Distribution Characteristics and Influencing Factors of Geological Hazards in Tibet

Tibet is one of the areas with most serious geological hazards in China, and the distribution of disasters has obvious local charac teristics. Tibet can be classified as three parts through zoning the danger degree, the mountain canyon high danger zone of east and southeast Tibet, the plateau mountain lake basin and valley middle danger zone of south Tibet, and the Plateau Mountain lake basin low danger zone of south Tibet. This paper takes the debris flow, collapse, landslide as the key points to analyze the distribution characteristics of geological hazards, and analyze the factors which influence the distribution of geological hazards, such as terrain landform, formation lithology, geologic structure pattern, precipitation, earthquake, human activity and so on. finally, as a conclusion., in whole Tibet, the geological hazards are more in southeast than in northwest, more in mountainous area which in the edge of plateau and river valley than in the interior of plateau and lake basin. And most hazards distribute in the regions where human activity is stronger than in other regions, for example towns or strips along the highway.

Exploring the Impact of Factors Affecting the Lifespan of HIVs/AIDS Patient’s Survival: An Investigation Using Advanced Statistical Techniques

This study investigates the impact of various factors on the lifespan and diagnostic time of HIV/AIDS patients using advanced statistical techniques. The Power Chris-Jerry (PCJ) distribution is applied to model CD4 counts of patients, and the goodness-of-fit test confirms a strong fit with a p-value of 0.6196. The PCJ distribution is found to be the best fit based on information criteria (AIC and BIC) with the smallest negative log-likelihood, AIC, and BIC values. The study uses datasets from St. Luke hospital Uyo, Nigeria, containing HIV/AIDS diagnosis date, age, CD4 count, gender, and opportunistic infection dates. Multiple linear regression is employed to analyze the relationship between these variables and HIV/AIDS diagnostic time. The results indicate that age, CD4 count, and opportunistic infection significantly impact the diagnostic time, while gender shows a nonsignificant relationship. The F-test confirms the model's overall significance, indicating the factors are good predictors of HIV/AIDS diagnostic time. The R-squared value of approximately 72% suggests that administering antiretroviral therapy (ART) can improve diagnostic time by suppressing the virus and protecting the immune system. Cox proportional hazard modeling is used to examine the effects of predictor variables on patient survival time. Age and CD4 count are not significant factors in the hazard of HIV/AIDS diagnostic time, while opportunistic infection is a significant predictor with a decreasing effect on the hazard rate. Gender shows a strong but nonsignificant relationship with decreased risk of death. To address the violation of the assumption of proportional hazard, the study employs an assumption-free alternative, Aalen’s model. In the Aalen model, all predictor variables except age and gender are statistically significant in relation to HIV/AIDS diagnostic time. The findings provide valuable insights into the factors influencing diagnostic time and survival of HIV/AIDS patients, which can inform interventions aimed at reducing transmission and improving early diagnosis and treatment. The Power Chris-Jerry distribution proves to be a suitable fit for modeling CD4 counts, while multiple linear regression and survival analysis techniques provide insights into the relationships between predictor variables and diagnostic time. These results contribute to the understanding of HIV/AIDS patient outcomes and can guide public health interventions to enhance early detection, treatment, and care.

Exploring the Impact of Factors Affecting the Lifespan of HIVs/AIDS Patient’s Survival: An Investigation Using Advanced Statistical Techniques

