Latent profile analysis of perceived stress and influencing factors in colorectal cancer patients

Objective:To understand the latent categories of perceived stress in colorectal cancer patients and analyze the characteristics of different categories of patients.Methods:A total of 255 colorectal cancer patients receiving treatment in the gastrointestinal surgery and oncology depar tments of a ter tiary Grade A hospital in Sichuan Province,from January 2023 to June 2023,were selected as the study subjects.General information questionnaire,Chinese version of the Perceived Stress Scale(CPSS),and Comprehensive Score Table for Patient-Repor ted Outcome Measures of Economic Toxicity(COST-PROM)were used for data collection.Results:Perceived stress in colorectal cancer patients was classified into 3 latent categories:C1“Low stress-stable type”(19.2%),C2“Moderate stress-uncontrolled type”(23.9%),and C3“High stress-anxious type”(56.9%).The average score of perceived stress was(34.07±5.08).Compared with C1 type,patients with a monthly household income of≤3000 RMB were more likely to belong to the C2 and C3 types(P<0.05),and patients without a stoma were less likely to belong to C3 type(P<0.05).Compared with C2 type,male patients were more likely to belong to C3 type(P<0.05),and patients without a stoma were less likely to belong to C3 type(P<0.05).Compared with C3 type,patients with higher economic toxicity scores were more likely to be classified into C1 and C2 types(P<0.05).Conclusions:Perceived stress in colorectal cancer patients exhibits distinct categorical features.Male gender,lower income,presence of a stoma,and higher economic toxicity are associated with higher levels of perceived stress in colorectal cancer patients.

Analysis of a Type Ⅱ Snowstorm Process in the Early Spring of 2022 in Ulanqab

Based on the observation data of meteorological stations,Doppler radar observation data of Ulanqab City,and ERA-5 reanalysis data,a snowstorm process in Ulanqab City from March 17 to 18,2022 was analyzed.The results show that this was a type Ⅱ snowstorm process generated under the joint influence of upper trough and ground low inverted trough and frontal cyclone.The main period of snowfall can be divided into two time stages,and the total snowfall was more in the south and less in the north,which was consistent with that of average specific humidity field.Water vapor conditions provided by strong water vapor transport and convergence,strong upward movement shown by large vertical velocity field,and the suction action of high-and low-layer divergence and convergence were the reasons for the hourly heavy snowfall on the 18^(th).During the process,radar echoes were mainly sheet-shaped,and composite reflectivity was 15-25 dBZ in most areas.The zero speed line in the first period was positively"S"-shaped,and there was warm advection and southwest wind.On the morning of the 18^(th),after the cold front transited the city,Ulanqab City was gradually controlled by northwest wind,and the snow tended to end.

Influencing factor analysis of interception probability and classification-regression neural network based estimation

The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.

Quality of life of hospitalized patients after lung cancer operation and analysis of influencing factors

Objective:To explore the current status and influencing factors of quality of life in patients with lung cancer after surgery in a tertiary hospital in Hainan province.Methods:To investigate the influencing factors of quality of life of lung cancer patients after surgery in a tertiary hospital in Hainan province by cross‑sectional survey method.Results:The scores of insomnia,appetite loss,constipation and pain in 186 lung cancer patients after surgery in a tertiary hospital in Hainan Province were significantly higher than the reference value.Multiple linear regression analysis showed that older patients(>60 years)had lower scores in physical function domain(β=-0.193),and female patients had more appetite loss symptoms(β=0.245).Compared with other minority ethnic groups,Han ethnic group had lower scores in role function domain(β=0.179),more severe fatigue symptoms(β=-0.162),and higher general health level(β=0.166).Patients with employee medical insurance had lower scores of emotional function(β=0.194),cognitive function(β=0.281),the lowest score in social function(β=0.188),and severe pain in other parts(β=-0.227).Smokers had less cough symptoms(β=0.175)and more arm and shoulder pain symptoms(β=-0.21)than non‑smokers.Patients with secondhand smoke exposure had lower cognitive function scores(β=-0.158)and more obvious symptoms of oral ulcer(β=0.185).Patients who drank alcohol frequently(drinking frequency>1 time/day)had more severe cough symptoms(β=0.27).Patients with small number of children(0‑1)had milder cough symptoms(β=0.178).Patients who did not understand the disease had obvious symptoms of arm and shoulder pain(β=0.151).Patients with early pathological stage(stageⅠ‑Ⅱ)had more severe shortness of breath(β=-0.159)and pain(β=-0.181).The symptoms of appetite loss were more obvious in patients living in cities(β=0.192).The symptoms of peripheral neuropathy were more obvious(β=0.174).Patients who often consumed pickulated food had severe pain symptoms(β=-0.219),and pain in other parts was obvious(β=-0.149).Male patients had obvious alopecia symptoms(β=-0.306).Conclusion:Age,ethnicity,residence,type of medical insurance,number of children,pathological stage of lung cancer,smoking,second‑hand smoke exposure,alcohol consumption,and frequent consumption of pickled food were related to the quality of life of lung cancer patients in hospital after surgery.Medical staff and family members should pay attention to the emotional communication of patients during the treatment of lung cancer patients in hospital after surgery.Patients should avoid exposure to smoking,alcohol and second‑hand smoke,and reduce consumption of pickled food.

