基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

内皮细胞特异性骨形态发生蛋白2对血管新生的影响:生物信息学分析和实验验证

背景:血管新生是心血管疾病的主要干预靶点,骨形态发生蛋白2具有调控血管新生作用,但内皮细胞特异性骨形态发生蛋白2对血管新生的调控作用不清楚。目的:探讨内皮细胞特异性骨形态发生蛋白2对血管新生的影响。方法:(1)生物信息学分析:通过Panglao DB公共基因表达数据库单细胞转录组荟萃分析观察骨形态发生蛋白2细胞群表达丰度和定位。血管新生小鼠和内皮(心内膜)过表达骨形态发生蛋白2小鼠转录组测序数据集探索内皮细胞骨形态发生蛋白2对血管新生信号通路的调控作用。(2)体内实验验证:建立小鼠后肢缺血模型,对比模型小鼠患侧与健侧缺血后肢7,14和21 d血流灌注情况,免疫荧光和免疫组织化学染色评估小鼠骨形态发生蛋白2和CD31的表达定位情况。(3)体外实验验证:体外培养人脐静脉内皮细胞,分为对照组、缺氧组和骨形态发生蛋白2抑制剂(Noggin蛋白)干预组,培养24 h,观察各组内皮细胞血管新生情况。结果与结论:(1)内皮细胞是表达骨形态发生蛋白2的重要细胞亚群,在血管新生内皮细胞和骨形态发生蛋白2过表达内皮细胞转录组再分析均发现骨形态发生蛋白2表达明显升高,血管新生通路明显激活。(2)缺血7 d小鼠新生血管周围骨形态发生蛋白2阳性血管明显增加(P<0.05),缺血2周骨形态发生蛋白2阳性血管明显减少(P<0.001)。(3)体外培养人脐静脉内皮细胞,缺氧干预后,内皮细胞迁移能力和血管出芽明显增加,血管新生因子血管内皮生长因子和血小板衍生生长因子的表达明显升高,Noggin明显减少了缺氧诱导的内皮细胞血管新生(P<0.001),并下调血管内皮生长因子和血小板衍生生长因子的表达(P<0.01)。(4)结果证实,内皮细胞特异性骨形态发生蛋白2具有调控血管新生作用,靶向性内皮细胞骨形态发生蛋白2可望改善血管新生。

Phosphorus limitation on CO_(2)fertilization effect in tropical forests informed by a coupled biogeochemical model

Tropical forests store more than half of the world's terrestrial carbon(C)pool and account for one-third of global net primary productivity(NPP).Many terrestrial biosphere models(TBMs)estimate increased productivity in tropical forests throughout the 21st century due to CO_(2)fertilization.However,phosphorus(P)liaitations on vegetation photosynthesis and productivity could significantly reduce the CO_(2)fertilization effect.Here,we used a carbon-nitrogen-phosphorus coupled model(Dynamic Land Ecosystem Model;DLEM-CNP)with heterogeneous maximum carboxylation rates to examine how P limitation has affected C fluxes in tropical forests during1860-2018.Our model results showed that the inclusion of the P processes enhanced model performance in simulating ecosystem productivity.We further compared the simulations from DLEM-CNP,DLEM-CN,and DLEMC and the results showed that the inclusion of P processes reduced the CO_(2)fertilization effect on gross primary production(GPP)by 25%and 45%,and net ecosystem production(NEP)by 28%and 41%,respectively,relative to CN-only and C-on ly models.From the 1860s to the 2010s,the DLEM-CNP estimated that in tropical forests GPP increased by 17%,plant respiration(Ra)increased by 18%,ecosystem respiration(Rh)increased by 13%,NEP increased by 121%per unit area,respectively.Additionally,factorial experiments with DLEM-CNP showed that the enhanced NPP benefiting from the CO_(2) fertilization effect had been offset by 135%due to deforestation from the 1860s to the 2010s.Our study highlights the importance of P limitation on the C cycle and the weakened CO_(2)fertilization effect resulting from P limitation in tropical forests.

