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.

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.

Morphological analysis for thermodynamics of cavitation collapse near fractal solid wall

A fractal geometric boundary with natural wall features is introduced into a hybrid lattice-Boltzmann-method(LBM)multiphase model. The physical model of cavitation bubble collapse near the irregular geometric wall is established to study the thermodynamic characteristics of the bubble collapse. Due to the lack of periodicity, symmetry, spatial uniformity and obvious correlation in the LBM simulation of the bubble collapse near the fractal wall, the morphological analysis based on Minkowski functional is introduced into the thermodynamic investigation of cavitation bubble so as to analyze and obtain the effective information. The results show that the Minkowski functional method can employed to study the temperature information in complex physical fields hierarchically and quantitatively. The high/low temperature region of the cavitation flow is explored, and thermal effect between irregular and fractal geometric wall and cavitation bubble can be revealed. It illustrates that LBM and morphological analysis complement each other, and morphological analysis can also be used as an optional and potential tool in research field of complex multiphase flows.

The value of toxicological analysis in acute poisoning patients with uncertain exposure histories:a retrospective and descriptive study from an institute of poisoning

BACKGROUND:In clinical practice,some patients might not be able or unwilling to provide a thorough history of medication and poison exposure.The aim of this study was to use toxicological analysis to examine the clinical characteristics of patients with acute poisoning whose exposure history was uncertain from a toxicological analysis perspective.METHODS:This was a retrospective and descriptive study from an institute of poisoning.Patient registration information and test reports spanning the period from April 1,2020 to March 31,2022,were obtained.Patients with uncertain exposure histories and who underwent toxicological analysis were included.Clinical manifestations and categories of toxics were analyzed.RESULTS:Among the 195 patients with positive toxicological analysis results,the main causes of uncertain exposure history was disturbance of consciousness(62.6%),unawareness(23.6%)and unwillingness or lack of cooperation(13.8%).The predominant clinical manifestations were disturbed consciousness(62.6%),followed by vomiting and nausea(14.4%)and liver function abnormalities(8.7%).A comparison of clinical manifestations between patients with positive and negative(n=99)toxicological analyses results revealed significantly different proportions of disturbances in consciousness(63%vs.21%),dizziness(1.5%vs.5.1%),multi-organ failure(1.5%vs.7.1%),and local pain(0 vs 4%).The main categories of substances involved were psychiatric medications(23.1%),sedatives(20.5%),insecticides(13.8%),and herbicides(12.8%).CONCLUSION:The clinical manifestations of acute poisoning in patients with an uncertain exposure history are diverse and nonspecific,and toxicological analysis plays a pivotal role in the diagnosis and differential diagnosis of such patients.

Insights into the dwarfing mechanism of pear(Pyrus betulaefolia) based on anatomical and structural analysis using X-ray scanning

The lack of a suitable rootstock to control scion growth has limited the development of high-density plantations in pear production, which is partly attributed to poor understanding of the dwarfing mechanism. In the present study, the rootstock of the dwarf-type pear (Pyrus betulaefolia)PY-9’ was identified and used as the material for anatomical analysis.PY-9’ grew to half the tree height of the normal cultivar Zhengdu’, along with fewer internodes and shorter length. Significant differences in growth rate betweenPY-9’ andZhengdu’ were detected at approximately 30 days after full bloom, which corresponded with the time of the greatest difference in water potential between the dwarf and normal cultivar.PY-9’ showed a higher photosynthetic rate thanZhengdu’. Anatomical analysis showed thatPY-9’ had higher area ratios of both phloem and xylem and more developed vascular tissues thanZhengdu’. The three-dimensional reconstructed skeleton of the xylem from X-ray computed tomography scanning revealed greater intervessel connectivity inZhengdu’ than inPY-9’, which could contribute to the more vigorous growth ofZhengdu’. This study thus provides the first comparison of the microstructural properties of xylem elements between a dwarfing-type and vigorous-type pear rootstock, providing new insights into the dwarfing mechanism in pear and facilitating breeding of dwarf pear rootstocks to increase crop productivity.

