Coupled multiphysical model for investigation of influence factors in the application of microbially induced calcite precipitation

The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiphysics involved in MICP,such as bacterial ureolytic activities,biochemical reactions,multiphase and multicomponent transport,and alteration of the porosity and permeability.The model incorporates multiphysical coupling effects through well-established constitutive relations that connect parameters and variables from different physical fields.It was implemented in the open-source finite element code OpenGeoSys(OGS),and a semi-staggered solution strategy was designed to solve the couplings,allowing for flexible model settings.Therefore,the developed model can be easily adapted to simulate MICP applications in different scenarios.The numerical model was employed to analyze the effect of various factors,including temperature,injection strategies,and application scales.Besides,a TBCH modeling study was conducted on the laboratory-scale domain to analyze the effects of temperature on urease activity and precipitated calcium carbonate.To understand the scale dependency of MICP treatment,a large-scale heterogeneous domain was subjected to variable biochemical injection strategies.The simulations conducted at the field-scale guided the selection of an injection strategy to achieve the desired type and amount of precipitation.Additionally,the study emphasized the potential of numerical models as reliable tools for optimizing future developments in field-scale MICP treatment.The present study demonstrates the potential of this numerical framework for designing and optimizing the MICP applications in laboratory-,prototype-,and field-scale scenarios.

A Problem Not to Be Ignored: The Influencing Factors of Mobile Phone Addiction and Its Influence on Sleep Quality

Background and Objective: With the popularity and widespread use of mobile phones, the effects of mobile phone dependence and addiction on individuals’ physical and mental health have attracted more and more attention. The present study aims to analyze the current state of mobile phone addiction and its impact on sleep quality within the population, while also exploring the influence of related factors on sleep quality. Ultimately, this research will provide a scientific foundation for targeted intervention measures and strategies. Methods: A total of 253 permanent residents in Nanjing were randomly selected as study subjects. The Mobile Phone Addiction Index (MPAI) and Pittsburgh Sleep Quality Index (PSQI) were used to evaluate the degree of smartphone addiction and sleep quality of the study subjects. Body mass index (BMI) was measured according to standardized procedures. Independent sample t-test, Chi-square test, rank sum test and multiple linear regression were used to analyze the correlation between mobile phone addiction and sleep quality, and P Results: 117 people (46.2%) were addicted to mobile phones. Chi-square test showed that the rate of mobile phone addiction in drinking group was significantly higher than that in non-drinking group (P P P P P P P P P P Conclusion: Mobile phone addiction may lead to shorter sleep duration and reduce sleep efficiency. The withdrawal of mobile phone addiction may have a negative impact on sleep quality. According to the characteristics of the population, appropriate comprehensive intervention measures should be taken to build an effective evaluation system, so as to reduce the impact of mobile phone addiction and withdrawal problems on sleep and improve sleep quality.

Influence of Production Factors on the Physico-Chemical Characteristics of Fermented Cassava Dough and Sensory Evaluation of Attieke

Attieke is an Ivorian semolina which obtained by fermenting, pressing and steaming cassava dough. Attieke production remains a traditional activity carried out by less literate women. However, perceived differences in measurable factors and attieke qualities require an investigation of their influence on the characteristics of the pressed dough and attieke. The aim of this study is to improve the quality of the dough in relation to that of the attieke produced. The experiment was carried out on 4 production factors, namely the type of boiled or braised ferment, the incorporation rate of the ferment between 8 and 10%, the addition of oil from 0.1 to 1% and the fermentation time from 12 to 15 hours applied to the Improved African Cassava (IAC) variety. A complete experiment design of 16 samples of fermented dough and attieke was employed. These samples underwent physic-chemical analyses for the fermented dough and sensory evaluation for the attieke. It was found that, except for titratable acidity, reducing sugar content and ash content, the physico-chemical characteristics of the dough of IAC variety were significantly influenced by all production factors and their interaction. Fermentation time significantly influences 60% of the physico-chemical characteristics of the fermented dough. The type of ferment, the oil addition and the ferment rate have a significant influence at 40% of these characteristics. At the sensory level, color, acidity and grain binding with an explained variance of 34.60% were essential for the appreciation of the attieke samples. Thus, these production factors could be considered for the improvement of the fermented dough and attieke production process.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Klebsiella pneumoniae infections after liver transplantation:Drug resistance and distribution of pathogens,risk factors,and influence on outcomes