Reduction of uncertainties in rice yield response to elevated CO2 by experiment-model integration:A case study in East China

Accurate prediction of future rice yield needs the precise estimations of rice yield response to climate change factors,of which the most important one is the increasing carbon dioxide(CO_(2))concentrations.Estimates of CO_(2) fertilization effect(CFE)on rice,however,still had large uncertainties.Therefore,using the rice planting areas in East China as the study area,we firstly compared the rice yields and CFE predicted by four state-of-the-art crop models,and found that the CFE predicted by these models had significant differences.We then quantified the CFE on rice yield using the field-controlled experiment conducted at Danyang site at Jiangsu province.Using CFE measurements from a field experiment as benchmark,we have developed an experiment–model integration approach aiming to reduce this variation.This study thus highlights the large CFE uncertainties of current crop models and provides us with a method to reduce this uncertainty,which is beneficial for the accurate prediction of future global rice yield in the context of climate change.

Performance validation of High Mountain Asia 8-meter Digital Elevation Model using ICESat-2 geolocated photons

High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate change.An accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to analyze it in a 3D environment and understand its intricate role as the Water Tower of Asia.The science teams of NASA realized an 8-m DEM using satellite stereo imagery for HMA,termed HMA 8-m DEM.In this research,we assessed the vertical accuracy of HMA 8-m DEM using reference elevations from ICESat-2 geolocated photons at three test sites of varied topography and land covers.Inferences were made from statistical quantifiers and elevation profiles.For the world’s highest mountain,Mount Everest,and its surroundings,Root Mean Squared Error(RMSE)and Mean Absolute Error(MAE)resulted in 1.94 m and 1.66 m,respectively;however,a uniform positive bias observed in the elevation profiles indicates the seasonal snow cover change will dent the accurate estimation of the elevation in this sort of test sites.The second test site containing gentle slopes with forest patches has exhibited the Digital Surface Model(DSM)features with RMSE and MAE of 0.58 m and 0.52 m,respectively.The third test site,situated in the Zanda County of the Qinghai-Tibet,is a relatively flat terrain bed,mostly bare earth with sudden river cuts,and has minimal errors with RMSE and MAE of 0.32 m and 0.29 m,respectively,and with a negligible bias.Additionally,in one more test site,the feasibility of detecting the glacial lakes was tested,which resulted in exhibiting a flat surface over the surface of the lakes,indicating the potential of HMA 8-m DEM for deriving the hydrological parameters.The results accrued in this investigation confirm that the HMA 8-m DEM has the best vertical accuracy and should be of high use for analyzing natural hazards and monitoring glacier surfaces.

A multi-mechanism numerical simulation model for CO_(2)-EOR and storage in fractured shale oil reservoirs

Under the policy background and advocacy of carbon capture,utilization,and storage(CCUS),CO_(2)-EOR has become a promising direction in the shale oil reservoir industry.The multi-scale pore structure distribution and fracture structure lead to complex multiphase flow,comprehensively considering multiple mechanisms is crucial for development and CO_(2) storage in fractured shale reservoirs.In this paper,a multi-mechanism coupled model is developed by MATLAB.Compared to the traditional Eclipse300 and MATLAB Reservoir Simulation Toolbox(MRST),this model considers the impact of pore structure on fluid phase behavior by the modified Peng—Robinson equation of state(PR-EOS),and the effect simultaneously radiate to Maxwell—Stefan(M—S)diffusion,stress sensitivity,the nano-confinement(NC)effect.Moreover,a modified embedded discrete fracture model(EDFM)is used to model the complex fractures,which optimizes connection types and half-transmissibility calculation approaches between non-neighboring connections(NNCs).The full implicit equation adopts the finite volume method(FVM)and Newton—Raphson iteration for discretization and solution.The model verification with the Eclipse300 and MRST is satisfactory.The results show that the interaction between the mechanisms significantly affects the production performance and storage characteristics.The effect of molecular diffusion may be overestimated in oil-dominated(liquid-dominated)shale reservoirs.The well spacing and injection gas rate are the most crucial factors affecting the production by sensitivity analysis.Moreover,the potential gas invasion risk is mentioned.This model provides a reliable theoretical basis for CO_(2)-EOR and sequestration in shale oil reservoirs.