This study investigates the impact of various factors on the lifespan and diagnostic time of HIV/AIDS patients using advanced statistical techniques. The Power Chris-Jerry (PCJ) distribution is applied to model CD4 counts of patients, and the goodness-of-fit test confirms a strong fit with a p-value of 0.6196. The PCJ distribution is found to be the best fit based on information criteria (AIC and BIC) with the smallest negative log-likelihood, AIC, and BIC values. The study uses datasets from St. Luke hospital Uyo, Nigeria, containing HIV/AIDS diagnosis date, age, CD4 count, gender, and opportunistic infection dates. Multiple linear regression is employed to analyze the relationship between these variables and HIV/AIDS diagnostic time. The results indicate that age, CD4 count, and opportunistic infection significantly impact the diagnostic time, while gender shows a nonsignificant relationship. The F-test confirms the model's overall significance, indicating the factors are good predictors of HIV/AIDS diagnostic time. The R-squared value of approximately 72% suggests that administering antiretroviral therapy (ART) can improve diagnostic time by suppressing the virus and protecting the immune system. Cox proportional hazard modeling is used to examine the effects of predictor variables on patient survival time. Age and CD4 count are not significant factors in the hazard of HIV/AIDS diagnostic time, while opportunistic infection is a significant predictor with a decreasing effect on the hazard rate. Gender shows a strong but nonsignificant relationship with decreased risk of death. To address the violation of the assumption of proportional hazard, the study employs an assumption-free alternative, Aalen’s model. In the Aalen model, all predictor variables except age and gender are statistically significant in relation to HIV/AIDS diagnostic time. The findings provide valuable insights into the factors influencing diagnostic time and survival of HIV/AIDS patients, which can inform interventions aimed at reducing transmission and improving early diagnosis and treatment. The Power Chris-Jerry distribution proves to be a suitable fit for modeling CD4 counts, while multiple linear regression and survival analysis techniques provide insights into the relationships between predictor variables and diagnostic time. These results contribute to the understanding of HIV/AIDS patient outcomes and can guide public health interventions to enhance early detection, treatment, and care.

Hazardous and Harmful Factors on Construction Sites and Their Prevention

In this paper, the status quo of safety production on construction sites and the hazardous and harmful factors in the construction process were analyzed, and corresponding suggestions were proposed to make up for the shortcomings of the safety production assurance system standards on construction sites.

The Development of Time-of-flight Mass Spectrometry( TOF-MS) and Its Applications in Screening Food Hazard Factors

The time-of-flight mass spectrometry(TOF-MS),one of the mass spectrometry techniques,has been widely applied in the field of rapid screening of food hazard factors as a superior analysis technique because of its wide mass range,high resolution and mass measurement accuracy,high sensitivity and high analysis speed.In this paper,research progresses of TOF-MS on the detection of food additives,food contaminants and residues,illegal additives,pesticide residues,veterinary drug residues and mycotoxin were reviewed,and its probable approaching applications were prospected.

Geological factors controlling deep geothermal anomalies in the Qianjiaying Mine,China

Here,the geological factors controlling deep geothermal anomalies in mines were studied based on the geotemperature,lithologic thermal conductivity,and related geological data collected from the Qianjiaying Mine,China.A simulation of the change in magma waste heat,conducted using the ANSYS Workbench,revealed the distribution characteristics of geothermal anomalies in this mine and the corresponding geological control factors.The results revealed the following points.(1)First-degree heat hazard level(temperature=31-37℃)occurred in the central and southwestern parts of the mine at an^600-m depth,while second-degree heat hazard level(temperature≥37℃)occurred at an^800-m depth.The geotemperature and geothermal gradient in the southwestern part of the mine were anomalously high.(2)The geotemperatures measured in the mine generally reflected a standard increase with depth,while the geothermal gradient remained unchanged with depth.The geothermal gradient and its average value in the study area were 0.70-4.23 and 2.12C·hm^-1,respectively.(3)A combination of stratum characteristics,geological structure,and groundwater characteristics led to geothermal anomalies in mines;additionally,the waste heat from magma had no significant effect on the geothermal field.

Log-normal censored regression model detecting prognostic factors in gastric cancer:A study of 3018 cases

AIM:To investigate the efficiency of Cox proportional hazard model in detecting prognostic factors for gastric cancer.METHODS:We used the log-normal regression model to evaluate prognostic factors in gastric cancer and compared it with the Cox model.Three thousand and eighteen gastric cancer patients who received a gastrectomy between 1980 and 2004 were retrospectively evaluated.Clinic-pathological factors were included in a log-normal model as well as Cox model.The akaike information criterion (AIC) was employed to compare the efficiency of both models.Univariate analysis indicated that age at diagnosis,past history,cancer location,distant metastasis status,surgical curative degree,combined other organ resection,Borrmann type,Lauren's classification,pT stage,total dissected nodes and pN stage were prognostic factors in both log-normal and Cox models.RESULTS:In the final multivariate model,age at diagnosis,past history,surgical curative degree,Borrmann type,Lauren's classification,pT stage,and pN stage were significant prognostic factors in both log-normal and Cox models.However,cancer location,distant metastasis status,and histology types were found to be significant prognostic factors in log-normal results alone.According to AIC,the log-normal model performed better than the Cox proportional hazard model (AIC value:2534.72 vs 1693.56).CONCLUSION:It is suggested that the log-normal regression model can be a useful statistical model to evaluate prognostic factors instead of the Cox proportional hazard model.