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.

Simplified quantitative analysis method and its application in the insitu synthesized copper-based azide chips

Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

New insights into developmental biology of Eimeria tenella revealed by comparative analysis of mRNA N6-methyladenosine modification between unsporulated oocysts and sporulated oocysts

Evidence showed that N6-methyladenosine(m^(6)A)modification plays a pivotal role in influencing RNA fate and is strongly associated with cell growth and developmental processes in many species.However,no information regarding m^(6)A modification in Eimeria tenella is currently available.In the present study,we surveyed the transcriptome-wide prevalence of m^(6)A in sporulated oocysts and unsporulated oocysts of E.tenella.Methylated RNA immunoprecipitation sequencing(MeRIP-seq)analysis showed that m^(6)A modification was most abundant in the coding sequences,followed by stop codon.There were 3,903 hypermethylated and 3,178 hypomethylated mRNAs in sporulated oocysts compared with unsporulated oocysts.Further joint analysis suggested that m^(6)A modification of the majority of genes was positively correlated with mRNA expression.The mRNA relative expression and m^(6)A level of the selected genes were confirmed by quantitative reverse transcription PCR(RT-qPCR)and MeRIP-qPCR.GO and KEGG analysis indicated that differentially m^(6)A methylated genes(DMMGs)with significant differences in mRNA expression were closely related to processes such as regulation of gene expression,epigenetic,microtubule,autophagy-other and TOR signaling.Moreover,a total of 96 DMMGs without significant differences in mRNA expression showed significant differences at protein level.GO and pathway enrichment analysis of the 96 genes showed that RNA methylation may be involved in cell biosynthesis and metabolism of E.tenella.We firstly present a map of RNA m^(6)A modification in E.tenella,which provides significant insights into developmental biology of E.tenella.

Degradation analysis and doping modification optimization for high-voltage P-type layered cathode in sodium-ion batteries

Advancing high-voltage stability of layered sodium-ion oxides represents a pivotal avenue for their progress in energy storage applications.Despite this,a comprehensive understanding of the mechanisms underpinning their structural deterioration at elevated voltages remains insufficiently explored.In this study,we unveil a layer delamination phenomenon of Na_(0.67)Ni_(0.3)Mn_(0.7)O_(2)(NNM)within the 2.0-4.3 V voltage,attributed to considerable volumetric fluctuations along the c-axis and lattice oxygen reactions induced by the simultaneous Ni^(3+)/Ni^(4+)and anion redox reactions.By introducing Mg doping to diminished Ni-O antibonding,the anion oxidation-reduction reactions are effectively mitigated,and the structural integrity of the P2 phase remains firmly intact,safeguarding active sites and precluding the formation of novel interfaces.The Na_(0.67)Mg_(0.05)Ni_(0.25)Mn_(0.7)O_(2)(NMNM-5)exhibits a specific capacity of100.7 mA h g^(-1),signifying an 83%improvement compared to the NNM material within the voltage of2.0-4.3 V.This investigation underscores the intricate interplay between high-voltage stability and structural degradation mechanisms in layered sodium-ion oxides.

Data driven analysis reveals prognostic genes and immunological targets in human sepsis-associated acute kidney injury