BACKGROUND Liver transplantation(LT)is the only curative treatment for end-stage liver disease.However,LT recipients are susceptible to infection,which is the leading cause of early mortality after LT.Klebsiella pneumoniae infections(KPIs)in the bloodstream are common in LT recipients.We hypothesized that KPIs and carbapenemresistant Klebsiella pneumoniae(CRKP)infections may affect the outcomes of LT recipients.AIM To assess KPI incidence,timing,distribution,drug resistance,and risk factors following LT and its association with outcomes.METHODS This retrospective study included 406 patients undergoing LT at The Third Xiangya Hospital of Central South University,a tertiary hospital,from January 2015 to January 2023.We investigated the risk factors for KPIs and assessed the impact of KPIs and CRKP infections on the prognosis of LT recipients using logistic regression analysis.RESULTS KPI incidence was 7.9%(n=32),with lung/thoracic cavity the most frequent site of infection;the median time from LT to KPI onset was 7.5 d.Of 44 Klebsiella pneumoniae isolates,43(97.7%)and 34(77.3%)were susceptible to polymyxin B or ceftazidime/avibactam and tigecycline,respectively;>70%were resistant to piperacillin/tazobactam,ceftazidime,cefepime,aztreonam,meropenem,and levofloxacin.Female sex[odds ratio(OR)=2.827,95%confidence interval(CI):1.256-6.364;P=0.012],pre-LT diabetes(OR=2.794,95%CI:1.070-7.294;P=0.036),day 1 post-LT alanine aminotransferase(ALT)levels≥1500 U/L(OR=3.645,95%CI:1.671-7.950;P=0.001),and post-LT urethral catheter duration over 4 d(OR=2.266,95%CI:1.016-5.054;P=0.046)were risk factors for KPI.CRKP infections,but not KPIs,were risk factors for 6-month all-cause mortality post-LT.CONCLUSION KPIs occur frequently and rapidly after LT.Risk factors include female sex,pre-LT diabetes,increased post-LT ALT levels,and urethral catheter duration.CRKP infections,and not KPIs,affect mortality.

Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.

Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Short-term inbound rail transit passenger flow prediction based on BILSTM model and influence factor analysis

Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.

Risk Factors of Enternal Nutrition Intolerance in Septic Patients:A Case-control Study

Objective:This study aimed to investigate the incidence of enteral nutrition intolerance(ENI)in patients with sepsis and explore potential risk factors.Methods:A case-control study was conducted in patients with sepsis who were receiving enteral nutrition(EN)at a tertiary hospital in China.The included patients were divided into the ENI group and the non-ENI group.Univariate and multivariate analyses were performed to identify the risk factors for ENI.Results:A total of 859 patients were included in the study.Among them,288(33.53%)patients experienced symptoms of ENI,including diarrhea,vomiting,bloating,and gastric retention.Logistic regression analysis revealed that the Acute Physiology and Chronic Health Evaluation H(APACHE H)score,thoracocentesis,and usage of cardiotonic drugs(namely,inotropes)were independent predictors of the ENI.Conclusion:The incidence of ENI is relatively high in patients with sepsis,especially in those who have higher APACHE H scores,have undergone thoracocentesis,and have received inotropes.

