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.

Quantum correlations and entanglement in coupled optomechanical resonators with photon hopping via Gaussian interferometric power analysis

Quantum correlations that surpass entanglement are of great importance in the realms of quantum information processing and quantum computation.Essentially,for quantum systems prepared in pure states,it is difficult to differentiate between quantum entanglement and quantum correlation.Nonetheless,this indistinguishability is no longer holds for mixed states.To contribute to a better understanding of this differentiation,we have explored a simple model for both generating and measuring these quantum correlations.Our study concerns two macroscopic mechanical resonators placed in separate Fabry–Pérot cavities,coupled through the photon hopping process.this system offers a comprehensively way to investigate and quantify quantum correlations beyond entanglement between these mechanical modes.The key ingredient in analyzing quantum correlation in this system is the global covariance matrix.It forms the basis for computing two essential metrics:the logarithmic negativity(E_(N)^(m))and the Gaussian interferometric power(P_(G)^(m)).These metrics provide the tools to measure the degree of quantum entanglement and quantum correlations,respectively.Our study reveals that the Gaussian interferometric power(P_(G)^(m))proves to be a more suitable metric for characterizing quantum correlations among the mechanical modes in an optomechanical quantum system,particularly in scenarios featuring resilient photon hopping.

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.

Correlation Analysis Between Changes of D-Dimer Level and Rheumatoid Arthritis Complicated with Interstitial Lung Disease

Objective:To explore the correlation between the change of D-dimer level and rheumatoid arthritis complicated with interstitial lung disease.Methods:From January 2022 to February 2024,20 rheumatoid arthritis patients complicated with interstitial lung disease(interstitial lung disease group),20 rheumatoid arthritis patients without interstitial lung disease(without interstitial lung disease group),and 20 healthy people(control group)in Xijing Hospital were selected for this study.The fasting venous blood of the three groups of subjects was collected and their D-dimer,C-reactive protein(CRP),rheumatoid factor(RF),and erythrocyte sedimentation rate(ESR)were detected.Subsequently,the correlation between each index and rheumatoid arthritis complicated with interstitial lung disease was analyzed.Results:The D-dimer level of the interstitial lung disease group was significantly higher than the other two groups(P<0.05).The D-dimer level of the group without interstitial lung disease was significantly higher than the control group(P<0.05).CRP levels in the interstitial lung disease group and the group without interstitial lung disease were significantly higher than those of the control group(P<0.05).The ESR and RF levels of the interstitial lung disease group were significantly higher than the other two groups(P<0.05).The levels of ESR and RF levels of the group without interstitial lung disease were significantly higher than the control group(P<0.05).Conclusion:D-dimer levels of rheumatoid arthritis patients are higher than those of healthy individuals,and those complicated with interstitial lung disease present even higher levels.This finding shows that there is a correlation between D-dimer levels and rheumatoid arthritis with interstitial lung disease,which may facilitate the evaluation and diagnosis of this disease.

A novel diurnal and seasonal variation analysis of BTEX in Bengaluru urban area

In the urban atmosphere of Bengaluru, various volatile organic compounds(VOCs), particularly Benzene,Toluene, Ethylbenzene, and Xylene(BTEX), have shown an increasing trend in concentration. The present research was conducted during summer and monsoon seasons, focusing on Kadubeesanahalli, a high-traffic area within the Bengaluru Metropolitan City. Hourly sample data was collected using a BTEX analyzer(Model GC955-600) and subsequently transformed into daily, monthly, and seasonal values. The study revealed distinct patterns in benzene concentrations. Benzene levels were lowest during the early morning hours, specifically from 1:00 a.m.to 7:00 a.m.. Concentrations then increased from 7:00 a.m. to 9:00 a.m. and again from 4:00 p.m. to 11:00 p.m.,corresponding to the morning and evening peak traffic hours. However, between 10:00 a.m. and 4:00 p.m., the concentration decreased due to reduced traffic levels. These diurnal variations in benzene concentration are influenced by meteorological parameters. Comparing the two seasons, higher concentrations of Benzene, EthylBenzene, and MP-xylene were observed during the summer season. This increase is attributed to the elevated temperatures during summer, which promote the vaporization of BTEX compounds. Conversely, lower BTEX concentrations were recorded during the monsoon season due to the wet deposition process. The observed positive correlation(r > 0.5) among BTEX parameters strongly suggests a common source, most likely originating from vehicular emissions.