Analysis of Risks in Hainan Island Typhoon Hazard Factor Based on GIS

[Objective] The aim of this paper was to analyze the risks in the typhoon hazard factors in Hainan Island. [Method] Taking the theory and method of natural disasters evaluation as starting point and supporting point, and selecting Hainan province as the research target, where the typhoon disaster occurred relatively serious, based on the typhoon data during 1958-2008, with happening frequency of typhoon hazard-formative factors, maximum rainfall, potentially devastating effects of typhoon winds as evaluation indexes, the typhoon disaster risk evaluation index system and evaluation model were established. And by dint of GIS technique, Hainan island typhoon disaster risk zoning of hazard-formative factors and grading were prepared. [Result] Typhoon occurred frequently in Hainan and there were no certain rules of its annual changes. The monthly changes mainly happed during July to October. The highly dangerous area of typhoon mainly distributed in east coast area. The annual daily precipitation decreased from central mountainous area to the surroundings; typhoon hided in the destructive highly risked area in east, south and west area; low disastrous area occurred in the middle area; the risks of disastrous factors weakened from east area to west area. The distribution area of each level was that low dangerous area>mild dangerous area>highly dangerous area>secondary low dangerous area>highly dangerous area. [Conclusion] The study supplied scientific reference for the government in the united organization and direction of disaster relief work.

Influence of Carcinogenic Factors in the Maxillofacial Region

Objective To study the influence of carcinogenic factors on tissues and organs of the maxillofacial region(MFR)by measuring the expression of biomarkers in the oral fluid.Methods We recruited 421 patients who were divided into 2 groups:356 patients with a tumour of the MFR and 65 healthy people without somatic pathology in medical history.Results The effects of carcinogenic factors on the expression of biomarkers in the oral fluid in patients with a tumour of the MFR revealed a significant increase in the levels of biomarkers of tobacco use-MMP-8,TIMP-1,TIMP-2,and CA 72-4,CEA and CA 125;frequent use or abuse of alcohol-MMP-8,TIMP-1,TIMP-2,AFP and NSE;use of narcotics-TIMP-1 and TIMP-2;presence of occupational hazards in the medical history-MMP-8,MMP-9,TIMP-1 and TIMP-2;with a diagnostic sensitivity(DS)of over 60%.Also our analysis showed that the use of tobacco was significantly affecting the expression of TIMP-1and CA 125;frequent use or abuse of alcohol-CA 19-9,AFP and CEA;use of drugs had an impact on MMP-8expression.However,the occupational hazards in the medical history did not show a statistically significant effect.Conclusion Factors of carcinogenesis affect the expression of biomarkers in the oral fluid.The expression of the biomarkers of the MFR should be compared with that in the control group of patients with no carcinogenic factors.

