Multi-mode process monitoring based on a novel weighted local standardization strategy and support vector data description

There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.

GIS Analysis of Spatial Distribution of Crop Incidence

Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.

Estimating liver weight of adults by body weight and gender

AIM： To estimate the standard liver weight for assessing adequacies of graft size in live donor liver transplantation and remnant liver in major hepatectomy for cancer. METHODS： In this study, anthropometric data of body weight and body height were tested for a correlation with liver weight in 159 live liver donors who underwent donor right hepatectomy including the middle hepatic vein. Liver weights were calculated from the right lobe graft weight obtained at the back table, divided by the proportion of the right lobe on the computed tomography. RESULTS： The subjects, all Chinese, had a mean age of 35.8 ± 10.5 years, and a female to male ratio of 118：41. The mean volume of the right lobe was 710.14 ±131.46 mL and occupied 64.55%±4.47% of the whole liver on computed tomography. Right lobe weighed 598.90±117.39 g and the estimated liver weight was 927.54 ± 168.78 g. When body weight and body height were subjected to multiple stepwise linear regression analysis, body height was found to be insignificant. Females of the same body weight had a slightly lower liver weight. A formula based on body weight and gender was derived： Estimated standard liver weight （g）=218＋BW （kg）× 12.3＋gender×51 （R^2 = 0.48） （female=0, male= 1）. Based on the anthropometric data of these 159 subjects, liver weights were calculated using previously published formulae derived from studies on Caucasian, .lapanese, Korean, and Chinese. All formulae overestimated liver weights compared to this formula. The Japanese formula overestimated the estimated standard liver weight （ESLW） for adults less than 60 kg.CONCLUSION： A formula applicable to Chinese males and females is available. A formula for individual races appears necessary.

APPLICATION OF GEOGRAPHICAL PARAMETER DATABASE TO ESTABLISHMENT OF UNIT POPULATION DATABASE

Now GIS is turning into a good tool in handling geographical, economical, and population data, so we can obtain more and more information from these data. On the other hand, in some cases, for a calamity, such as hurricane, earthquake, flood, drought etc., or a decision-making, such as setting up a broadcasting transmitter, building a chemical plant etc., we have to evaluate the total population in the region influenced by a calamity or a project. In this paper, a method is put forward to evaluate the population in such special region. Through exploring the correlation of geographical parameters and the distribution of people in the same region by means of quantitative analysis and qualitative analysis, unit population database (1km× 1km) is established. In this way, estimating the number of people in a special region is capable by adding up the population in every grid involved in this region boundary. The geographical parameters are obtained from topographic database and DEM database on the scale of 1: 250 000. The fundamental geographical parameter database covering county administrative boundaries and 1km × 1km grid is set up and the population database at county level is set up as well. Both geographical parameter database and unit population database are able to oiler sufficient conditions for quantitative analysis. They will have important role in the research fields of data mining (DM), Decision-making Support Systems (DSS), and regional sustainable development.

Unbiased Estimation Formula of Unit Weight Standard Deviation in Regularization Solution

Regularization method is an effective method for solving ill\|posed equation. In this paper the unbiased estimation formula of unit weight standard deviation in the regularization solution is derived and the formula is verified with numerical case of 1 000 sample data by use of the typical ill\|posed equation, i.e. the Fredholm integration equation of the first kind.

Standard liver weight model in adult deceased donors with fatty liver: A prospective cohort study