Correlation and variability analysis of yield and quality related traits in different peanut varieties across various ecological zones of China

Peanut cultivation in China spans various ecological zones, each with unique environmental conditions. Identifying suitable peanut varieties for these regions has been challenging due to significant phenotypic variations observed across environments. This study, based on a comprehensive analysis of 256 peanut varieties, selected nine representative varieties(Huayu23, Yuanza9102, Silihong, Wanhua2, Zhonghua6, Zhonghua16, Zhonghua21,Zhonghua215, Zhonghua24) for cultivation in five distinct ecological zones including Chengdu, Hefei, Nanjing,Shijiazhuang, and Wuhan. The yield and quality related phenotypic traits of these varieties were thoroughly assessed, revealing a complex interplay between genetic and environmental factors. Principal component analysis(PCA) effectively distinguished varieties based on yield and quality traits. Strong correlations were observed between specific traits, such as seed size and quality components. The G × E interaction was evident, as some varieties consistently performed better in certain environments. Varieties with lower coefficient of variation(CV)values exhibited stable trait expression, making them reliable choices for broad cultivation. In contrast, varieties with higher CV values displayed greater sensitivity to environmental fluctuations, potentially due to specific genetic factors. Two high oleic acid varieties, Zhonghua24 and Zhonghua215, demonstrated remarkable stability in oleic acid content across diverse environments, suggesting the presence of genetic mechanisms that buffer against environmental variations. Overall, this study underscores the importance of selecting peanut varieties based on their adaptability and performance in specific ecological zones. These findings provide valuable insights for peanut breeders and farmers, facilitating informed decisions for improved crop production and quality.

Analysis of the Employment Situation of Non Private Enterprises in Various Regions of China

In the past 30 years, Chinese enterprises have been a hot topic of discussion and concern among the general public in terms of economic and social status, ownership structure, business mechanism, and management level. Solving the problem of employment for the people is an important prerequisite for their peaceful living and work, as well as a prerequisite and foundation for building a harmonious society. The employment situation of private enterprises has always been of great concern to the outside world, and these two major jobs have always occupied an important position in the employment field of China that cannot be ignored. With the establishment of the market economy system, individual and private enterprises have become important components of the socialist economy, making significant contributions to economic development and social progress. The rapid development of China’s economy, on the one hand, is the embodiment of the superiority of China’s socialist market economic system, and on the other hand, it is the role of the tertiary industry and private enterprises in promoting the national economy. Since the 1990s, China’s private enterprises have become a new economic growth point for local and even national countries, and are one of the important ways to arrange employment and achieve social stability. This paper studies the employment of private enterprises and individuals from the perspective of statistics, extracts relevant data from China statistical Yearbook, uses the relevant knowledge of statistics to process the data, obtains the conclusion and puts forward relevant constructive suggestions.

Analysis of Osteoporosis Risk Factors in 148 Retired Employees Based on Physical Examination Results

Objective:To investigate and thoroughly understand the physical examination results of retired employees from a certain unit in Beijing,analyze their bone mineral density(BMD),and identify risk factors that may indicate osteoporosis.This provides a reference for the individualized prevention,identification,and control of osteoporosis among retired employees.Methods:The bone mineral density and potential factors of 148 retired employees from a unit in 2023 were analyzed and categorized into osteoporosis and non-osteoporosis groups.Key factors from the physical examinations of the two groups were compared.Spearman’s correlation analysis was used to determine the correlation between key factors and osteoporosis.Significant key factors were included in a regression analysis.A multivariate binary logistics regression was employed to identify risk factors indicative of osteoporosis.Results:Correlation analysis revealed that gender,age,and ECG ST-segment length were significantly associated with osteoporosis.Regression analysis showed that for each additional year of age,the likelihood of developing osteoporosis increased by 1.058 times;females were 2.865 times more likely to develop osteoporosis compared to males;the longer the ECG ST-segment,the higher the likelihood of osteoporosis.Conclusion:Gender,age,and ECG ST-segment length are significantly associated with osteoporosis.These indicators can provide reference points for early identification,early intervention,and reducing the incidence of osteoporosis in clinical settings.