Influence of transcatheter arterial embolization on symptom distress and fatigue in liver cancer patients

BACKGROUND Hepatocellular carcinoma(HCC)is a prevalent malignancy,and transcatheter arterial embolization(TAE)has emerged as a pivotal therapeutic modality.How-ever,TAE may induce symptom distress and fatigue,adversely affecting the quality of life of patients.AIM To investigate symptom distress,fatigue,and associated factors in HCC patients undergoing TAE.METHODS We used a cross-sectional design and purposive sampling to enroll HCC patients who underwent TAE at our institution from January to December 2022.Question-naires were utilized to collect data on symptom distress and fatigue scores from the first to the third day after TAE.RESULTS Our study revealed a significant reduction in fatigue and symptom distress among patients after TAE.Pain,fatigue,insomnia,fever and abdominal dis-tension were the most common symptoms troubling patients during the first 3 d post-TAE.Marital status,presence of family support,physical functional status,age,and symptom distress were identified as predictors of fatigue in patients.CONCLUSION Healthcare professionals should educate HCC patients on symptom distress and INTRODUCTION Hepatocellular carcinoma(HCC)ranks as the fifth most prevalent cancer and the third leading cause of cancer-related mortality globally.Surgical intervention remains the cornerstone of HCC treatment;however,due to the challenges associated with early diagnosis and the lack of specific diagnostic markers,a considerable proportion of patients are diagnosed at advanced stages,rendering them ineligible for surgical interventions.Transcatheter arterial embolization(TAE)is an interventional therapeutic approach involving the insertion of a fine catheter via the femoral artery to reach the vasculature near the tumor site.TAE aims to obstruct the arterial supply to the tumor by deploying embolic agents,thereby inducing necrosis in cancer cells.This procedure is suitable for patients with good liver function and overall health,particularly those with large HCCs that have not invaded the portal vein[1,2].Nonetheless,following TAE,hepatocytes incur variable degrees of damage,leading to the development of a constel-lation of symptoms reminiscent of acute hepatitis.These symptoms include fatigue and systemic discomfort,such as nausea,vomiting,fever,abdominal pain,as well as transient elevations in aspartate aminotransferase(AST)and alanine aminotransferase(ALT),collectively referred to as postembolization syndrome[3,4].These symptoms may arise due to ischemia of the liver and gallbladder,temporary liver enlargement,and peritoneal irritation.While many studies have explored fatigue and symptom distress in cancer patients both nationally and internationally,with some focusing on symptom distress following transcatheter arterial chemoembolization,there has been limited in-depth investigation into the fatigue and symptom distress resulting from TAE treatment[5-8].Fatigue and pain are both subjective experiences,typically arising from the gradual depletion of energy reserves during the course of illness[9].Fatigue is particularly prevalent among cancer patients,with rates soaring as high as 90%.Despite extensive research exploring cancer-related fatigue and its influencing factors,a unanimous consensus remains elusive.Hence,the primary objective of this study was to investigate the symptom distress and fatigue experienced by liver cancer patients following TAE treatment and to analyze potential contributing factors.

Spatiotemporal variations,influencing factors,and configurational promotion paths of energy efficiency in China’s cities

The promotion of energy efficiency(EE)helps address energy constraints and promote environmental sustainability.This study comprehensively explores the spatiotemporal variations,influencing factors,and configuration promotion paths of EE in 284 Chinese cities during 2003‒2019 using the global super-efficiency minimum distance to strong efficient frontier(G-S-MinDS),exploratory spatial data analysis(ESDA),multiscale geographically weighted regression(MGWR),and fuzzy set qualitative comparative analysis(fsQCA)methods.The findings are:①China’s cities have an annual average EE of 0.658 with a growth rate of 0.53%,showing considerable promotion potential.②Industrial structure optimization,population agglomeration,economic development,and increased green coverage contribute positively,while government intervention and openness hinder China’s urban EE.③Four configurational promotion paths for enhancing China’s urban EE are identified,where among those paths population density is a core condition,while government intervention is not.This study provides valuable insights into substantially improving urban EE,emphasizing the need for targeted policies to address energy and environmental crises in China.

