Comprehensive Risk Assessment of Sea Level Rise and Tropical Cyclones in Dongzhaigang Mangroves,China

Mangroves play a pivotal role in tropical and subtropical coastal ecosystem,yet they are highly vulnerable to the effects of climate change,particularly the accelerated global sea level rise(SLR)and stronger tropical cyclones(TCs).However,there is a lack of research addressing future simultaneous combined impacts of the slow-onset of SLR and rapid-onset of TCs on China's mangroves.In order to develop a comprehensive risk assessment method considering the superimposed effects of these two factors and analyze risk for mangroves in Dongzhaigang,Hainan Island,China,we used observational and climate model data to assess the risks to mangroves under low,intermediate,and very high greenhouse gas(GHG)emission scenarios(such as SSP1-2.6,SSP2-4.5,and SSP5-8.5)in 2030,2050,and 2100,and compiled a risk assessment scheme for mangroves in Dongzhaigang,China.The results showed that the combined risks from SLR and TCs will continue to rise;however,SLRs will increase in intensity,and TCs will decrease.The comprehensive risk of the Dongzhaigang mangroves posed by climate change will remain low under SSP1-2.6 and SSP2-4.5 scenarios by 2030,but it will increase substantially by 2100.While under SSP5-8.5 scenario,the risks to mangroves in Dongzhaigang are projected to increase considerably by 2050,and approximately 68.8%of mangroves will be at very high risk by 2100.The risk to the Dongzhaigang mangroves is not only influenced by the hazards but also closely linked to their exposure and vulnerability.We therefore propose climate resilience developmental responses for mangroves to address the effects of climate change.This study for the combined impact of TCs and SLR on mangroves in Dongzhaigang,China can enrich the method system of mangrove risk assessment and provide references for scientific management.

Application of Feature, Event, and Process Methods to Leakage Scenario Development for Offshore CO_(2) Geological Storage

Offshore carbon dioxide(CO_(2)) geological storage(OCGS) represents a significant strategy for addressing climate change by curtailing greenhouse gas emissions. Nonetheless, the risk of CO_(2) leakage poses a substantial concern associated with this technology. This study introduces an innovative approach for establishing OCGS leakage scenarios, involving four pivotal stages, namely, interactive matrix establishment, risk matrix evaluation, cause–effect analysis, and scenario development, which has been implemented in the Pearl River Estuary Basin in China. The initial phase encompassed the establishment of an interaction matrix for OCGS systems based on features, events, and processes. Subsequent risk matrix evaluation and cause–effect analysis identified key system components, specifically CO_(2) injection and faults/features. Building upon this analysis, two leakage risk scenarios were successfully developed, accompanied by the corresponding mitigation measures. In addition, this study introduces the application of scenario development to risk assessment, including scenario numerical simulation and quantitative assessment. Overall, this research positively contributes to the sustainable development and safe operation of OCGS projects and holds potential for further refinement and broader application to diverse geographical environments and project requirements. This comprehensive study provides valuable insights into the establishment of OCGS leakage scenarios and demonstrates their practical application to risk assessment, laying the foundation for promoting the sustainable development and safe operation of ocean CO_(2) geological storage projects while proposing possibilities for future improvements and broader applications to different contexts.

Risk Assessment Mapping of Landscape Development Based on Ecological Service and Goods in Malaysia Lowland Tropical Rainforest

Amongst the impacts of converting forest to agricultural activities are soil erosion and degradation of ecology service values and goods （ESVG）. The soil erosion can be seen as on-site impacts, such as the problems of decreasing soil fertility and also its off-site impact such as the problems of sedimentation of the nearby rivers, whilst the degradation of ESVG are more holistie in nature, These impacts can be devastating in environmental, biological, and socio-economic manners. This paper reports the study undertaken on the impacts of agricultural development in 0.8 million ha of forest dominated landscape in Pasoh Forest Region （PFR）, Malaysia, within period of 8 years from 1995 to 2003. Three folds of impacts on agricultural development examined and analysed, are： （i） relationship of total soil loss and changes in land use pattern, （ii） mapping trends of ESVG for PFR in 1995 and 2003, and （iii） risk assessment of ESVG based on simulation of converting 339,630 ha of primary forest into mass-scale oil palm plantation. Results of this study indicated that although only minor changes of about 1464 ha （about 0.2% of PFR） of primary forest was converted to agricultural activities, it have significantly increased the total soil loss from 59 to 69 million ton/ha/yr. The mean rate of soil is loss for PFR is 0.8 mil ton/ha/yr and if translated into ESVG term, the soil loss costs about US$ 4.8mil/yr. However, majority of the soil loss within all land use classes are within range of very low-low risk categories （〈10 ton/ha/yr）. ESVG for PFR were costing US$ 179 millions in 1995, declined to US$114 millions in 2003 due to 0.2% reduction of forested land. The ESVG of converting 339,630 ha primary forest into mass plantation cost less than original forest within period of 20 years examined; the 20th year of conversion, the ESVG of plantation and to-remain as forest cost US$ 963 and US$ 575 millions, respectively. However, this difference is only marginal when full attributes of ESVG are considered.

