Tongue image feature correlation analysis in benign lung nodules and lung cancer

Objective To analyze the differences in the correlation of tongue image indicators among patients with benign lung nodules and lung cancer.Methods From July 1;2020 to March 31;2022;clinical information of lung cancer patients and benign lung nodules patients was collected at the Oncology Department of Longhua Hos-pital Affiliated to Shanghai University of Traditional Chinese Medicine and the Physical Ex-amination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chi-nese Medicine;respectively.We obtained tongue images from patients with benign lung nod-ules and lung cancer using the TFDA-1 digital tongue diagnosis instrument;and analyzed these images with the TDAS V2.0 software.The extracted indicators included color space pa-rameters in the Lab system for both the tongue body(TB)and tongue coating(TC)(TB/TC-L;TB/TC-a;and TB/TC-b);textural parameters[TB/TC-contrast(CON);TB/TC-angular second moment(ASM);TB/TC-entropy(ENT);and TB/TC-MEAN];as well as TC parameters(perAll and perPart).The bivariate correlation of TB and TC features was analyzed using Pearson’s or Spearman’s correlation analysis;and the overall correlation was analyzed using canonical correlation analysis(CCA).Results Samples from 307 patients with benign lung nodules and 276 lung cancer patients were included after excluding outliers and extreme values.Simple correlation analysis indi-cated that the correlation of TB-L with TC-L;TB-b with TC-b;and TB-b with perAll in lung cancer group was higher than that in benign nodules group.Moreover;the correlation of TB-a with TC-a;TB-a with perAll;and the texture parameters of the TB(TB-CON;TB-ASM;TB-ENT;and TB-MEAN)with the texture parameters of the TC(TC-CON;TC-ASM;TC-ENT;and TC-MEAN)in benign nodules group was higher than lung cancer group.CCA further demon-strated a strong correlation between the TB and TC parameters in lung cancer group;with the first and second pairs of typical variables in benign nodules and lung cancer groups indicat-ing correlation coefficients of 0.918 and 0.817(P<0.05);and 0.940 and 0.822(P<0.05);re-spectively.Conclusion Benign lung nodules and lung cancer patients exhibited differences in correla-tion in the L;a;and b values of the TB and TC;as well as the perAll value of the TC;and the texture parameters(TB/TC-CON;TB/TC-ASM;TB/TC-ENT;and TB/TC-MEAN)between the TB and TC.Additionally;there were differences in the overall correlation of the TB and TC be-tween the two groups.Objective tongue diagnosis indicators can effectively assist in the diag-nosis of benign lung nodules and lung cancer;thereby providing a scientific basis for the ear-ly detection;diagnosis;and treatment of lung cancer.

过年就是过五关

春运关 对于背井离乡的人来说，春运无疑是回家过年的首道关。尽管每年相关部门都要在春运上下功夫，但春运的难题却从没真正解决过。一票难求啊!大家使出浑身解数，终于把票挤到手了，可是上车又是一大考验。尽管使出吃奶力气挤上了车，可能在密不透风的车厢里挨到家乡的车站，才是对你意志的真正考验。

Facial expression recognition based on fuzzy-LDA/CCA

A novel fuzzy linear discriminant analysis method by the canonical correlation analysis （fuzzy-LDA/CCA）is presented and applied to the facial expression recognition. The fuzzy method is used to evaluate the degree of the class membership to which each training sample belongs. CCA is then used to establish the relationship between each facial image and the corresponding class membership vector, and the class membership vector of a test image is estimated using this relationship. Moreover, the fuzzy-LDA/CCA method is also generalized to deal with nonlinear discriminant analysis problems via kernel method. The performance of the proposed method is demonstrated using real data.

Principal Component-Discrimination Model and Its Application

Having researched for many years, seismologists in China presented about 80 earthquake prediction factors which reflected omen information of earthquake. How to concentrate the information that the 80 earthquake prediction factors have and how to choose the main factors to predict earthquakes precisely have become one of the topics in seismology. The model of principal component-discrimination consists of principal component analysis, correlation analysis, weighted method of principal factor coefficients and Mahalanobis distance discrimination analysis. This model combines the method of maximization earthquake prediction factor information with the weighted method of principal factor coefficients and correlation analysis to choose earthquake prediction variables, applying Mahalanobis distance discrimination to establishing earthquake prediction discrimination model. This model was applied to analyzing the earthquake data of Northern China area and obtained good prediction results.