Influencing factors and solution strategies of chimeric antigen receptor T-cell therapy(CAR–T)cell immunotherapy

Chimeric antigen receptor T-cesll therapy(CAR–T)has achieved groundbreaking advancements in clinical application,ushering in a new era for innovative cancer treatment.However,the challenges associated with implementing this novel targeted cell therapy are increasingly significant.Particularly in the clinical management of solid tumors,obstacles such as the immunosuppressive effects of the tumor microenvironment,limited local tumor infiltration capability of CAR–T cells,heterogeneity of tumor targeting antigens,uncertainties surrounding CAR–T quality,control,and clinical adverse reactions have contributed to increased drug resistance and decreased compliance in tumor therapy.These factors have significantly impeded the widespread adoption and utilization of this therapeutic approach.In this paper,we comprehensively analyze recent preclinical and clinical reports on CAR–T therapy while summarizing crucial factors influencing its efficacy.Furthermore,we aim to identify existing solution strategies and explore their current research status.Through this review article,our objective is to broaden perspectives for further exploration into CAR–T therapy strategies and their clinical applications.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Analysis of influencing factors of anxiety and depression in patients with periodontitis

BACKGROUND Periodontitis is a chronic oral disease caused by pathogenic microorganisms that corrode tooth tissue,form periodontal pockets,absorb alveolar bone,and finally lead to tooth loss.During treatment,patients are prone to anxiety,tension,and other negative emotions,which affect their ability to face the disease and may also lead to aggravation of the original condition and affect oral health.Therefore,it is important to improve the negative psychology of patients with periodontitis to clarify the factors that may lead to negative psychological emotions.AIM To investigate the risk factors that may lead to anxiety and depression in patients with periodontitis.METHODS One hundred patients with periodontitis were selected between March 2022 and March 2023 at our hospital.All patients were assessed with the Zung Self-rating Depression Scale(SDS)(≥53 points indicate a depressive state)and Zung Selfrating Anxiety Scale(SAS)(≥50 points indicates an anxious state).In this study,patients who experienced anxiety or depression were included in the occurrence group and those without anxiety or depression were included in the nonoccurrence group.The baseline data of the two groups were compared to explore the risk factors for anxiety and depression in patients with periodontitis.RESULTS A total of 100 patients with periodontitis were included in this study.According to the SDS,38 patients(38.00%)developed depression,with an average SDS score of(68.52±5.85)points.According to the SAS,40 patients(40.00%)developed anxiety,and the average SAS score was(72.15±4.15)points.In this study,56 patients with anxiety or depression were included.Compared with the nonoccurrence group,the occurrence group had higher ages(≥60 years),lower level of hope(low level),educational level(high school or below),disease perception(poor),and sleep disorder(yes).The negative coping dimension scores of the simplified coping style questionnaire(SCSQ)and Dental Fear Scale(DFS)in the occurrence group were higher,whereas the score of the positive coping dimension of the SCSQ was significantly lower(P<0.05).There were no significant differences in the other data between the groups(P>0.05).The results of multiple logistics regression analysis showed that age(≥60 years),level of hope(low level),educational level(high school or below),disease perception(poor),sleep disorder(yes),high negative coping dimension scores of SCSQ,high score of DFS,and low positive coping dimension scores of SCSQ were all factors contributing to the anxiety and depression in patients with periodontitis(odds ratio>1,P<0.05).CONCLUSION Age,hope level,educational level,disease perception,sleep disorders,coping style,and dental fear were all associated with anxiety and depression in patients with periodontitis.

Status quo and factors of depression and anxiety in patients with non-muscle invasive bladder cancer after plasma electrocision

BACKGROUND Bladder cancer is a type of cancer with a high incidence in men.Plasma electrosurgery(PES)is often used in the treatment of bladder cancer.Postoperative complications often cause depression and anxiety in patients after surgery.AIM To investigate the current state of depression and anxiety after PES in patients with non-muscle-invasive bladder cancer and analyze the factors affecting them.METHODS A retrospective study was conducted to compare the baseline data of patients by collecting their medical history and grouping them according to their mental status into negative and normal groups.Logistic regression analysis was used to explore the risk factors affecting the occurrence of anxiety and depression after surgery in patients with bladder cancer.RESULTS Comparative analyses of baseline differences showed that the patients in the negative and normal groups differed in terms of their first surgery,economic status,educational level,and marital status.A logistic regression analysis showed that it affected the occurrence of anxiety in patients with bladder cancer,and the results showed that whether the risk factors were whether or not it was the first surgery,monthly income between 3000 and 3000-6000,secondary or junior high school education level,single,divorced,and widowed statuses.CONCLUSION The risk factors affecting the onset of anxiety and depression in bladder cancer patients after PES are the number of surgeries,economic status,level of education,and marital status.This study provides a reference for the clinical treatment and prognosis of bladder cancer patients in the future.