Data-Driven Model for Risk Assessment of Cable Fire in Utility Tunnels Using Evidential Reasoning Approach

Cable fire is one of the most important events for operation and maintenance(O&M)safety in underground utility tunnels(UUTs).Since there are limited studies about cable fire risk assessment,a comprehensive assessment model is proposed to evaluate the cable fire risk in different UUT sections and improve O&M efficiency.Considering the uncertainties in the risk assessment,an evidential reasoning(ER)approach is used to combine quantitative sensor data and qualitative expert judgments.Meanwhile,a data transformation technique is contributed to transform continuous data into a five-grade distributed assessment.Then,a case study demonstrates how the model and the ER approach are established.The results show that in Shenzhen,China,the cable fire risk in District 8,B Road is the lowest,while more resources should be paid in District 3,C Road and District 25,C Road,which are selected as comparative roads.Based on the model,a data-driven O&M process is proposed to improve the O&M effectiveness,compared with traditional methods.This study contributes an effective ER-based cable fire evaluation model to improve the O&M efficiency of cable fire in UUTs.

New development in risk assessment of genotoxic carcinogens in foods

The no-observed-effect level (NOEL) in a study of carcinogenicity for compounds that are both genotoxic and carcinogenic represents the limit of detection in that bioassay, rather than an estimate of a possible threshold. Therefore, for those genotoxic and carcinogenic contaminants (e.g. acrylamides, PAHs, etc.) in foods it is not possible to develop health-based guidance values (e.g. ADI or PTWI) using the traditional NOEL and safety/uncertainty factors.

Need for education of psychiatric evaluation of offenders with mental disorders:A questionnaire survey for Japanese designated psychiatrists

BACKGROUND The management of offenders with mental disorders has been a significant concern in forensic psychiatry.In Japan,the introduction of the Medical Treatment and Supervision Act in 2005 addressed the issue.However,numerous psychiatric patients at risk of violence still find themselves subject to the administrative involuntary hospitalization(AIH)scheme,which lacks clarity and updated standards.AIM To explore current as well as optimized learning strategies for risk assessment in AIH decision making.METHODS We conducted a questionnaire survey among designated psychiatrists to explore their experiences and expectations regarding training methods for psychiatric assessments of offenders with mental disorders.RESULTS The findings of this study’s survey suggest a prevalent reliance on traditional learning approaches such as oral education and on-the-job training.CONCLUSION This underscores the pressing need for structured training protocols in AIH consultations.Moreover,feedback derived from inpatient treatment experiences is identified as a crucial element for enhancing risk assessment skills.

Risk Assessment of Multi‑Hazards in Hangzhou:A Socioeconomic and Risk Mapping Approach Using the CatBoost‑SHAP Model

As the global push for sustainable urban development progresses, this study, set against the backdrop of Hangzhou City,one of China's megacities, addressed the conflict between urban expansion and the occurrence of urban geological hazards.Focusing on the predominant geological hazards troubling Hangzhou-urban road collapse, land subsidence, and karst collapse-we introduced a Categorical Boosting-SHapley Additive exPlanations(CatBoost-SHAP) model. This model not only demonstrates strong performance in predicting the selected typical urban hazards, with area under the curve(AUC) values reaching 0.92, 0.92, and 0.94, respectively, but also, through the incorporation of the explainable model SHAP, visually presents the prediction process, the interrelations between evaluation factors, and the weight of each factor. Additionally, the study undertook a multi-hazard evaluation, producing a susceptibility zoning map for multiple hazards, while performing tailored analysis by integrating economic and population density factors of Hangzhou. This research enables urban decision makers to transcend the “black box” limitations of machine learning, facilitating informed decision making through strategic resource allocation and scheduling based on economic and demographic factors of the study area. This approach holds the potential to offer valuable insights for the sustainable development of cities worldwide.