BACKGROUND:The molecular mechanism of sepsis-associated acute kidney injury(SA-AKI)is unclear.We analyzed co-differentially expressed genes(co-DEGs)to elucidate the underlying mechanism and intervention targets of SA-AKI.METHODS:The microarray datasets GSE65682,GSE30718,and GSE174220 were downloaded from the Gene Expression Omnibus(GEO)database.We identified the co-DEGs and constructed a gene co-expression network to screen the hub genes.We analyzed immune correlations and disease correlations and performed functional annotation of the hub genes.We also performed single-cell and microenvironment analyses and investigated the enrichment pathways and the main transcription factors.Finally,we conducted a correlation analysis to evaluate the role of the hub genes.RESULTS:Interleukin 32(IL32)was identified as the hub gene in SA-AKI,and the main enriched signaling pathways were associated with hemopoiesis,cellular response to cytokine stimulus,inflammatory response,and regulation of kidney development.Additionally,IL32 was significantly associated with mortality in SA-AKI patients.Monocytes,macrophages,T cells,and NK cells were closely related to IL32 and were involved in the immune microenvironment in SA-AKI patients.IL32 expression increased significantly in the kidney of septic mouse.Toll-like receptor 2(TLR2)was significantly and negatively correlated with IL32.CONCLUSION:IL32 is the key gene involved in SA-AKI and is significantly associated with prognosis.TLR2 and relevant immune cells are closely related to key genes.

The Clinical Value of Ultrasound Image Texture Analysis in the Diagnosis of Uterine Adhesions

Purpose: This review examines the diagnostic value of transvaginal 3D ultrasound image texture analysis for the diagnosis of uterine adhesions. Materials and Methods: The total clinical data of 53 patients with uterine adhesions diagnosed by hysteroscopy and the imaging data of transvaginal three-dimensional ultrasound from the Second Affiliated Hospital of Chongqing Medical University from June 2022 to August 2023 were retrospectively analysed. Based on hysteroscopic surgical records, patients were divided into two independent groups: normal endometrium and uterine adhesion sites. The samples were divided into a training set and a test set, and the transvaginal 3D ultrasound was used to outline the region of interest (ROI) and extract texture features for normal endometrium and uterine adhesions based on hysteroscopic surgical recordings, the training set data were feature screened and modelled using lasso regression and cross-validation, and the diagnostic efficacy of the model was assessed by applying the subjects’ operating characteristic (ROC) curves. Results: For each group, 290 texture feature parameters were extracted and three higher values were screened out, and the area under the curve of the constructed ultrasonographic scoring model was 0.658 and 0.720 in the training and test sets, respectively. Conclusion Relative clinical value of transvaginal three-dimensional ultrasound image texture analysis for the diagnosis of uterine adhesions.

Cross-Project Software Defect Prediction Based on SMOTE and Deep Canonical Correlation Analysis

Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project.However,existing CPDP methods only consider linear correlations between features(indicators)of the source and target projects.These models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target projects.As a result,the performance of such CPDP models is compromised.In this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as S-DCCA.Canonical Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the dataset.The redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss function.Finally,cross-project defect prediction is achieved through the application of the SMOTE data sampling technique.Area Under Curve(AUC)and F1 scores(F1)are used as evaluation metrics.This paper conducted experiments on 27 projects from four public datasets to validate the proposed method.The results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 score.This indicates that the proposed method exhibits favorable performance characteristics.

Physiological and Transcriptome Analysis Illuminates the Molecular Mechanisms of the Drought Resistance Improved by Alginate Oligosaccharides in Triticum aestivum L.

Alginate oligosaccharides(AOS)enhance drought resistance in wheat(Triticum aestivum L.),but the definite mechanisms remain largely unknown.The physiological and transcriptome responses of wheat seedlings treated with AOS were analyzed under drought stress simulated with polyethylene glycol-6000.The results showed that AOS promoted the growth of wheat seedlings and reduced oxidative damage by improving peroxidase and superoxide dismutase activities under drought stress.A total of 10,064 and 15,208 differentially expressed unigenes(DEGs)obtained from the AOS treatment and control samples at 24 and 72 h after dehydration,respectively,were mainly enriched in the biosynthesis of secondary metabolites(phenylpropanoid biosynthesis,flavonoid biosynthesis),carbohydrate metabolism(starch and sucrose metabolism,carbon fixation in photosynthetic organisms),lipid metabolism(fatty acid elongation,biosynthesis of unsaturated fatty acids,alpha-linolenic acid metabolism,cutin,suberine and wax biosynthesis),and signaling transduction pathways.The up-regulated genes were related to,for example,chlorophyll a-b binding protein,amylosynthease,phosphotransferase,peroxidase,phenylalanine ammonia lyase,flavone synthase,glutathione synthetase.Signaling molecules(including MAPK,plant hormones,H_(2)O_(2) and calcium)and transcription factors(mainly including NAC,MYB,MYB-related,WRKY,bZIP family members)were involved in the AOS-induced wheat drought resistance.The results obtained in this study help underpin the mechanisms of wheat drought resistance improved by AOS,and provides a theoretical basis for the application of AOS as an environmentally sustainable biological method to improve drought resistance in agriculture.