Assessing the current situation and the influencing factors affecting perceived stigma among older patients after leukemia diagnosis

BACKGROUND Psychological problems are becoming increasingly prominent among older patients with leukemia,with patients potentially facing stigmatization after diagnosis.However,there is limited research on the stigma experienced by these patients and the factors that may contribute to it.AIM To investigate the stigma faced by older patients after being diagnosed with leukemia and to analyze the potential influencing factors.METHODS A retrospective analysis was conducted using clinical data obtained from questionnaire surveys,interviews,and the medical records of older patients with leukemia admitted to the Hengyang Medical School from June 2020 to June 2023.The data obtained included participants’basic demographic information,medical history,leukemia type,family history of leukemia,average monthly family income,pension,and tendency to conceal illness.The Chinese versions of the Social Impact Scale(SIS),Perceived Social Support Scale(PSSS),Self-Rating Anxiety Scale(SAS),and Self-Rating Depression Scale(SDS)were used to assess indicators related to stigma,social support,and mental health status.We used Pearson’s correlation coefficient to analyze the strength and direction of the relationship between the scores of each scale,and regression analysis to explore the factors related to the stigma of older patients with leukemia after diagnosis.RESULTS Data from 120 patients with leukemia aged 65-80 years were analyzed.The total score on the SIS and PSSS was 43.60±4.07 and 37.06±2.87,respectively.The SAS score was 58.35±8.32 and the SDS score was 60.58±5.97.The stigma experienced by older leukemia patients was negatively correlated with social support(r=-0.691,P<0.05)and positively correlated with anxiety and depression(r=0.506,0.382,P<0.05).Age,education level,smoking status,average monthly family income,pension,and tendency to conceal illness were significantly associated with the participants’level of stigma(P<0.05).Age,smoking status,social support,anxiety,and depression were predictive factors of stigmatization among older leukemia patients after diagnosis(all P<0.05),with a coefficient of determination(R2)of 0.644 and an adjusted R2 of 0.607.CONCLUSION Older patients commonly experience stigmatization after being diagnosed with leukemia.Factors such as age,smoking status,social support,and psychological well-being may influence older patients’reported experience of stigma.

Influence of Blended Course Teaching Reform on Student Satisfaction

With the rapid development of information technology in contemporary times,the blended teaching mode that blends online and offline courses has become an international trend in higher education.Taking blended tourism management courses at Chongqing Three Gorges University as an example,we explored the impact of such teaching reform on student satisfaction based on the SERVPERF model.Empirical analysis of 179 valid questionnaires revealed that five elements of the reform,namely,reliability,assurance,valuableness,responsiveness,and empathy,have a significant positive impact on students’learning satisfaction.Specifically,in the context of blended courses,factors such as a stable and reliable teaching environment,comprehensively guaranteed educational conditions,teaching content that highly aligns with students’demands and value expectations,prompt responses to students’needs and feedback,and empathetic consideration of students’perspectives are critical for enhancing student satisfaction.Based on these conclusions,we propose several strategies and methods for improving the effectiveness of blended teaching in the hope of propelling its continuous improvement and optimization,thus further elevating the quality of higher education.

Analysis of status and influencing factors of mental health in patients with systemic lupus erythematosus