Correlation analysis between fault frequency and service time of underground fluid instruments

In this paper, we make a statistical analysis of the fault information of the underground fluid instruments of 12 models in China from January 2021 to May 2022 based on the Pearson correlation coefficient, and compare the fault statistics of the meteorological three-element instruments of 3 models during the study period. The results show that:(1) The numbers of faults of the underground fluid instruments of 12models with different service times are basically positively correlated with the numbers of the corresponding instruments, with good consistency. Moreover, the automatic observation instruments(8models) with more than 30 units are significantly correlated at a 0.05 significance level(95% confidence level). Even at a 0.01 significance level(99% confidence level), there are 7 models(7/8) with significant correlation.(2) The positive and negative correlations between the monthly average number of faults and the corresponding service times of the underground fluid instruments of 12 models with different service times are random, and there are 9 models(75%) with no significant correlation at a 0.05 significance level(95% confidence level), while 12 models(100%) with no significant correlation at a 0.01significance level(99% confidence level).(3) The monthly average numbers of faults of the underground fluid instruments of 12 models are basically 0.02-0.05 times/(unit·month), and the overall fault frequency is low.(4) The fault statistics results of the meteorological three-element instruments of 3 models are consistent with the characteristics of the underground fluid instruments of 12 models. In general,there is no significant correlation between the fault frequency and the service time of underground fluid instruments.(5) The results of this paper demonstrate that the service time of underground fluid instruments cannot be taken as the main reason for whether to update the instruments. Similarly, the fault frequency of the instruments cannot be taken as the main reason for the service life of the instruments in the process of formulating the service life standards of underground fluid instruments.

Heritability of Main Yield Traits in Red-seed Watermelon and Their Correlation Analysis

[Objectives]This study was conducted to provide a reliable theoretical basis for the correct formulation of breeding programs for red-seed watermelon and the effective breeding of hybrid offspring.[Methods]With local varieties and inbred lines of red-seed watermelon as test materials,the generalized heritability of fruit number per plant,single-fruit weight,single-fruit seed number,single-fruit seed weight,seed kernel weight,1000-seed weight,kernel-producing ratio,seed production ratio and seed volume were estimated by variance analysis;and the heritability,genetic variation coefficients,and correlation of the nine yield traits in 43 red-seed watermelon varieties were studied.[Results]The generalized heritability of fruit number per plant,single-fruit weight,single-fruit seed number,single-fruit seed weight,seed kernel weight,1000-seed weight,kernel-producing ratio,seed production ratio and seed volume were 12.86%,80.14%,75.96%,74.39%,48.01%,17.12%,24.97%,18.60%,and 37.07%,respectively.The heritability of single-fruit weight,single-fruit seed number and single-fruit seed weight was higher,and early-generation individual selection could achieve a better effect on them;and 1000-seed weight and kernel-producing ratio had a higher coefficient of genetic variation,indicating a high selection potential.[Conclusions]Indirect selection could be achieved for traits such as the single-fruit seed number,single-fruit seed weight,seed kernel weight,and seed volume by selecting the single-fruit weight.In the process of red-seed watermelon breeding,traits with high heritability can be selected in early generations of hybrids,thus playing the role of early-generation orientation.