Short-term and long-term risk factors in gastric cance

While in chronic diseases, such as diabetes, mortalityrates slowly increases with age, in oncological seriesmortality usually changes dramatically during thefollow-up, often in an unpredictable pattern. Forinstance, in gastric cancer mortality peaks in thefirst two years of follow-up and declines thereafter.Also several risk factors, such as TNM stage, largelyaffect mortality in the first years after surgery, whileafterward their effect tends to fade. Temporal trendsin mortality were compared between a gastric cancerseries and a cohort of type 2 diabetic patients. Forthis purpose, 937 patients, undergoing curativegastrectomy with D1/D2/D3 lymphadenectomy forgastric cancer in three GIRCG （Gruppo Italiano RicercaCancro Gastrico = Italian Research Group for GastricCancer） centers, were compared with 7148 type 2diabetic patients from the Verona Diabetes Study. Inthe early/advanced gastric cancer series, mortality fromrecurrence peaked to 200 deaths per 1000 personyears1 year after gastrectomy and then declined,becoming lower than 40 deaths per 1000 person-yearsafter 5 years and lower than 20 deaths after 8 years.Mortality peak occurred earlier in more advanced Tand N tiers. At variance, in the Verona diabetic cohort overall mortality slowly increased during a 10-yearfollow-up, with ageing of the type 2 diabetic patients.Seasonal oscillations were also recorded, mortalitybeing higher during winter than during summer. Alsothe most important prognostic factors presented adifferent temporal pattern in the two diseases： whilethe prognostic significance of T and N stage markedlydecrease over time, differences in survival amongpatients treated with diet, oral hypoglycemic drugsor insulin were consistent throughout the follow-up.Time variations in prognostic significance of main riskfactors, their impact on survival analysis and possiblesolutions were evaluated in another GIRCG series of568 patients with advanced gastric cancer, undergoingcurative gastrectomy with D2/D3 lymphadenectomy.Survival curves in the two different histotypes （intestinaland mixed/diffuse） were superimposed in the first threeyears of follow-up and diverged thereafter. Likewise,survival curves as a function of site （fundus vs body/antrum） started to diverge after the first year. On thecontrary, survival curves differed among age classesfrom the very beginning, due to different post-operativemortality, which increased from 0.5% in patients aged65-74 years to 9.9% in patients aged 75-91 years;this discrepancy later disappeared. Accordingly, theproportional hazards assumption of the Cox modelwas violated, as regards age, site and histology. Tocope with this problem, multivariable survival analysiswas performed by separately considering either thefirst two years of follow-up or subsequent years.Histology and site were significant predictors only aftertwo years, while T and N, although significant bothin the short-term and in the long-term, became lessimportant in the second part of follow-up. Increasingage was associated with higher mortality in the firsttwo years, but not thereafter. Splitting survival timewhen performing survival analysis allows to distinguishbetween short-term and long-term risk factors.Alternative statistical solutions could be to excludepost-operative mortality, to introduce in the modeltime-dependent covariates or to stratify on variablesviolating proportionality assumption.

Investigation on Occupational Disease Inductive Factors ofA utomobile Manufacturing Enterprises and Evaluation of Control Effect

The automobile manufacturing industry has a complex process and various processes,so it has buried many occupational-disease-related safety hazards and is the industry of high incidence of occupational diseases.Accurate identification and effective control of hazards in automobile manufacturing are an important guarantee for effective prevention of occupational disease.In order to investigate the types and status of occupational-disease-inductive factors of a car manufacturer,and evaluate the control effect,the general situation of the enterprise is collected from August 2016 to October 2017.And then the targeted treatment,including management measures,engineering protection and personal protection.The occupational-disease-inductive factors that are mainly produced in automobile manufacturing are productive dust,chemical substance and physical factors.

Determination of a potential set of factors which influence the situation of methane emission into roadways being driven

The currently applied methodology of absolute gassiness forecasting in roadways being driven in Polish hard coal mines is based on the results of investigations frombefore more than twenty years. At present the roadways are being driven in majority ofcases in quite different conditions than those which had been the subject of the said investigations. The application of 'old' methods of forecasting of methane emission during driving of roadways often brings about great discrepancies between the results of the forecasts and actual situation. It is firstly necessary to determine a potential set of factorswhich exert an influence on situation regarding methane emission into roadways beingdriven in order to prepare a verified mathematical model of absolute gassiness forecastingOn the basis of available literature and the investigations conducted by the Central MiningInstitute an initial list of factors has been prepared which can have an impact upon methane emission into roadways being driven. The assumptions of heuristic method have beentaken advantage of for selection of parameters and indices describing the phenomenon ofmethane emission. It has been dictated by the fact that the available literature is lacking apretty unambiguous viewpoint on the subject under consideration and at the same time itis necessary to perform an a priori assessment of the information contained in a givenfeature (factor). A prepared initial set has been scrutinized to be verified on the basis of aconducted expert survey among seventy specialists in this field. After collecting of the results of the survey their statistical elaboration was prepared. The co-efficient of agreementof multiple ordering, the so called concordance co-efficient has been taken advantage of inorder to check the competency of experts. The investigations prove that the experts are inagreement in their opinions. The estimation of a collective assessment of all participants ofthe survey was conducted with the use of the rank sum's test by J. Gren, The results ofthe conducted analysis allowed determining a potential set of factors which influence thesituation of methane emission into roadways being driven. This set, after conductance offurther detailed investigations, can constitute a base for elaboration of a function describ-ing methane emission into roadways being driven in hard coal mines.