BACKGROUND Systemic lupus erythematosus(SLE)is a heterogeneous autoimmune disorder with varied clinical courses and prognoses,not only did the patients suffer from physical impairment,but also various physical and psychiatric comorbidities.Growing evidence have suggested that mental disorders in SLE patients,can lead to various adverse consequences.AIM To explored the features and influencing factors of mental health in patients with SLE and clarifying the correlations between mental health and personality characteristics and perceived social support.The results would provide a basis for psychological intervention in patients with SLE.METHODS The clinical data of 168 patients with SLE admitted at the First Affiliated Hospital of Hainan Medical University between June 2020 and June 2022 were collected.Psychological assessment and correlation analysis were conducted using the Symptom Checklist-90(SCL-90)and Perceived Social Support Scale,and the collected data were compared with the national norms in China.The relevant factors influencing mental health were identified by statistical analysis.A general information questionnaire,the Revised Life Orientation Test,and Short-Form 36-Item Health Survey were employed to assess optimism level and quality of life(QoL),respectively.RESULTS Patients with SLE obtained higher scores for the somatization,depression,anxiety,and phobic anxiety subscales than national norms(P<0.05).A correlation was identified between total social support and total SCL-90 score or each subscale(P<0.05).The factors significantly affecting patients’mental health were hormone dosage and disease activity index(DAI)(P<0.05).The average optimism score of patients with SLE was 14.36±4.42,and 30 cases were in the middle and lower levels.A positive correlation was found between optimism level and QoL scores.CONCLUSION Patients with SLE develop psychological disorders at varying degrees,which are significantly influenced by hormone dosage and DAI.Patients’mental health should be closely monitored during clinical diagnosis and treatment and provided adequate support in establishing positive,healthy thinking and behavior patterns and improving their optimism level and QoL.

A study on the influencing factors of rural tourism promoting households'shared prosperity in Yinan County of Shandong Province

This study examines the influencing factors of rural tourism in promoting shared prosperity among households,using the case study of Yinan County in Shandong province,China.The research aims to provide insights into the economic benefits experienced by low-income households in the context of rural tourism development.Based on field research conducted from April 8,2023,to May 17,2023,including interviews and site visits,the study constructs an evaluation index system to assess the influencing factors.Through expert scoring and the application of a weighted set-valued mathematical statistical model,the importance and quantification of each factor are determined.The results indicate that the current stage of promoting shared prosperity through rural tourism in Yinan County is primarily influenced by the scale of tourist consumption of external visitors.This factor outweighs others such as the participation capacity and willingness of low-income households,the capacity of investment enterprises,and the policies and financial allocation of the local government.The findings emphasize the significance of external visitor spending and highlight the need to address the obstacles faced by low-income households in accessing economic benefits.The evaluation index system and measurement model presented in this study offer a scientific basis for assessing and improving the income situation of low-income households in rural tourism development initiatives.However,it is crucial to note that the importance of these influencing factors may evolve with the lifecycle of the tourism destination.Future research should include long-term tracking and consider a broader range of indicators to deepen our understanding of their mechanisms and significance.Furthermore,alternative approaches and theories may provide valuable perspectives for further exploration in this field.

Characterization of rock thermophysical properties and factors affecting thermal conductivity−A case study of Datong Basin,China

Rock thermal physical properties play a crucial role in understanding deep thermal conditions,modeling the thermal structure of the lithosphere,and discovering the evolutionary history of sedimentary basins.Recent advancements in geothermal exploration,particularly the identification of high-temperature geothermal resources in Datong Basin,Shanxi,China,have opened new possibilities.This study aims to characterize the thermal properties of rocks and explore factors influencing thermal conductivity in basins hosting high-temperature geothermal resources.A total of 70 groups of rock samples were collected from outcrops in and around Datong Basin,Shanxi Province.Thermal property tests were carried out to analyze the rock properties,and the influencing factors of thermal conductivity were studied through experiments at different temperature and water-filled states.The results indicate that the thermal conductivity of rocks in Datong,Shanxi Province,typically ranges from 0.690 W/(m·K)to 6.460 W/(m·K),the thermal diffusion coefficient ranges from 0.441 mm^(2)/s to 2.023 mm^(2)/s,and the specific heat capacity of the rocks ranges from 0.569 KJ/(kg·℃)to 1.117 KJ/(kg·°C).Experimental results reveal the impact of temperature and water saturation on the thermal conductivity of the rock.The thermal conductivity decreases with increasing temperature and rises with high water saturation.A temperature correction formula for the thermal conductivity of different lithologies in the area is proposed through linear fitting.The findings from this study provide essential parameters for the assessment and prediction,development,and utilization of geothermal resources in the region and other basins with typical high-temperature geothermal resource.