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.

Block Incremental Dense Tucker Decomposition with Application to Spatial and Temporal Analysis of Air Quality Data

How can we efficiently store and mine dynamically generated dense tensors for modeling the behavior of multidimensional dynamic data?Much of the multidimensional dynamic data in the real world is generated in the form of time-growing tensors.For example,air quality tensor data consists of multiple sensory values gathered from wide locations for a long time.Such data,accumulated over time,is redundant and consumes a lot ofmemory in its raw form.We need a way to efficiently store dynamically generated tensor data that increase over time and to model their behavior on demand between arbitrary time blocks.To this end,we propose a Block IncrementalDense Tucker Decomposition(BID-Tucker)method for efficient storage and on-demand modeling ofmultidimensional spatiotemporal data.Assuming that tensors come in unit blocks where only the time domain changes,our proposed BID-Tucker first slices the blocks into matrices and decomposes them via singular value decomposition(SVD).The SVDs of the time×space sliced matrices are stored instead of the raw tensor blocks to save space.When modeling from data is required at particular time blocks,the SVDs of corresponding time blocks are retrieved and incremented to be used for Tucker decomposition.The factor matrices and core tensor of the decomposed results can then be used for further data analysis.We compared our proposed BID-Tucker with D-Tucker,which our method extends,and vanilla Tucker decomposition.We show that our BID-Tucker is faster than both D-Tucker and vanilla Tucker decomposition and uses less memory for storage with a comparable reconstruction error.We applied our proposed BID-Tucker to model the spatial and temporal trends of air quality data collected in South Korea from 2018 to 2022.We were able to model the spatial and temporal air quality trends.We were also able to verify unusual events,such as chronic ozone alerts and large fire events.

Composition Analysis and Identification of Ancient Glass Products Based on L1 Regularization Logistic Regression

In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.

Data-driven analysis of chemicals,proteins and pathways associated with peanut allergy:from molecular networking to biological interpretation

Peanut allergy is majorly related to severe food induced allergic reactions.Several food including cow's milk,hen's eggs,soy,wheat,peanuts,tree nuts(walnuts,hazelnuts,almonds,cashews,pecans and pistachios),fish and shellfish are responsible for more than 90%of food allergies.Here,we provide promising insights using a large-scale data-driven analysis,comparing the mechanistic feature and biological relevance of different ingredients presents in peanuts,tree nuts(walnuts,almonds,cashews,pecans and pistachios)and soybean.Additionally,we have analysed the chemical compositions of peanuts in different processed form raw,boiled and dry-roasted.Using the data-driven approach we are able to generate new hypotheses to explain why nuclear receptors like the peroxisome proliferator-activated receptors(PPARs)and its isoform and their interaction with dietary lipids may have significant effect on allergic response.The results obtained from this study will direct future experimeantal and clinical studies to understand the role of dietary lipids and PPARisoforms to exert pro-inflammatory or anti-inflammatory functions on cells of the innate immunity and influence antigen presentation to the cells of the adaptive immunity.