Weight Analysis of the Influencing Factors of Homestay Competitiveness in Rural Guangzhou,China

At present,Guangzhou homestay industry is facing a bottleneck.Therefore,it is particularly important to analyze the factors that influence the competitiveness of rural homestays in Guangzhou,determine the evaluation system of competitiveness,and determine the weight of each factor.Based on Porter’s diamond theory,this paper analyzes and summarizes the influencing factors of homestay competitiveness,and divides the influencing factors into 5 primary factors and 34 secondary factors.The analytic hierarchy process(AHP)was used to determine the judgment matrix to form the weight results of each factor,and the results show that product characteristics account for the largest proportion among first level factors.Secondary factors such as theme creativity,personalized brand and the overall score account for a large proportion.The research results can act as a reference for the construction of competitiveness evaluation mechanism and model of local rural quality homestays.

ASSESSMENT OF LOCAL INFLUENCE IN MULTIVARIATE ANALYSIS

A recent method for assessing the local influence is introduced by Cook(1986), in which the normal curvature of the influence graph based on the likelihood displacement is used to monitor the influence of small perturbation. Since then this method has been applied to various kind of models. However, the local influence in multivariate analysis is still an unexplored area because the influence for many statistics in multivariate analysis is not convenient to handle based on the Cook's likelihood displacement. In this paper, we suggest a method with a slight modification in Cook's approach to assess the local influence of small perturbation on a certain statistic. The local influence of the perturbation on eigenvalue and eigenvector of variance-covariance matrix in theoretical and sample version is assessed, some results for the other statistics in multivariate analysis such as generalized variance, canonical correlations are studied. Finally, two examples are analysed for illustration.

Baishideng’s Reference Citation Analysis database announces the first Journal Article Influence Index of 101 core journals and a list of high-quality academic journals in gastroenterology and hepatology

After three rounds of rigorous evaluation of core journals in gastroenterology andhepatology conducted by the Reference Citation Analysis (RCA) editorial team ofBaishideng Publishing Group (Baishideng), the RCA database of Baishidengofficially released the 2022 Journal Article Influence Index (2022 JAII) of 101 corejournals in gastroenterology and hepatology, for the first time. The list of 101 corejournals can be found at: https://www.referencecitationanalysis.com/Search-Journal. Among them, the highest 2022 JAII is 48.014 and the lowest is 3.900. Thisarticle highlights the top 20 journals, describes the calculation method for the 2022JAII, the evaluation process, and the inclusion principles for journals in the RCA.These steps are the underpinning of the RCA’s empirical journal academicevaluation service by which the digital platform addresses the needs of authors toselect reliable journals for submission, readers to select high-quality literature forreading, and editors to track their own journal citation performance. As such, theRCA core journal list will serve as a useful Find-a-Journal tool. Any interestedparty is welcome to use this journal list and recommend it to their peers.

Analysis of the Influence Factors of Grain Supply-Demand Gap in China

Based on the analysis of the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand gap. Then this paper calculates the correlation degree between the main grain varieties’ supply and demand gap and its influence factors. The results show that sown area and unit yield have the greatest impact on wheat supply and demand gap;per capita disposable income and unit yield have the greatest impact on corn supply and demand gap;per capita disposable income and agricultural mechanization level have the greatest impact on the supply and demand gap of soybean and rice. From the analysis results, we can obtain the difference between the factors affecting the grain supply and demand gap, and provide a certain theoretical basis and new ideas for the balance of grain supply and demand in China.