3D seismic forward modeling from the multiphysical inversion at the Ketzin CO_(2) storage site

From June 2008 to August 2013,approximately 67 kt of CO_(2) was injected into a deep saline formation at the Ketzin pilot CO_(2) storage site.During injection,3D seismic surveys have been performed to monitor the migration of sequestered CO_(2).Seismic monitoring results are limited by the acquisition and signal-to-noise ratio of the acquired data.The multiphysical reservoir simulation provides information regarding the CO_(2) fluid behavior,and the approximated model should be calibrated with the monitoring results.In this work,property models are delivered from the multiphysical model during 3D repeated seismic surveys.The simulated seismic data based on the models are compared with the real data,and the results validate the effectiveness of the multiphysical inversion method.Time-lapse analysis shows the trend of CO_(2) migration during and after injection.

Depositional model of the Member Deng-2 marginal microbial mound-bank complex of the Dengying Formation in the southwestern Sichuan Basin, SW China: Implications for the Ediacaran microbial mound construction and hydrocarbon exploration

Recent advances in hydrocarbon exploration have been made in the Member Deng-2 marginal microbial mound-bank complex reservoirs of the Dengying Formation in the western Sichuan Basin, SW China,where the depositional process is regarded confusing. The microfacies, construction types, and depositional model of the Member Deng-2 marginal microbial mound-bank complex have been investigated using unmanned aerial vehicle photography, outcrop section investigation, thin section identification,and seismic reflections in the southwestern Sichuan Basin. The microbialite lithologic textures in this region include thrombolite, dendrolite, stromatolite, fenestral stromatolite, spongiostromata stone,oncolite, aggregated grainstone, and botryoidal grapestone. Based on the comprehensive analysis of“depositional fabrics-lithology-microfacies”, an association between a fore mound, mound framework,and back mound subfacies has been proposed based on water depth, current direction, energy level and lithologic assemblages. The microfacies of the mound base, mound core, mound flank, mound cap, and mound flat could be recognized among the mound framework subfacies. Two construction types of marginal microbial mound-bank complex have been determined based on deposition location, mound scale, migration direction, and sedimentary facies association. Type Jinkouhe microbial mound constructions(TJMMCs) develop along the windward margin owing to their proximity to the seaward subfacies fore mound, with a northeastwardly migrated microbial mound on top of the mud mound,exhibiting the characteristics of large-sized mounds and small-sized banks in the surrounding area. Type E'bian microbial mound constructions(TEMMCs) primarily occur on the leeward margin, resulting from the presence of onshore back mound subfacies, with the smaller southwestward migrated microbial mounds existing on a thicker microbial flat. The platform margin microbial mound depositional model can be correlated with certain lateral comparison profile and seismic reflection structures in the 2D seismic section, which can provide references for future worldwide exploration. Microbial mounds with larger buildups and thicker vertical reservoirs are typically targeted on the windward margin, while small-sized microbial mounds and flats with better lateral connections are typically focused on the leeward margin.

Metal-N_(4) model single‐atom catalyst with electroneutral quadri‐pyridine macrocyclic ligand for CO_(2) electroreduction