Correlation analysis of mental health conditions and personality of patients with alcohol addiction

BACKGROUND Alcohol addiction,or alcohol dependence,refers to a psychological state of strong craving for alcohol caused by drinking when both the drinking times and alcohol consumption reach a certain level.Alcohol addiction can cause irreversible damage,leading to mental illness or mental disorders,negative changes in their original personality,and a tendency to safety incidents such as committing suicide or violent attacks on others.Significant attention needs to be given to the mental health of alcohol addicts,which could reflect their abnormal personality traits.However,only a few papers on this issue have been reported in China.AIM To investigate the correlation between mental health and personality in patients with alcohol addiction.METHODS In this single-center observational study,we selected 80 patients with alcohol addiction as the research subjects,according to the criteria of the K10 scale to evaluate the mental health of patients with alcohol addiction,and divided these patients into four groups based on the evaluation results:Good,average,relatively poor and bad.And then analyzed the correlation between mental health conditions and personality characteristics from these four groups of patients.RESULTS The average score of the K10 scale(Kessler 10 Simple Psychological Status Assessment Scale)in 80 patients with alcohol addiction was 25.45 points,the median score was 25 points,the highest score was 50 points,and the lowest score was 11 points.Pearson's analysis showed that the K10 score was positively correlated with the scores of these two subscales,such as the P-subscale and the N-subscale(P<0.05).In contrast,the K10 score had no significant correlation with the scores from the E-subscale and the L-subscale(P>0.05).CONCLUSION The mental health conditions of patients with alcohol addiction are positively correlated with their personality characteristics.

Correlation analysis of serum thyroglobulin,thyroid-stimulating hormone levels,and thyroid-cancer risk in thyroid nodule surgery

BACKGROUND Thyroglobulin(Tg)is one of the markers of thyroid cancer,and its concentration may be elevated in patients with malignant thyroid tumors.Thyroid-stimulating hormone(TSH)is secreted by the pituitary gland,which has a significant impact on thyroid gland function.Excessively high or low TSH levels may be associated with an increased risk of thyroid cancer.Thus,in-depth studies on the association of serum Tg and TSH levels with thyroid cancer risk in patients with thyroid nodules are warranted.This can help determine whether Tg and TSH levels can predict the degree of malignancy of thyroid nodules,which can in turn guide doctors in making accurate diagnoses and treatment decisions.Furthermore,such studies can provide more accurate diagnostic methods for thyroid nodules and help patients become aware of the presence of thyroid cancer as early as possible,thereby improving the success rate of treatment and prognosis.AIM To investigate the association of serum Tg and TSH levels with the risk of thyroid cancer in patients undergoing thyroid nodule surgery.METHODS The clinical data and laboratory examination results of 130 patients who underwent thyroid nodule surgery were retrospectively analyzed.Furthermore,their preoperative serum Tg and TSH levels were recorded.Histopathological examination conducted during follow-up revealed the presence of thyroid cancer.Correlation analysis were used to analyze the association of Tg and TSH levels with the risk of thyroid cancer.RESULTS Of the 130 patients,60 were diagnosed with thyroid cancer.Statistical analysis revealed a significant positive correlation between serum Tg levels and the risk of thyroid cancer(P<0.05).This suggests that high serum Tg levels are associated with an increased risk of thyroid cancer.However,no significant correlation was observed between serum TSH levels and the risk of thyroid cancer(P>0.05).CONCLUSION In patients who underwent thyroid nodule surgery,serum Tg levels exhibited a significant correlation with the risk of thyroid cancer but serum TSH levels did not.These findings suggest that serum Tg can serve as an important biomarker for assessing the risk of thyroid cancer in these patients.

Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.

Quantitative traits correlative analysis and growth comparison among different populations of bay scallop,Argopecten irradians

The shell traits and weight traits are measured in cultured populations of bay scallop, Argopecten irradians. The results of regression analysis show that the regression relationships for all the traits are significant (P<0.01). The correlative coefficients between body weight, as well as tissue weight with shell length, shell height and shell width are significant (P<0.05). But the correlative coefficients between the anterior and posterior auricle length with body weight as well as tissue weight are not significant (P>0.05). The multiple regression equation is obtained to estimate live body weight and tissue weight. The above traits except anterior and posterior auricle length are used for the growth and production comparison among three cultured populations, Duncan's new multiple range procedure analysis shows that all the traits in the Lingshuiqiao (LSQ) population are much more significant than those of the other two populations (P<0.01), and there is no significant difference between the Qipanmo (QPM) and Dalijia (DLJ) populations in all traits (P>0.05). The results indicate that the LSQ population has a higher growth rate and is expected to be more productive than the other two populations.