Baishideng’s Reference Citation Analysis database announces the first Journal Article Influence Index of 104 core journals and a list of high-quality academic journals in orthopedics

After three rounds of rigorous evaluation of core journals in orthopedics conducted by the Reference Citation Analysis(RCA)editorial team of Baishideng Publishing Group(Baishideng),the RCA database of Baishideng officially released the 2022 Journal Article Influence Index(2022 JAII)of 104 core journals and a list of high-quality academic journals in orthopedics,for the first time on August 9,2022.The list of 104 core journals can be found at:https://www.referencecitationanalysis.com/SearchJournal.Among them,the highest 2022 JAII is 55.015 and the lowest is 3.076.This article introduces the 21 high-quality academic journals and describes the calculation method for the 2022 JAII,the evaluation process,and the inclusion principles for journals in the RCA.These steps are the underpinning of the RCA’s empirical journal academic evaluation service by which the digital platform addresses the needs of authors to select reliable journals for submission,readers to select high-quality literature for reading,and editors to track their own journal citation performance.As such,the RCA core journal list will serve as a useful Find-a-Journal tool.Any interested party is welcome to use this journal list and recommend it to their peers.

Baishideng’s Reference Citation Analysis database announces the first Article Influence Index of multidisciplinary scholars

After three rounds of rigorous evaluation of registered scholars conducted by the Reference Citation Analysis(RCA)editorial team of Baishideng Publishing Group(Baishideng),the RCA database of Baishideng officially released the 2022 Article Influence Index(2022 AII)of 632 scholars from 74 countries/territories in 98 research categories,for the first time.The list of 632 scholars can be found at:https://www.referencecitationanalysis.com/searchscholar.Among them,the highest 2022 AII is 348.211,the highest number of total citations is 42830,and the highest number of total articles is 901.The category with the largest number of RCA scholars is Gastroenterology&Hepatology,with a total of 100(15.8%),and the second is Surgery,with a total of 46(7.3%).This article summarizes the RCA scholars and describes the mission of RCA,the openness and transparency of RCA evaluation,the calculation method for the 2022 AII,and the evaluation process of RCA scholars.The RCA scholar list will effectively serve as a useful Find-a-Scholar tool.Any interested scholar is welcome to register and join this RCA scholar list.

Analysis of Disease Influence on the Flue-cured Tobacco During the Growth and Development Period of Enshi in 2014

The growth of flue-cured tobacco can be significantly influenced by the temperature, sunlight, water, etc. The paper presents and analyzes the details of the disease influence on the flue-cured tobacco during the growth and development period in the high-mountainous and the middle-mountainous regions of Enshi based on the detailed climatolgical data. The results demonstrate that the most important climatic factors affecting the growth and development of flue-cured tobacco contain low temperature, even rainy, lack of sunlight and low evaporation. The deterious ef-fects in the high-mountainous region, the heavy fog region and the flat ground are more serious compared with the middle- and low-mountainous regions, the light fog region and the sloping field, respectively. Furthermore, in order to reduce the deteri-ous effects, helpful countermeasures are proposed favoring the growth and produc-tion of the flue-cured tobacco.

Mathematical Modeling in Social Network Analysis： Using TOPSIS to Find Node Influences in a Social Network

In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes？ Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers＇ inputs as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature： the Kite network and the Information flow network from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers＇ inputs or the topology of the network.

Social Influence Analysis： Models, Methods, and Evaluation

Social influence analysis （SIA） is a vast research field that has attracted research interest in many areas. In this paper, we present a survey of representative and state-of-the-art work in models, methods, and eval- uation aspects related to SIA. We divide SIA models into two types： microscopic and macroscopic models. Microscopic models consider human interactions and the structure of the influence process, whereas macroscopic models consider the same transmission probability and identical influential power for all users. We analyze social influence methods including influence maximization, influence minimization, flow of influence, and individual influence. In social influence evaluation, influence evaluation metrics are introduced and social influence evaluation models are then analyzed. The objectives of this paper are to provide a comprehensive analysis, aid in understanding social behaviors, provide a theoretical basis for influencing public opinion, and unveil future research directions and potential applications.

ASSESSMENT OF INFLUENCE IN CANONICAL CORRELATION ANALYSIS

By expanding the perturbation of covariance matrix in the powers of er-ror term,the influence functions for five canonical measurements in CCA are devel-oped and three sample versions are given.For generalized correlation coefficient p_z,the influence function is a quadratic form of r.v.z,and its distribution is considered.A practical example iUustrates the utility of the proposed influence functions.

Local Influence Analysis of Generalized Linear Model

Nearly thirty years, the diagnosis and influence analysis of linear regression model has been fully developed. So far the local influence analysis of the generalized linear model has not yet seen in the literature. In this paper, local influence is discussed. Then, concise influence matrix is obtained. At last, an example is given to illustrate our results.