Metal–N–C single‐atom catalysts,mostly prepared from pyrolysis of metalorganic precursors,are widely used in heterogeneous electrocatalysis.Since metal sites with diverse local structures coexist in this type of material and it is challenging to characterize the local structure,a reliable structure–property relationship is difficult to establish.Conjugated macrocyclic complexes adsorbed on carbon support are well‐defined models to mimic the singleatom catalysts.Metal–N_(4) site with four electroneutral pyridine‐type ligands embedded in a graphene layer is the most commonly proposed structure of the active site of single‐atom catalysts,but its molecular counterpart has not been reported.In this work,we synthesized the conjugated macrocyclic complexes with a metal center(Co,Fe,or Ni)coordinated with four electroneutral pyridinic ligands as model catalysts for CO_(2) electroreduction.For comparison,the complexes with anionic quadri‐pyridine macrocyclic ligand were also prepared.The Co complex with the electroneutral ligand expressed a turnover frequency of CO formation more than an order of magnitude higher than that of the Co complex with the anionic ligand.Constrained ab initio molecular dynamics simulations based on the well‐defined structures of the model catalysts indicate that the Co complex with the electroneutral ligand possesses a stronger ability to mediate electron transfer from carbon to CO_(2).

Delayed treatment of diabetic foot ulcer in patients with type 2 diabetes and its prediction model

BACKGROUND Diabetic foot(DF)is a serious complication of type 2 diabetes.This study aimed to investigate the factors associated with DF occurrence and the role of delayed medical care in a cohort of patients with type 2 diabetes.AIM To reveal the impact of delayed medical treatment on the development of DF in patients with type 2 diabetes and to establish a predictive model for DF.METHODS In this retrospective cohort study,292 patients with type 2 diabetes who underwent examination at our hospital from January 2023 to December 2023 were selected and divided into the DF group(n=82,DF)and nondiabetic foot group(n=210,NDF).Differential and correlation analyses of demographic indicators,laboratory parameters,and delayed medical treatment were conducted for the two groups.Logistic regression was applied to determine influencing factors.Receiver operating characteristic(ROC)analysis was performed,and indicators with good predictive value were selected to establish a combined predictive model.RESULTS The DF group had significantly higher body mass index(BMI)(P<0.001),disease duration(P=0.012),plasma glucose levels(P<0.001),and HbA1c(P<0.001)than the NDF group.The NDF group had significantly higher Acute Thrombosis and Myocardial Infarction Health Service System(ATMHSS)scores(P<0.001)and a significantly lower delayed medical treatment rate(72.38%vs 13.41%,P<0.001).BMI,duration of diabetes,plasma glucose levels,HbA1c,diabetic peripheral neuropathy,and nephropathy were all positively correlated with DF occurrence.ATMHSS scores were negatively correlated with delayed time to seek medical treatment.The logistic regression model revealed that BMI,duration of diabetes,plasma glucose levels,HbA1c,presence of diabetic peripheral neuropathy and nephropathy,ATMHSS scores,and delayed time to seek medical treatment were influencing factors for DF.ROC analysis indicated that plasma glucose levels,HbA1c,and delayed medical treatment had good predictive value with an area under the curve of 0.933 for the combined predictive model.CONCLUSION Delayed medical treatment significantly affects the probability of DF occurrence in patients with diabetes.Plasma glucose levels,HbA1c levels,and the combined predictive model of delayed medical treatment demonstrate good predictive value.

Study of the Effect of High-Voltage Low-Frequency Electrotherapy on Type 2 Diabetes in an in Vivo Model

The study investigates the impact of high-voltage low-frequency electrotherapy on glucose levels and hematological parameters in an in vivo model of type 2 diabetes. The results demonstrate a significant reduction in glucose increases during glucose tolerance tests (GTT) and suggest potential mechanisms, including improved insulin sensitivity and reduced inflammation. Hematological analysis indicates no adverse effects of electrotherapy on healthy or diabetic mice. This study supports the potential of high-voltage low-frequency electrotherapy as an adjunctive treatment for type 2 diabetes, warranting further research into its mechanisms and long-term effects.

