and to identify the values of different esthetic criteria.Patients sample included 50 patients who responded to a dental appearance questionnaire(DAQ).Two frontal photographs were taken,one during a smile and one with retracted lips.Laypersons and dentists were asked to evaluate both photographs using a Linear Scale from(0-10),where 0 represent(absolutely unaesthetic)and 10 represent(absolutely aesthetic).One-way analysis of variance(ANOVA)and t-test analysis were measured for each group.Most patients in the sample expressed satisfaction with most aspects of their smiles and dental appearance.Among laypersons(including 488 participants),47 pictures“with lips”out of 50 had higher mean aesthetic scores compared to pictures“without lips”.Among the dentist sample,90 dentists’perception towards the esthetic smile and dental appearance for photos“with lips”and“without lips”were the same for 23 out of 50 patients.Perception of smile aesthetics differed between patients,laypersons and dentists.Several factors can contribute to shape the perception of smile aesthetic.AIM To compare the perception of dental aesthetic among patients,laypersons,and professional dentists,to evaluate the impact of age,sex,educational background,and income on the judgments made by laypersons,to assess the variations in experience,specialty,age,and sex on professional dentists’judgment,and to evaluate the role of lips,skin shade and tooth shade in different participants’judgments.METHODS Patients sample included 50 patients who responded to DAQ.Two frontal photographs were taken:one during a smile and one with retracted lips.Laypersons and dentists were asked to evaluate both photographs using a Linear Scale from(0-10),where 0 represent(absolutely unaesthetic)and 10 represent(absolutely aesthetic).One-way ANOVA and t-test analysis were measured for each group.RESULTS Most patients in the sample expressed satisfaction with most aspects of their smiles and dental appearance.Among laypersons(including 488 participants),47 pictures“with lips”out of 50 had higher mean aesthetic scores compared to pictures“without lips”.Whereas among the dentist sample,90 dentists’perception towards the esthetic smile and dental appearance for photos“with lips”and“without lips”were the same for 23 out of 50 patients.Perception of smile aesthetics differed between patients,laypersons and dentists.CONCLUSION Several factors can contribute to shape the perception of smile aesthetic.