Probabilistic analysis of tunnel displacements based on correlative recognition of rock mass parameters

Displacement is vital in the evaluations of tunnel excavation processes,as well as in determining the postexcavation stability of surrounding rock masses.The prediction of tunnel displacement is a complex problem because of the uncertainties of rock mass properties.Meanwhile,the variation and the correlation relationship of geotechnical material properties have been gradually recognized by researchers in recent years.In this paper,a novel probabilistic method is proposed to estimate the uncertainties of rock mass properties and tunnel displacement,which integrated multivariate distribution function and a relevance vector machine(RVM).The multivariate distribution function is used to establish the probability model of related random variables.RVM is coupled with the numerical simulation methods to construct the nonlinear relationship between tunnel displacements and rock mass parameters,which avoided a large number of numerical simulations.Also,the residual rock mass parameters are taken into account to reflect the brittleness of deeply buried rock mass.Then,based on the proposed method,the uncertainty of displacement in a deep tunnel of CJPL-II laboratory are analyzed and compared with the in-situ measurements.It is found that the predicted tunnel displacements by the RVM model closely match with the measured ones.The correlations of parameters have significant impacts on the uncertainty results.The uncertainty of tunnel displacement decreases while the reliability of the tunnel increases with the increases of the negative correlations among rock mass parameters.When compared to the deterministic method,the proposed approach is more rational and scientific,and also conformed to rock engineering practices.

Correlative Analysis between Contents of Nutrients and Secondary Substances in Damaged Pinus massoniana Needles and Population Parameters of Dendrolimus kikuchii(Lepidoptera:Lasiocampidae)

In order to explore the effects of chemical substances changes in damaged masson pine （Pinus massoniana） needles on population dynamics of Dendroli- mus kikuchii, D. kikuchii larvae were reat~ with P. massoniana needles with different damage degrees （mild, moderate and severe）, and its population parame- ters and contents of nutrients and secondary substances in damaged P. massoniana needles were measured, and the integrated correlation coefficient was adopted for data analysis. The results showed that with the damage degree aggravating, flavones in needles increased accordingly, while contents of soluble sugars, polysaeeha- rides and proteins decreased. The average developmental duration and mortality of D. kikuchii larvae increased with the damage degree increasing. No significant correlation was found between the changes in contents of tannins or total phenols and the developmental duration or mortality of each instar larvae. There were signif- icant direct and integrated correlations between contents of nutrients and secondary substances of P. massoniana needles and the developmental duration or mortality of each instar larvae except the 6＇h instar larvae. With the damage degree increasing, all parameters of D. kikuchii population including body weight of the 7~ instar larvae, average feeding capacity of larvae, pupal weight, pupation rate, female ratio and fecundity decreased. No significant correlation was found between the changes in contents of tannins or total phenols and population parameters of D. kikuchii larvae. The results suggest that the contents of nutrients and secondary sub- stances in P. ,mssoniana needles dramatically influenced the population parameters of D. kikuchii, and the importance from high to low successively was soluble sugars 〉 proteins 〉 polysaccharides 〉 flavones. Contents of tannins and total phenols seemed to have little influence.

Analysis of Short-Shoot Fuji Apple Tree Structure and Correlative Factors

In order to clarify the correlation between short-shoot Fuji apple tree structure and different factors under different trimming and pruning modes,we investigate the trunk taperingness of free-spindle short-shoot Fuji and slender-spindle short-shoot Fuji,respectively,as well as the total thickness,average thickness,total length and average length of small main branches in the standard demonstration apple garden in Xingtang County of Hebei Province. By SPSS analysis,we study the correlation between trunk taperingness of trees with different shapes and the growth indices of their small main branches. The results show that the trunk taperingness of free-spindle short-shoot Fuji apple is negatively correlated with the total thickness,average thickness,total length and average length of small main branches,but the correlation is not significant; the trunk taperingness of slender-spindle short-shoot Fuji apple is negatively correlated with the total thickness but positively correlated with other factors,and the correlation with average length reaches a significant level. The results of this study can provide a scientific basis for guiding the high-density dwarf rootstock short-shoot Fuji apple tree trimming technology.