Main Factors Affecting the Distribution of the Macroscopic Destruction Field of Earthquake

It is proposed that some possible macroseismic epicenters can be determined quickly from the relationship that the microseismic epicenters located by instruments bear with faults. Based on these so-called macroseismic epicenters, we can make fast seismic hazard estimation after a shock by use of the empirical distribution model of seismic intensity. In comparison with the method that uses the microseismic epicenters directly, this approach can increase the precision of fast seismic hazard estimation. Statistical analysis of 133 main earthquakes in China was made. The result shows that the deviation distance between the microseismic epicenter and macroseismic epicenter falls within the range of 35 km for 88 % earthquakes of the total and within the range of 35 to 75 km for the remaining ones. Then, we can take the area that has the microseismic epicenter as its center and is 35 km in radius as the area for emphatic analysis, and take the area within 75 km around the microseismic epicenter as the area for general analysis. The relation between the 66 earthquake cases on the N-S Seismic Belt in China and the spatial distribution characteristics of faults and the results of focal mechanism solution were analyzed in detail. We know from the analysis that the error of instrumental epicenter determination is not the only factor that gives effects to the deviation of the macroseismic epicenter. In addition to it, the fault size, fault distribution, fault activity, fault intersection types, earthquake magnitude, etc. are also main affecting factors. By sorting out, processing and analyzing these affecting factors, the principle and procedures for quickly determining the possible position of the macroseismic epicenter were set up. Taking these as a basis and establishing a nationwide database of faults that contains relevant factors, it is possible to apply this method in practical fast estimation of seismic hazard.

糖尿病肾脏疾病预后影响因素的COX比例风险回归模型分析

目的基于COX比例风险回归模型分析糖尿病肾脏疾病(diabetic kidney disease,DKD)预后的影响因素,为临床早期评估和防治DKD提供科学的依据。方法收集多中心(河南中医药大学第一附属医院、河南中医药大学第三附属医院、河南省中医院及郑州市人民医院)2010—2021年就诊治疗的DKD患者资料,包括一般资料、实验室指标、中医辨证分型及中医药治疗,以肾小球滤过率(eGFR)下降≥50%、血肌酐(Scr)翻倍、DKD 5期、死亡为结局指标,随访其发生时间及情况,利用COX比例风险回归模型分析筛选DKD预后影响因素。结果本研究最终纳入1947例患者,随访时间为4.65(4.557~4.746)年,发生复合终点事件305例(15.67%)。单因素COX回归分析结果表明,不同年龄、DKD病程≥4年、饮酒史、吸烟史、高血压、冠心病、脑血管病、糖尿病足、糖尿病眼病、糖化血红蛋白(HbA1c)、血尿酸(SUA)、Scr、24 h尿蛋白定量(24 h-UTP)、eGFR、湿热血瘀证、脾肾气虚兼湿聚血瘀证、脾肾阳虚兼血瘀证、中药熏洗、服用中药患者DKD预后情况比较,差异有统计学意义(P<0.05)。多因素COX回归分析结果表明,年龄[HR(95%CI)=2.52(1.92,3.30)]、DKD病程[HR(95%CI)=1.62(1.09,2.42)]、吸烟史[HR(95%CI)=1.61(1.13,2.29)]、饮酒史[HR(95%CI)=1.41(1.01,1.95)]、脑血管病[HR(95%CI)=1.33(1.01,1.75)]、糖尿病眼病[HR(95%CI)=1.43(1.13,1.82)]、SUA[HR(95%CI)=1.72(1.26,2.33)]、24 h-UTP[HR(95%CI)=1.48(1.14,1.91)]、脾肾气虚兼湿聚血瘀证[HR(95%CI)=2.22(1.44,3.43)]与DKD发生终点事件的风险关系密切(P<0.05),服用中药[HR(95%CI)=2.57(2.00,3.31)]能够减少终点事件的发生(P<0.05)。结论年龄、DKD病程、吸烟史、饮酒史、脑血管病、糖尿病眼病、SUA、24 h-UTP、脾肾气虚兼湿聚血瘀证是影响DKD患者预后的危险因素,而服用中药治疗为其保护因素。