Population amount risk assessment of extreme precipitation-induced landslides based on integrated machine learning model and scenario simulation

In this study,the future landslide population amount risk(LPAR)is assessed based on integrated machine learning models(MLMs)and scenario simulation techniques in Shuicheng County,China.Firstly,multiple MLMs were selected and hyperparameters were optimized,and the generated 11 models were crossintegrated to select the best model to calculate landslide susceptibility;by calculating precipitation for different extreme precipitation recurrence periods and combining the susceptibility results to assess the landslide hazard.Using the town as the basic unit,the exposure and vulnerability of the future landslide population under different Shared Socioeconomic Pathways(SSPs)scenarios in each town were assessed,and then combined with the hazard to estimate the LPAR in 2050.The results showed that the integrated model with the optimized random forest model as the combination strategy had the best comprehensive performance in susceptibility assessment.The distribution of hazard classes is similar to susceptibility,and with an increase in precipitation,the low-hazard area and high-hazard decrease and shift to medium-hazard and very high-hazard classes.The high-risk areas for future landslide populations in Shuicheng County are mainly concentrated in the three southwestern towns with high vulnerability,whereas the northern towns of Baohua and Qinglin are at the lowest risk class.The LPAR increased with the intensity of extreme precipitation.The LPAR differs significantly among the SSPs scenarios,with the lowest in the“fossil-fueled development(SSP5)”scenario and the highest in the“regional rivalry(SSP3)”scenario.In summary,the landslide susceptibility model based on integrated machine learning proposed in this study has a high predictive capability.The results of future LPAR assessment can provide theoretical guidance for relevant departments to cope with future socioeconomic development challenges and make corresponding disaster prevention and mitigation plans to prevent landslide risks from a developmental perspective.

基于故障树和贝叶斯网络的管廊运维风险评估

城市地下综合管廊在运维过程中事故时有发生,为了量化管廊运维风险并分析关键风险因素,提出一种基于故障树和模糊贝叶斯网络的城市地下综合管廊运维风险评估方法。在综合考虑管廊风险因素的基础上构建故障树模型,将其映射为贝叶斯网络。基于ALARP准则划分风险因素状态等级,根据模糊数和模糊子集计算底事件的发生概率,利用最大似然估计法求解中间事件的条件概率,构建管廊运维风险贝叶斯网络模型,精准评估城市地下综合管廊运维风险。结果表明:所评估的管廊运维过程风险等级为High的概率为28%,接近30%的风险阈值,因此需要及时对管廊风险进行管控。该方法能够科学、合理地评价风险水平并确定关键因素,可为管廊运维安全保障和管理提供参考。

ICU患者暴露性角膜炎风险评估量表的编制及信效度检验

目的编制ICU患者暴露性角膜炎风险评估量表,并检验其信度和效度。方法基于循证系统查阅文献编制量表初始条目池;通过2轮德尔菲专家函询,形成初始版量表;采用方便抽样法选取298例ICU患者,采用暴露性角膜炎风险评估量表进行调查,对量表信效度进行检验,并绘制受试者工作特征曲线确定最佳临界值。结果ICU患者暴露性角膜炎风险评估量表包括3个维度、12个条目;2轮函询专家积极系数分别为100%和80.95%,权威系数为0.892、0.888,肯德尔和谐系数为0.364和0.492;量表整体的Cronbach′sα系数为0.834,折半信度为0.795,评定者间信度0.841,内容效度为0.917;最佳临界值为8.5分,受试者工作特征曲线下面积为0.925。结论ICU患者暴露性角膜炎风险评估量具有良好的信效度,可用于ICU患者暴露性角膜炎的风险评估。

郑州市西部山地丘陵区地质灾害发育特征及危险性评价

郑州市西部山地丘陵区地质环境条件复杂,崩塌、滑坡及泥石流等地质灾害频发,尤其是2021年“7·20”特大暴雨引发了大量地质灾害。地质灾害危险性评价主要采用单一方法进行,存在评价准确性略低等问题。通过对研究区地质环境背景、地质灾害分布特征的分析研究,选取坡度、地貌、工程地质岩组、高程、距断裂距离、距河流距离、24小时最大降雨量和人类工程活动强度8个评价因子,采用加权信息量法,对研究区进行地质灾害危险性评价。结果表明:低、中、高危险区面积分别为1387.14 km^(2)、1803.18 km^(2)、1066.47 km^(2),分别占总面积的32.59%、42.36%、25.05%,地质灾害点的空间分布与地质灾害危险性评价结果基本一致,利用受试者工作特征(ROC)曲线检验评价结果合理,研究结论可为郑州市西部山地丘陵区地质灾害防治提供准确的依据。