VARIATION FEATURES OF SOMALI CROSS-EQUATORIAL FLOW AND ITS IMPACT ON THE LOCATION OF THE SUBTROPICAL HIGH RIDGE FROM JULY TO SEPTEMBER

The variation features of the cross-equatorial flow and its impact on the ridge position of the subtropical high have been analyzed in this paper. It is shown as follows. (1) The intensity of the Somali cross-equatorial flow is increasing in winter and summer in the past 44 years and the airflow of Northern Hemisphere exchanges more and more intensively with that of Southern Hemisphere. (2) The Somali cross-equatorial flow in May has the most impact on the ridge position of the subtropical high in the typhoon season, presenting a positive correlation. (3) The diagnosis is consistent with the real situation in 2005.

Identification of Telecom Operators' Core Distribution Channels Based on Strategic Value Evaluation System

The strategic value evaluation ofphysical channels is the main purpose of thispaper.To interpret this value,we refine finance,location and competition dimensions.Atotal of 166 social high-star channels are selected as empirical samples.Practice showsthat all second-layer indicators can be quantified by information system or artificial collection.The weight of three first-layer indicatorscan be defined by correlation analysis.The valuecomprehensive ranking of the channels is clearbased on the first-layer and second-layer indicators.In the sample group in this study,theweight of location value is higher.The resultson channels' strategic value research may provide further insights on business value,servicevalue and other related fields.

Temporal-spatial cross-correlation analysis of non-stationary near-surface wind speed time series

Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.

Establishment of an HPLC method for the analysis of biapenem and its impurities

An HPLC method for routine quality control of biapenem was established.A Dikma Diamonsil C_(18) column(250mm×4.6 mm,5μm) was used with diode array detection and single wavelength detection at 220 nm.The mobile phase was consisted of acetonitrile-0.1%triethylamine water(1:99,v/v).The liner range for biapenem quantification was 0.05-10.0 mg/mL(r^2= 0.999). The LOD and LOQ of impurity were 4.8 ng(S/N = 3) and 18.5 ng(S/N = 10),respectively.Intra-day RSD of main impurity and total impurity were 1.84%and 3.37%(n = 3);inter-day RSD of main impurity and total impurity were 4.84%and 7.58% (n = 9).The test solution was stable when stored at 4℃for 6 h.The impurity peaks of biapenem can be identified by chromatographic spectral correlation analysis using high-performance liquid chromatography-diode array detection data from the quality control method by calculating correlation coefficients without reference standards.Two hydrolysis degradation products with relative retention times(RRTs) of 0.528 and 0.743,two dimers with RRTs of 1.062 and 2.817 were identified in the quality control chromatogram.It provides a new way to identify impurity peaks by the routine HPLC-UV method.

Coupling analysis-based false monitoring information identification of production system in process industry

False monitoring information is a major problem in process production system and several ineffective methods have been proposed to identify false monitoring information in the production system. In this paper, a new method is proposed to identify false monitoring information based on system coupling analysis and collision detection from the perspective of data analysis. Coupling multifractal features are extracted to reflect the changes in coupling relationship by utilizing the multifractal detrended cross-correlation analysis (MF-DXA). Each monitoring variable in process production system has more than one coupled variable, which can be regarded as multi-source. To achieve low redundancy in features and uniform description of coupling relationship, the feature level information fusion is studied based on modified Mahalanobis Taguchi system (MTS). False alarms are identified when the coupling relationships among the coupled monitoring variables collide. Analysis results of coupled R?ssler and Henon datasets indicate the feasibility of this method for selecting the effective coupling feature and uniform description of coupling relationship. The compressor system case of Coal Chemical Ltd. Group is studied and false monitoring information is identified.

SPECIES-AREA RELATIONSHIP FOR POWER-LAW SPECIES ABUNDANCE DISTRIBUTION

We studied the mathematical relations between species abundance distributions （SADs） and species-area relationships （SARs） and found that a power-law SAR can be generally derived from a power-law SAD without a special assumption such as the ＂canonical hypothesis＂. In the present analysis, an SAR-exponent is obtained as a function of an SAD-exponent for a finite number of species. We also studied the inverse problem, from SARs to SADs, and found that a power-SAD can be derived from a power-SAR under the condition that the functional form of the corresponding SAD is invariant for changes in the number of species. We also discuss general relationships among lognormal SADs, the broken-stick model （exponential SADs）, linear SARs and logarithmic SARs. These results suggest the existence of a common mechanism for SADs and SARs, which could prove a useful tool for theoretical and experimental studies on biodiversity and species coexistence.