考虑时间变化的洪涝灾害损失评估

洪涝灾害是对我国影响最大的自然灾害之一。聚焦灾害损失评估问题,本文构建了考虑时间变化的洪涝灾害损失函数。一方面,表征灾害损失随着致灾因子强度先递增、而后增幅趋缓的静态S型曲线关系;另一方面,通过量级、形状和位置三个参数综合考虑灾害损失随时间的动态变化情况。基于《中国水旱灾害防御公报》提供的受灾人口、直接经济损失数据,对于各省级行政区2006—2021年洪涝灾害损失进行评估分析。结果表明:通过拟合洪涝灾害损失函数,洪涝灾害损失关于致灾因子强度和时间的三维空间散点图可有效地拓展成为连续的三维空间曲面及二维空间热力图。各省级行政区受灾人口整体上呈现出逐年下降的特征,但随致灾因子强度的增加而趋于增加。各省级行政区直接经济损失则表现出明显的差异,随时间呈现出大幅下降、缓慢下降和略有增加等不同特征。考虑时间变化的洪涝灾害损失函数是变化环境下灾害评估的有效工具,可为区域洪涝灾情评估提供借鉴和参考。

基于风雨综合指数的安徽省台风灾害房屋风险评估方法

台风致灾因子具有多重性,相对于其他灾种其风险评估更加复杂。采用安徽省81个国家气象站及1035个区域气象站台风过程逐日降水量、最大风速资料,构建台风风雨综合指数;利用台风风雨综合指数及孕灾环境影响系数,开展台风致灾危险性评估;基于自然灾害风险系统理论,综合致灾危险性、承灾体暴露度和脆弱性信息,评估安徽省台风灾害房屋风险。结果表明:影响安徽省台风年均个数为1.9个,持续天数以2~4 d居多;台风降水南部多于北部、山区多于平原。台风致灾高危险区位于皖南山区和大别山区,较高危险区位于江淮之间东部,低危险区位于沿淮淮北大部及江淮之间西北部。台风灾害房屋高及较高风险区主要分布在大别山区、江淮之间东部及皖南山区,这些区域海拔总体较高,台风过境易引发山洪地质灾害,加之房屋脆弱性较高,房屋倒塌及损毁风险高;中等风险区位于沿淮至江淮之间、江南部分地区,呈零星分布;较低和低风险区位于淮河以北中西部、沿江部分地区及城市主城区。利用全省各县区台风造成的房屋倒损数据,从空间一致性及散点相关对区划结果进行验证得到,区划结果与灾损具有高度的空间一致性,二者散点相关通过0.01的显著性水平检验,安徽省台风灾害房屋风险区划结果与实际情况基本吻合。