Electricity Price Influence Factors Analysis Using Stochastic Matrix for Real-Time Electricity Price Forecasting

Real-time electricity price( RTEP) influence factor extraction is essential to forecasting accurate power system electricity prices. At present,new electricity price forecasting models have been studied to improve predictive accuracy,ignoring the extraction and analysis of RTEP influence factors. In this study,a correlation analysis method is proposed based on stochastic matrix theory.Firstly, an augmented matrix is formulated, including RTEP influence factor data and RTEP state data. Secondly, data correlation analysis results are obtained given the statistical characteristics of source data based on stochastic matrix theory.Mean spectral radius( MSR) is used as the measure of correlativity.Finally,the proposed method is evaluated in New England electricity markets and compared with the BP neural network forecasting method. Experimental results show that the extracted index system comprehensively generalizes RTEP influence factors,which play a significant role in improving RTEP forecasting accuracy.

Analysis of the Meteorological Factors of the Worst Drought Causes in Liupanshui and Its Influence

[Objective] The paper aimed to analyze the meteorological factors of the worst drought in 2010 in Liupanshui City and its impact on the agriculture.[Method] To make research analyses based on the real-time meteorological data and the characters of this drought disaster.[Result]Due to the influence of abnormal atmospheric circulation and El Nio events,the convergence of warm and cold air in the arid are inadequate,so the rainfall reduced seriously,shortage of water resources,and successive drought disasters were intensified by hot and dry weather,moreover,special geographical environment(Karst,desertification,etc.)increased the danger of drought.[Conclusion] Local people faced the test of the severest drought in a century which had great impact on drinking water,agriculture,forestry,hydropower production,residents living and so on.Taking advantage of favorable meteorological conditions for artificial rainfall,and combined with scientific drought-relief measures could help to east the drought in advance and reduce the losses.

Analysis on the Influence of Spring Low Temperature on the Agriculture and the Formation Reason in Liaoning Province in 2010

[Objective] The research aimed to study the influence of spring low temperature on the agriculture and the formation reason in Liaoning Province in 2010. [Method] Based on the synoptics analysis principle, by analyzing the atmospheric circulation situation and satellite cloud map, the influence of spring low temperature on the agriculture and the formation reason of low temperature weather in Liaoning Province during April-May, 2010 were discussed. [Result] The high-altitude situation analysis showed that it was two-trough-two-ridge situation in the high latitude of Eurasia in April, 2010. Ural Mountains high-pressure ridge strengthened to move eastward. Lake Baikal cold air went down toward the southeast along the front of ridge and strengthened into the cold vortex. Liaoning was in the front of cold vortex. Affected by the cold vortex, the temperature in Liaoning area was low. In the first dekad of May, 2010, the activity of cold air was frequent. There were two times cold vortex influence, and the temperature was still low. In the later period of middle dekad of May, the warm ridge entered, and the temperature rose. The high-altitude trough and the low-level jet were the main system and the dynamic condition of precipitation generation respectively. The cold vortex was the main reason of spring continuous low temperature generation, and the secondary reason was the more precipitation. [Conclusion] The research provided the reference basis for the prevention and prediction of spring low temperature in Liaoning Province.

Analysis on the Influence of Computer Technology on Agricultural Development in China

Wide application of the computer-leading information technology is promoting tremendous changes in agricultural management,production,sales and agricultural science and technology,and education,showing broad application prospects,bringing unprecedented development opportunities to the information technology industry,greatly driving agricultural modernization,but also bringing challenges to agricultural science and technology workers to meet the agricultural information technology revolution. Information technology,as a kind of resource,is manifesting its functions in agricultural production and operation of agricultural products,and farmers are also paying more attention to the use of information technology to guide production and sales. China should take full advantage of the computer-centered information resources,and take the road of agricultural modernization and information to develop agriculture.

Influences of load pattern selection and higher modes on pushover analysis for R.C. structures

Load pattern selection is one of the critical issues in pushover analysis (POA) when the influence of higher modes is evident. In terms of interstory drift, comparisons between the nonlinear time history analysis (NL-THA) and the pushover analysis (POA) were conducted for three typical RC frame buildings under a variety of ground motion levels. Eight typical earthquake inputs, including four earthquake records and four artificial earthquake waves, were employed as the input of NL-THA; five typical lateral load patterns were considered in POA. By means of modal participation factor, the higher mode effect in POA was quantified considering floor numbers and the ground motion intensity. Suggestions about load pattern selection in POA were provided when higher mode influence was found evident.