市县国土空间开发风险评估技术——以湖南省常德市为例

根据国土空间规划编制的需要,将国土空间开发风险定义为“一定区域内由于国土空间开发不当导致不理想事件发生的可能性和后果”,将国土空间开发风险评估定义为“在国土空间开发可能导致的风险事件发生之前或之后,分析该风险事件发生的可能性及可能造成的影响,并在国土空间规划中给出避免或减缓的措施”。技术流程整体上分为风险识别、提出减缓措施2个部分。风险识别方面,首先划分评估单元,然后根据评估单元典型特征构建不同类型国土空间开发风险评估的指标体系。提出减缓措施方面,根据风险情况提出风险减缓策略,并纳入国土空间规划。以湖南省常德市为例给出了生态安全风险、粮食安全风险、水安全风险、自然灾害风险(洪涝灾害和地质灾害)评估的技术方法。结果显示,该技术方法可以在空间上充分反映研究区在国土空间开发保护利用中存在的问题和面临的风险,并能够指导规划编制。

妊娠相关静脉血栓风险评估量表的编制及信效度检验

目的:编制适合我国孕产妇妊娠相关静脉血栓风险的评估量表,并验证其信效度。方法:通过文献研究法和2轮专家函询形成预试量表。选取202名孕产妇进行调查,对预试量表进行项目分析和信效度检验。结果:妊娠相关静脉血栓风险评估量表包含非手术相关因素、血液相关因素、手术相关因素、妊娠相关因素、人工辅助生殖5个维度,共16个条目,探索性因子分析共提取6个公因子,累计方差贡献率为60.832%,受试者工作特征(ROC)曲线下面积为0.836,总量表的Cronbach’s α系数为0.852,2周后重测信度为0.920。结论:编制的妊娠相关静脉血栓风险评估量表具有良好的信效度,可有效评估孕产妇妊娠相关静脉血栓的风险。

洪涝风险与发展潜力视角下村庄居民点布局优化——以福建省长汀县为例

全球气候变化加剧和城镇化快速推进使得洪涝灾害发生频率和破坏性显著升高,为应对洪涝灾害利用风险评估指导村庄居民点布局优化,以福建省长汀县为例,运用模糊综合评价方法划定洪涝风险等级区,通过双重目标决策法对村庄灾害风险和发展潜力进行综合评价,并基于引力模型确定村庄迁移方案。结果表明,长汀县洪涝灾害高风险区域主要分布在以汀州镇与大同镇为主体的集中建设区及以部分村庄居民点,针对高风险村庄居民点,以“避灾”为导向提出了村庄迁移合并方案,实现了村庄居民点布局的适灾和减灾优化调整。对于区域防控洪涝灾害、减少灾害损失具有重要作用,对山地村庄空间防灾减灾规划实施有较强指导意义。

人工智能发展和安全并重的法治探究——以人形机器人为例

基于“大数据+高算力+强算法”的人形机器人,能够实现连贯高效的人—机—环境智能交互,可服务特种领域需求,助力智能制造,成为人类生活助手和情感伴侣。尽管人形机器人存在功能安全、网络安全、个人信息安全、数据安全、国家安全、违法“代理”、侵权、伦理等多种风险,但如果过度追求安全,就会扼杀创新而阻碍发展。发展是安全的基础,安全是发展的条件,应实现人工智能发展和安全并重。通过理性实施包容审慎监管,推动人形机器人在发展中规范、在规范中发展。科学合理地开展安全风险评估,将人形机器人风险控制在可接受的水平。完善数据安全认证、个人信息保护认证等第三方声誉评价机制,并分级分类推动人形机器人标准制定。应合理配置相关主体的责任,避免人形机器人的过度拟人化,防止陷入“人形机器人陷阱”。通过完善的伦理规范约束人工智能研发者,并为人形机器人“加载”道德,使其对人和环境友好。

跨境数据流动规制的模式差异、协调路径与中国方案

截至目前,全球并未形成统一的数据流动规则体系,数据跨境流动规则主要分为美国模式、欧盟模式和中国模式。由于主要数字经济体在数据跨境流动与数据安全保护之间的关注焦点不同,以全球主义或国际软法为方法推进高标准的全球统一数据流动规则体系构建的方案,在短期内难以实现。作为数字经济大国,我国应转变对商业数据跨境流动相对保守的态度。我国可以全面与进步跨太平洋伙伴关系协定(CPTPP)“电子商务”章节为主要内容,探索通过与韩国、日本及欧洲、东南亚国家等缔结专门的数字贸易协定,推动跨境流动规则体系的建设。我国还应加快对区域全面经济伙伴关系协定(RCEP)等经贸协定“电子商务”规则的国内转化立法,特别是积极引入数据跨境流动的风险评估理念与制度。