Coupling Coordination Analysis of Cropland Intensification and Agroecosystem Services:Evidence from Loess Plateau in Shaanxi Province,China

One of the greatest challenges in the agroecosystem is to improve cropland intensification while preserving agroecosystem services.While many studies have investigated the effect of cropland intensification on agroecosystem service,the interactive coupling and coordination among these factors remain largely unexplored.In view of this,this study performed a case study of the Loess Plateau in Shaanxi Province,China and constructed comprehensive evaluation models to quantify the cropland intensification and agroecosystem service in this area.Balance analysis and the coupling coordination degree model were used to evaluate the interactive relationship between cropland intensification and agroecosystem service,and statistical analysis and spatial autocorrelation were used to analyze the spatial characteristics and potential mechanism of the coupling coordination.Results show that both the cropland intensification and agroecosystem service in the study area were relatively low yet gradually increased from 2000 to 2020.Agroecosystem service lag was identified as the dominant unbalanced development type.Improving the supply capacity of agroecosystem services plays a key role in the balanced development of cropland in the Loess Plateau.The coupling coordination degree between cropland intensification and agroecosystem service ranges from basic coordination to serious incoordination.Therefore,cropland intensification practices in the area should be optimized to enhance this coordination degree.An upward trend was also observed in the coupling coordination degree from2000 to 2020.The withdrawal of marginal cropland in the Grain for Green program is one of the most important reasons for this trend,especially for the northern region.Around 83.6%of the high-high clusters are concentrated in the southern region of the Loess Plateau,whereas 70.5%of the low-low clusters are distributed in the northern region.These clustering characteristics are mainly attributed to the environmental suitability of these areas for agriculture and their degree of economic development.

Meta analysis of the efficacy of western medicine combined with Qiliqiangxin capsule versus western medicine alone in the treatment of chronic heart failure

Objective: To compare the clinical efficacy of conventional Western medicine combined with Qiliqiangxin capsule and western medicine alone in the treatment of chronic heart failure, and to prove that Qiliqiangxin capsule combined treatment has more advantages, providing reference for clinical decision-making in the treatment of chronic heart failure. Methods: Randomized controlled trials (RCTs) of conventional Western medicine treatment and Western medicine combined with Qiliqiangxin capsule in the treatment of chronic heart failure were searched in databases such as PubMed, Embase, Webofscience, CNKI, WanFang, VIP, and CBM. The bias risk assessment was conducted using the RCT tool recommended by Cochrane, and then the meta-analysis was performed using RevMan5.4 and Stata17 software. Compare the efficacy evaluation of cardiac function, left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter (LVEDD), cardiac stroke output (SV), 6-minute walking test (6MWT), and N-terminal proBNP in the conventional western medicine combined with Qiliqiangxin capsule group (hereinafter referred to as the treatment group) and the conventional western medicine group (hereinafter referred to as the control group). Results: A total of 20 RCTs meeting the criteria were included, including 2953 patients, including 1508 in the treatment group and 1445 in the control group. The results of meta-analysis showed that the treatment group had significantly better cardiac function evaluation, LVEF, LVEDD, SV, 6MWT, and NT-proBNP improvement than the control group. Its central functional efficacy evaluation (OR=2.09,95% CI: 1.71-2.55, P<0.001), LVEF (WMD=7.05,95% CI: 5.30-8.79, P<0.00001), LVEDD (WMD=6.73, 95% CI: 3.18-10.29, P=0.0002), SV (WMD=6.73, 95% CI: 3.18-10.29, P=0.0002), 6MWT (SMD=0.70,95% CI: 0.54-0.87, P<0.00001), NT-proBNP (SMD=-1.95,95% CI: -2.5 2 to 1.38 (P<0.0001), with statistically significant differences. Conclusion: Conventional western medicine combined with Qiliqiangxin capsule can significantly improve the clinical efficacy of heart failure, improve LVEF, LVEDD, SV, and NT-proBNP index, and improve exercise tolerance. It is worth using for reference in the treatment.