Prediction of(n,2n)reaction cross-sections of long-lived fission products based on tensor model

Interest has recently emerged in potential applications of(n,2n)reactions of unstable nuclei.Challenges have arisen because of the scarcity of experimental cross-sectional data.This study aims to predict the(n,2n)reaction cross-section of long-lived fission products based on a tensor model.This tensor model is an extension of the collaborative filtering algorithm used for nuclear data.It is based on tensor decomposition and completion to predict(n,2n)reaction cross-sections;the corresponding EXFOR data are applied as training data.The reliability of the proposed tensor model was validated by comparing the calculations with data from EXFOR and different databases.Predictions were made for long-lived fission products such as^(60)Co,^(79)Se,^(93)Zr,^(107)P,^(126)Sn,and^(137)Cs,which provide a predicted energy range to effectively transmute long-lived fission products into shorter-lived or less radioactive isotopes.This method could be a powerful tool for completing(n,2n)reaction cross-sectional data and shows the possibility of selective transmutation of nuclear waste.

Tidal modeling based on satellite altimetry observations of TOPEX/ Poseidon, Jason1, Jason2, and Jason3 with high prediction capability: A case study of the Baltic Sea

This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon,Jason1,Jason2,and Jason3 altimetry missions for tidal modeling.We generate a time series of along-track observations and apply a developed method to produce tidal models with specific tidal constituents for each location.Our tidal modeling methodology follows an iterative process:partitioning sea surface height(SSH)observations into analysis/training and prediction/validation parts and ultimately identi-fying the set of tidal constituents that provide the best predictions at each time series location.The study focuses on developing 1256 time series along the altimetry tracks over the Baltic Sea,each with its own set of tidal constituents.Verification of the developed tidal models against the sSH observations within the prediction/validation part reveals mean absolute error(MAE)values ranging from 0.0334 m to 0.1349 m,with an average MAE of 0.089 m.The same validation process is conducted on the FES2014 and EOT20 global tidal models,demonstrating that our tidal model,referred to as BT23(short for Baltic Tide 2023),outperforms both models with an average MAE improvement of 0.0417 m and 0.0346 m,respectively.In addition to providing details on the development of the time series and the tidal modeling procedure,we offer the 1256 along-track time series and their associated tidal models as supplementary materials.We encourage the satellite altimetry community to utilize these resources for further research and applications.

24 Model在道路运输事故成因中的应用

为预防道路运输事故,基于事故致因“2-4”(24 Model)模型,对2015—2021年发生的215起道路运输事故的行为原因进行研究。从个人层面和组织层面分析导致事故发生的直接原因、间接原因、根本原因及其根源原因。结果表明:发生频次最多的不安全动作是驾驶员超速行驶(占10.67%);22.33%的道路运输事故存在管理者违章安排无资质员工上岗作业;管理者和领导者对57.67%的道路运输事故的发生有重要影响;由人为因素产生的不安全物态占比达71.53%;驾驶员、车辆安全生产管理制度欠缺或执行不到位在根本原因中尤为突出(占20.92%)。基于此,提出道路运输事故预防对策并构建出道路运输系统各因素关系图。

基于24Model的煤炭企业安全文化提升实践研究

为了发挥安全文化在事故预防中的重要作用,运用基于事故致因“2-4”模型的安全文化水平提升方法研究某煤炭企业的安全文化建设现状并提出改进措施。首先,明确了24Model视域下的安全文化水平提升方法在我国的适用性;然后,从安全文化水平现状和安全理念2方面开展了针对该企业的实践研究;最后,提出改进措施。结果表明:该企业安全文化水平总体上要比国内或同行业的安全业绩较差的企业好,比安全业绩较好的企业差;该企业安全理念涉及32元素的13个方面;一线人员、班组长、专业人员和领导层对部分元素的理解程度不佳,并且这些元素中仅有元素3、元素4、元素6、元素13、元素16的内容在企业的安全理念有所体现。提出了14条改进的安全理念用于提高企业的安全文化水平。

2-D Modeling and Calculations of Stratospheric Ozone and Influences of Convection, Diffusion, and Time