鸽粪农业利用潜力及其重金属风险评价

为了解鸽粪组分及其农业利用过程中重金属的潜在生态风险,本研究采集了广东省肉鸽养殖基地的鸽粪样品,检测分析了鸽粪中Cu、Zn、Cd、Cr、Ni、Pb、Hg、As 8种重金属含量以及全氮、全磷、全钾含量,采用单因子污染指数法与综合污染指数法评价了鸽粪重金属污染程度,同时,根据水稻所需全氮含量分析鸽粪安全农用年限,并通过Hakanson潜在生态污染评价法进行验算。结果表明:对比德国腐熟肥料标准,鸽粪中Cu、Zn含量超标,样品超标率分别为18.18%和36.36%,总超标率为45.45%。单因子污染指数表明鸽粪重金属Zn、Cu、Ni分别有36.36%、18.18%、18.18%的样品处于污染水平,其余重金属含量均在《有机肥料》(NY/T525-2021)的限量范围内。内梅罗综合污染指数表明,处于警示及以上污染水平的点位主要受Cu、Zn污染。在不考虑重金属流失情况下,广东省水稻种植中连续施用鸽粪10 a无重金属污染风险,而在水田旱作系统中,以作物所需全磷量为施肥指标的情况下,鸽粪安全农用年限可达50 a。研究表明,鸽粪农用过程中会使重金属在农田土壤中累积,引起重金属污染,应加强鸽粪无害化处理及安全利用等技术研究。

基于EFDC模型的靖江河道多码头开发段溢油事故综合污染风险分析

基于环境流体动力学模型EFDC模拟了长江靖江开发段6个码头溢油事故下油膜漂移路径,提出了溢油污染风险评估方法,计算了多码头溢油事故的污染风险指数分布及其对保护区的综合污染风险指数。结果表明:码头位置和周围流场影响油膜的漂移路径;急流区溢油事故产生的油膜峰值迁移速度快,影响距离长,而缓流区溢油事故产生的油膜聚集程度高,影响时间长;多码头溢油事故产生的污染风险主要分布在各油膜路径的叠加区域,在开发段中部至下游末端形成强等级污染风险带,综合污染风险指数约为1.6;风险带主要影响W1保护区,应在高风险区域提前采取应急防范措施。

基于概率神经网络和层次分析法的硐室群施工风险评估

地下硐室群施工风险研究尚处于起步阶段,为快速准确评判风险因素,预防施工安全事故,利用概率神经网络(PNN)和层次分析法(AHP)建立风险评估模型,并研发硐室群施工风险评估软件。通过统计分析硐室群施工风险因素,设置工程地质、自然、设计施工和管理4个一级风险因素,23个风险控制指标,建立针对硐室群施工的风险指标体系。收集典型样本数据后,基于PNN对施工风险等级进行评判,同时采用AHP定量分析风险因素权重,迅速捕捉风险点,采取风险控制措施并优化施工方案。运用研发软件对重庆轨道交通18号线歇台子站硐室群施工进行风险评价,得到风险概率等级为Ⅳ,在施工过程中需要重点监测和控制地下水、围岩等级和支护及时性等带来的影响,实例评价结果与现场情况相吻合,验证了该评估软件的有效性和实用性。研究表明:针对硐室群施工建立的指标体系和评估方法能有效预测风险级别,实时指导施工过程,确保地下硐室群施工安全。

综合管廊电力舱电缆火灾研究进展

综合管廊的电力运营输送安全是韧性城市的重要保证措施之一。在分析电力舱火灾成因、火灾特点及消防安全特殊性的基础上,归纳了综合管廊电力舱电缆火灾的关键科学问题。从电缆火灾的燃烧动力学机理、风险评估以及预警防护3个方面,综述了管廊电力舱火灾安全的研究成果和总体进展。结果表明:在电力舱电缆火灾的基础理论和实践应用上已经取得了较为系统的研究成果,但关于复杂廊体结构因素对火灾的影响研究还缺乏深入的探讨。结合管廊行业实际工程的发展,指出长通风区间电力舱电缆火灾的蔓延及联动防治是未来综合管廊消防系统研究的一个重要方向。