激素治疗慢性肾脏病进展高风险IgA肾病患者的预后分析——一项回顾性研究

背景IgA肾病(IgAN)是世界范围内常见的原发性肾小球肾炎之一,目前糖皮质激素是否能改善慢性肾脏病(CKD)进展高风险IgAN患者肾脏预后尚无明确结论。目的本研究旨在探讨激素治疗对CKD进展高风险IgAN患者的治疗反应及肾脏预后的影响。方法回顾性纳入2017年1月—2021年10月于郑州大学第一附属医院就诊的CKD进展高风险IgAN患者。根据是否进行激素治疗将患者分为激素治疗组和支持治疗组,采用倾向匹配法按照性别、年龄、24 h尿蛋白定量、估算肾小球滤过率(eGFR)对患者进行1∶1匹配筛选病例,收集患者的临床及病理资料,记录患者治疗1年内疾病缓解情况及不良反应发生情况。以开始支持治疗的日期作为随访起点,随访至2022-10-31,主要终点事件定义为:进展为终末期肾脏病(ESRD)或接受透析治疗。复合终点事件定义为:eGFR较基线持续下降超过30%或进入ESRD或接受透析或患者死亡;运用Kaplan-Meier法绘制生存曲线,并采用Log-rank检验比较两组患者主要/复合终点事件累积发生率的差异。运用Cox比例风险回归分析探究影响CKD进展高风险IgAN患者预后的可能因素。结果共有236例原发性IgAN患者符合纳入标准,经过1∶1匹配,激素治疗组97例与支持治疗组97患者匹配成功,两组基线数据匹配均衡。激素治疗组患者完全缓解率、部分缓解率均高于支持治疗组(χ^(2)=6.171,P=0.013;χ^(2)=3.973,P=0.046)。中位随访时间为18.00(9.75,28.00)个月。Kaplan-Meier生存分析结果显示,激素治疗组的主要终点事件累积发生率低于支持治疗组(χ^(2)=4.495,P=0.034);激素治疗组的复合终点事件累积发生率低于支持治疗组(χ^(2)=4.419,P=0.036)。符合纳入标准的236例患者中有177例中等量蛋白尿患者,采用倾向匹配法按照性别、年龄、24 h尿蛋白定量、eGFR对激素治疗和支持治疗的177例患者进行1∶1匹配后,激素治疗中等量蛋白尿者和支持治疗中等量蛋白尿者各有76例患者匹配成功。Kaplan-Meier生存曲线结果显示,激素治疗中等量蛋白尿者的主要终点事件累积发生率低于支持治疗中等量蛋白尿者(χ^(2)=4.127,P=0.042);激素治疗中等量蛋白尿者的复合终点事件累积发生率低于支持治疗中等量蛋白尿者(χ^(2)=4.934,P=0.026)。多因素Cox比例风险回归分析结果显示血红蛋白(HR=0.982)、血肌酐(HR=1.019)、eGFR(HR=1.020)、24 h尿蛋白定量(HR=1.205)是影响CKD进展高风险IgAN患者发生主要终点事件的影响因素(P<0.05)。激素治疗组感染发生率高于支持治疗组(P<0.05)。结论在CKD进展高风险IgAN肾病患者中,与单纯支持治疗相比,激素治疗可以显著提升肾脏缓解率,降低肾功能下降、肾衰竭风;但仍需警惕其不良反应的发生。

基于系统动力学的危险化学品运输风险因素研究

为了降低危化品运输事故频次,规避危化品在运输过程中的风险,基于系统动力学模型,从人、机、环、管4个维度构建危化品运输风险因素指标体系,使用AHP法对指标权重进行赋值,结合风险因素间的因果关系构建参数方程,利用Vensim软件仿真模拟危化品运输风险水平的变化趋势,确定单因素变量值和人、机、环、管风险子系统权重的变化对危化品运输风险系统动力学模型的影响程度。结果表明:安全意识薄弱、设备故障等风险因素的变动以及人、机、环、管风险子系统的权重变动都会影响危化品运输风险水平,人、机、环、管4个子系统对危化品运输风险的影响程度从高到低依次是人、管、环、机。研究结果可为降低危化品运输过程中的风险和制定危化品运输事故预防策略提供一定参考。

地质灾害易发性评价因子分级的AIFFC算法优化

针对地质灾害易发性评价因子分级数不确定的问题,引入自适应膨胀因子模糊覆盖分级方法(fuzzy cover approach for clustering based on adaptive inflation factor,AIFFC)对易发性评价因子分级进行优化。以湖南省湘乡市为研究区,提取了坡度、坡向、高程、年平均降雨量、归一化植被指数、道路、断层、岩性和土地利用9类评价因子,运用AIFFC及自然断点法(natural breakpoint classification,NBC)对连续型因子进行分级,并分别代入加权信息量模型和随机森林模型,获取研究区易发性区划图。采用单因子分级结果精度、灾积比分析和易发性分区结果对AIFFC分级法的优越性进行检验,结果表明:各因子采用AIFFC算法分级的AUC值均高于自然断点法;基于AIFFC的随机森林模型及加权信息量模型的高易发区灾积比分别提升了56.3%、74.6%,低易发区灾积比分别降低了48%、58.1%,AUC值分别提升了7.6%、2.7%。采用AIFFC分级方法优化了地质灾害易发性评价因子分级,显著提高了地质灾害易发性评价的合理性。