DIC Based Strain and Damage Analysis of Large Scale Steel to Composite Adhesive Joints Subjected to Tension and Compression Loading

This paper reports an experimental study of the mechanical response to tensile and compressive force of large scale steel to composite joints adhesively bonded with a thin layer of vinylester resin.In one specimen,the length of the reinforcing fibres in contact with the steel substrate has been reduced by saw cutting at both ends of the joint.This damaged specimen and four intact specimens were subjected to quasi-static tensile testing;six specimens were used for compression testing.The strain distribution at the composite surface and at the steel to hardwood connection of the specimen was monitored by digital image correlation(DIC).DIC allowed identifying the onset of damage in the tensile tested joints near the interface of the composite layer and the steel-hardwood connection.Both tensile and compression tested specimens failed due to significant peel strain concentration at the composite near the connection of steel and hardwood.The average strength of a specimen tested in compression was about 66%higher than the average strength of a specimen tested in tension.The strain concentration zone in the damaged specimen was away from the introduced saw cuts.As a result the damaged and intact tensile specimens showed the same failure strength and stiffness.All specimens failed by adhesive failure between the composite-hardwood interface.

Levels of serum homocysteine in depressive patients Self-correlation factor analysis and comparison with healthy subjects

BACKGROUND： Data indicate that the levels of serum homocysteine in depressive patients are higher than those in normal subjects. OBJECTIVE： To investigate the levels of serum homocysteine in patients with major depressive disorder, to determine whether serum homocysteine levels differ with sex, family history, or drug treatment, and to compare depressive patients with normal subjects. DESIGN： Non-randomized concurrent control trial. SETTING： Mental Heath Center of Shandong Province. PARTICIPANTS： Forty in-patients （23 males and 17 females, 18-63 years old） with major depressive disorder were selected from the Mental Health Center of Shandong Province from January to October 2006. All selected patients met the depressive diagnostic standard of Chinese Classification of Mental Disorder （3^rd Edition, CCMD-3）, and total scores evaluated by the 17-item Hamilton Rating Scale for Depression （HRSD） were ≥ 20. Meanwhile, 36 healthy subjects （20 males and 16 females, 18-60 years old） were enrolled as controls; their total 17-item HRSD scores were ≤ 7. All selected subjects provided consent, and the study was approved by the local ethics committee. METHODS： Fasting venous blood （3 mL） was drawn in both groups at 8：00 in the morning. The levels of serum homocysteine were determined by a fluorescence polarization immunoassay （FPIA）. The 17-item HRSD was also compiled from the patients when entering groups. The higher the scores were, the more severe the depression was. Enumeration data for both groups were compared by Chi-square test, measurement data were compared by t-test, and correlations were detected using Pearson and Spearman correlation analysis. MAIN OUTCOME MEASURES： ① Levels of serum homocysteine; ② incidence of hyperhomocysteinemia （HHcy）; ③ correlation between HRSD17 scores and levels of serum homocysteine in depressive patients. RESULTS： Forty depressive patients and 36 control subjects were included in the final analysis without any loss of participants. ① Levels of serum homocysteine and HHcy detection rate： the levels of serum homocysteine in the depressive patients were significantly higher than those in the control group （t = 4.377, P=0.000）. Hhcy detection rates were 42% （17/40） and 10% （4/36） in depressive group and control group, respectively. There was a significant difference between two groups （x^2 = 10.912, P = 0.001）. In the depressive group, there were no differences in serum homocysteine levels between males and females, before and after treatment, or between patients with positive or negative family histories of depression （t = 0.217-0.520, P 〉 0.05）. ② Correlation analysis： the HRSD17 scores in the depressive group were positively correlated with levels of serum homocysteine （r = 0.724, P = 0.000）. CONCLUSION： ① The increase in serum homocysteine levels may play an important role in the pathogenic mechanism of depressive disorder. ② The higher the levels of serum homocysteine are, the more severe the depressive disorder is. ③ There are no significant differences in serum homocysteine levels between patients of different sex or family history, or before and after drug treatment, among depressive patients.