An engineering system approach of 2-D cylindrical model of transient mass balance calculations of ozone and other concerned chemicals along with fourteen photolysis, ozone-generating and ozone-depleting chemical reaction equations was developed, validated, and used for studying the ozone concentrations, distribution and peak of the layer, ozone depletion and total ozone abundance in the stratosphere. The calculated ozone concentrations and profile at both the Equator and a 60˚N location were found to follow closely with the measured data. The calculated average ozone concentration was within 1% of the measured average, and the deviation of ozone profiles was within 14%. The monthly evolution of stratospheric ozone concentrations and distribution above the Equator was studied with results discussed in details. The influences of slow air movement in both altitudinal and radial directions on ozone concentrations and profile in the stratosphere were explored and discussed. Parametric studies of the influences of gas diffusivities of ozone DO3 and active atomic oxygen DO on ozone concentrations and distributions were also studied and delineated. Having both influences through physical diffusion and chemical reactions, the diffusivity (and diffusion) of atomic oxygen DO was found to be more sensitive and important than that of ozone DO3 on ozone concentrations and distribution. The 2-D ozone model present in this paper for stratospheric ozone and its layer and depletion is shown to be robust, convenient, efficient, and executable for analyzing the complex ozone phenomena in the stratosphere. .

Numerical Models and Methods of Atmospheric Parameters Originating in the Formation of the Earth’s Climatic Cycle

Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in2/s for humidity, 2.993 in2/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .

Driving factors of CO_(2)emissions in South American countries:An application of Seemingly Unrelated Regression model

Carbon emissions have become a critical concern in the global effort to combat climate change,with each country or region contributing differently based on its economic structures,energy sources,and industrial activities.The factors influencing carbon emissions vary across countries and sectors.This study examined the factors influencing CO_(2)emissions in the 7 South American countries including Argentina,Brazil,Chile,Colombia,Ecuador,Peru,and Venezuela.We used the Seemingly Unrelated Regression(SUR)model to analyse the relationship of CO_(2)emissions with gross domestic product(GDP),renewable energy use,urbanization,industrialization,international tourism,agricultural productivity,and forest area based on data from 2000 to 2022.According to the SUR model,we found that GDP and industrialization had a moderate positive effect on CO_(2)emissions,whereas renewable energy use had a moderate negative effect on CO_(2)emissions.International tourism generally had a positive impact on CO_(2)emissions,while forest area tended to decrease CO_(2)emissions.Different variables had different effects on CO_(2)emissions in the 7 South American countries.In Argentina and Venezuela,GDP,international tourism,and agricultural productivity significantly affected CO_(2)emissions.In Colombia,GDP and international tourism had a negative impact on CO_(2)emissions.In Brazil,CO_(2)emissions were primarily driven by GDP,while in Chile,Ecuador,and Peru,international tourism had a negative effect on CO_(2)emissions.Overall,this study highlights the importance of country-specific strategies for reducing CO_(2)emissions and emphasizes the varying roles of these driving factors in shaping environmental quality in the 7 South American countries.

IFAM与24Model的对比研究

为完善和推动事故致因理论的发展,提高事故防控水平,在对信息流事故致因模型(IFAM)和事故致因2-4模型(24Model)理论基础、组成要素和分析过程对比研究的基础上,通过实例分析辨识二者之间的异同。研究结果表明:IFAM与24Model都有较强的理论基础,部分组成要素存在对应关系,但原因类别划分存在差异。IFAM以信息流和组织为研究对象,研究过程相对复杂,更适用于分析单起事故;24Model以组织为研究对象,事故原因模块通用性和逻辑性强,适用于分析单起或某类事故。在实际应用中,IFAM与24Model均可用于事故调查分析和事故分级定责,具有一定的理论和实践价值。IFAM通过信息流表征事故致因,直观描述组织外部原因因素,但对个体能力的深入研究欠缺;而24Model认为组织外部因素需要通过组织内部原因模块的欠缺体现,认为个体能力是引发事故的间接原因并进行细致分析,但对组织间相关关系的探究欠缺。研究结果可为事故预防工作提供新视角和理论支撑。