BACKGROUND Standard liver weight(SLW)is frequently used in deceased donor liver transplantation to avoid size mismatches with the recipient.However,some deceased donors(DDs)have fatty liver(FL).A few studies have reported that FL could impact liver size.To the best of our knowledge,there are no relevant SLW models for predicting liver size.AIM To demonstrate the relationship between FL and total liver weight(TLW)in detail and present a related SLW formula.METHODS We prospectively enrolled 212 adult DDs from West China Hospital of Sichuan University from June 2019 to February 2021,recorded their basic information,such as sex,age,body height(BH)and body weight(BW),and performed abdominal ultrasound(US)and pathological biopsy(PB).The chi-square test and kappa consistency score were used to assess the consistency in terms of FL diagnosed by US relative to PB.Simple linear regression analysis was used to explore the variables related to TLW.Multiple linear regression analysis was used to formulate SLW models,and the root mean standard error and interclass correlation coefficient were used to test the fitting efficiency and accuracy of the model,respectively.Furthermore,the optimal formula was compared with previous formulas.RESULTS Approximately 28.8%of DDs had FL.US had a high diagnostic ability(sensitivity and specificity were 86.2%and 92.9%,respectively;kappa value was 0.70,P<0.001)for livers with more than a 5%fatty change.Simple linear regression analysis showed that sex(R2,0.226;P<0.001),BH(R2,0.241;P<0.001),BW(R2,0.441;P<0.001),BMI(R2,0.224;P<0.001),BSA(R2,0.454;P<0.001)and FL(R2,0.130;P<0.001)significantly impacted TLW.In addition,multiple linear regression analysis showed that there was no significant difference in liver weight between the DDs with no steatosis and those with steatosis within 5%.Furthermore,in the context of hepatic steatosis,TLW increased positively(nonlinear);compared with the TLW of the non-FL group,the TLW of the groups with hepatic steatosis within 5%,between 5%and 20%and more than 20%increased by 0 g,90 g,and 340 g,respectively.A novel formula,namely,-348.6+(110.7 x Sex[0=Female,1=Male])+958.0 x BSA+(179.8 x FLUS[0=No,1=Yes]),where FL was diagnosed by US,was more convenient and accurate than any other formula for predicting SLW.CONCLUSION FL is positively correlated with TLW.The novel formula deduced using sex,BSA and FLUS is the optimal formula for predicting SLW in adult DDs.

Association of ratios of visceral fat area/subcutaneous fat area and muscle area/standard body weight at T12 CT level with the prognosis of acute respiratory distress syndrome

Background:It is well-known that body composition metrics can influence the prognosis of various diseases.This study investigated how body composition metrics predict acute respiratory distress syndrome(ARDS)prognosis,focusing on the ratio of visceral fat area(VFA)to subcutaneous fat area(SFA),SFA to standard body weight(SBW),VFA to SBW,and muscle area(MA)to SBW.These metrics were assessed at the level of the twelfth thoracic vertebra(T12 computed tomography[CT]level)to determine their correlation with the outcomes of ARDS.The goal was to utilize these findings to refine and personalize treatment strategies for ARDS.Methods:Patients with ARDS admitted to the intensive care units(ICUs)of three hospitals from January 2016 to July 2023 were enrolled in this study.Within 24 hours of ARDS onset,we obtained chest CT scans to mea-sure subcutaneous fat,visceral fat,and muscle area at the T12 level.We then compared these ratios between survivors and non-survivors.Logistic regression was employed to identify prognostic risk factors.Receiver oper-ating characteristic(ROC)curve analysis was utilized to determine the optimal cutofffor predictors of in-hospital mortality.Based on this cutoff,patients with ARDS were stratified.To reduce confounding factors,1:1 propensity score matching(PSM)was applied.We conducted analyses of clinical feature and prognostic differences pre-and post-PSM between the stratified groups.Additionally,Kaplan-Meier survival curves were generated to compare the survival outcomes of these groups.Results:Of 258 patients with ARDS,150 survived and 108 did not.Non-survivors had a higher VFA/SFA ra-tio(P<0.001)and lower SFA/SBW and MA/SBW ratios(both P<0.001).Key risk factors were high VFA/SFA ratio(OR=2.081;P=0.008),age,acute physiology and chronic health evaluation(APACHE)II score,and lac-tate levels,while MA/SBW and albumin were protective.Patients with a VFA/SFA ratio≥0.73 were associated with increased mortality,while those with an MA/SBW ratio>1.55 cm^(2)/kg had lower mortality,both pre-and post-PSM(P=0.001 and P<0.001,respectively).Among 170 patients with pulmonary-origin ARDS,87 survived and 83 did not.The non-survivor group showed a higher VFA/SFA ratio(P<0.001)and lower SFA/SBW and MA/SBW(P=0.003,P<0.001,respectively).Similar risk and protective factors were observed in this cohort.For VFA/SFA,a value above the cutoffof 1.01 predicted higher mortality,while an MA/SBW value below the cutoffof 1.48 cm2/kg was associated with increased mortality(both P<0.001 pre-/post-PSM).Conclusions:Among all patients with ARDS,the VFA to SFA ratio,MA to SBW ratio at the T12 level,age,APACHE II score,and lactate levels emerged as independent risk factors for mortality.