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Mercury pollution in emerging industrial zones and surrounding areas, especially in industrial concentration areas, has attracted much attention. So as to clarify the characteristics of Hg in the environment in China's small and medium-sized industrial emerging and surrounding areas, central urban area of Gongzhuling, a traditional agricultural town with a high degree of industrialization in northeast Changchun industrial base, is taken as the scope. Geological accumulation trin (Igeo) was used to study the degree of soil mercury contamination in Gongzhuling area, latent Er (ecological risk) trin was used to appraise the Er of soil Hg in the study area, and non-carcinogenic risk assessment of mercury in soil using human exposure risk assessment model. The results showed that 34% of soil samples had higher Hg content than the background value of the province's soil (0.04 mg kg-1). The Igeo results showed that Hg pollution rate of soil in study area was 9% (index >0). In conclusion, the level of soil Hg pollution in Gongzhuling area was low, and the pollution area is mainly concentrated in the northwestern part of the study range. The highest and lowest Er values of soil Hg from the study sample were 2.23 and 214.83, and 24% of the samples had Er > 40, that means they pose a moderate or higher potential ecological risk, and most of these points are located in the northeast of the study range. The main route of human exposure to Hg is oral ingestion. The HQ (non-carcinogenic risk index) and HI (total non-carcinogenic risk value) of soil mercury were both much less than 1, it indicates that the present level of soil Hg in the study range does not pose a threat to local adult health for the time being. This study provides reference for other urban pollution risk assessment, and further defines the direction of future work. [ABSTRACT FROM AUTHOR]

Due to the complex hydrogeological conditions and water hazards in coal mines, there are multiple indexes, complexities, incompatibilities, and uncertainty issues in the risk evaluation process of coal-mine water hazards. To accurately evaluate the risk of coal-mine water hazards, a comprehensive evaluation method based on extension theory, game theory, and Dempster–Shafer (DS) evidence theory is proposed. Firstly, a hierarchical water-hazard risk-evaluation index system is established, and then matter-element theory in extension theory is used to establish a matter-element model for coal-mine water-hazard risk. The membership relationship between various evaluation indexes and risk grades of coal-mine water-hazard risk is quantified using correlation functions of extension set theory, and the quantitative results are normalized to obtain basic belief assignments (BBAs) of risk grades for each index. Then, the subjective weights of evaluation indexes are calculated using the order relation analysis (G1) method, and the objective weights of evaluation indexes are calculated using the entropy weight (EW) method. The improved combination weighting method of game theory (ICWMGT) is introduced to determine the combination weight of each evaluation index, which is used to correct the BBAs of risk grades for each index. Finally, the fusion of DS evidence theory based on matrix analysis is used to fuse BBAs, and the rating with the highest belief fusion result is taken as the final evaluation result. The evaluation model was applied to the water-hazard risk evaluation of Sangbei Coal Mine, the evaluation result was of II grade water-hazard risk, and it was in line with the actual engineering situation. The evaluation result was compared with the evaluation results of three methods, namely the expert scoring method, the fuzzy comprehensive evaluation method, and the extension method. The scientificity and reliability of the method adopted in this paper were verified through this method. At the same time, based on the evaluation results, in-depth data mining was conducted on the risk indexes of coal-mine water hazards, and it was mainly found that 11 secondary indexes are the focus of coal-mine water-hazard risk prevention and control, among which seven indexes are the primary starting point for coal-mine water-hazard risk prevention and control. The groundwater index in particular has the most prominent impact. These results can provide a theoretical basis and scientific guidance for the specific water-hazard prevention and control work of coal mines. [ABSTRACT FROM AUTHOR]

Copyright of Petroleum Refinery Engineering is the property of Petroleum Refinery Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To explore the heavy metal pollution characteristics and risk in Shaanxi typical mining soil and edible forest products, through sample collection in Huazhou District Weinan City, Zhashui County, Fengxian County mining area of soil and edible forestry products and analysis of the As, Hg, Pb, Cd, Cr, Cu content, using single factor pollution index method, Nemero comprehensive pollution index method, soil and agricultural products comprehensive quality index method, heavy metal pollution of soil and edible forest products was evaluated. The results showed that the accumulation levels of As, Hg, Pb, Cd, Cr and Cu occurred in the soil in the study area;different degrees of Cr and Cu accumulation, two samples of Pb content exceeded the standard;the single pollution index indicated that Cd was the main pollutant in the soil of the study area of Feng County, Cr and Cu were the main soil pollutants in Zhashui County;the soil in Fengxian County and Zhashui sampling area was slightly polluted (quality grade Ⅲ), the soil in Huazhou sampling area was still clean state (quality grade Ⅱ). The comprehensive quality effect index indicated that, soil in Fengxian County Presents slight pollution (sub-Ⅱ), Huazhou District presents mild pollution (sub-Ⅲ), Zhashui County was heavily polluted (sub-V). Heavy metal pollution occurs in the soil of Fengxian County, Huazhou county and Zhashui research area, and remediation measures should be taken in time to reduce the pollution of heavy metals in soil and edible forest products. [ABSTRACT FROM AUTHOR]

Most fisheries are conducted without any scientific knowledge about the size and productivity of the stocks that support them. This navigation in the dark in most fisheries is a major obstacle in making them sustainable sources of nutrition for people in general and income for fishers and other economic actors along supply chains. Fisheries that have not been assessed generally are data‐intermediate and data‐poor, the latter usually having annual time series of landings as the single piece of data available. A major effort in the last two decades has been directed toward developing 'catch‐only' stock assessment methods, although some of these methods have been tested and found deficient. Here we provide a novel approach to using annual landing time series as the single source of data to qualitatively judge the condition of un‐assessed stocks using frequentist cumulative probability ogives, both in terms of stock biomass and fishing mortality. A meta‐analysis of the FishSource database allowed us to infer statistical patterns from hundreds of assessed fisheries and thousands of annual landings, biomass, and fishing mortality observations. Four stock‐management types were considered separately in the analysis: short‐lived and others (mid‐ to long‐lived) stocks, controlled or not controlled by catch limits. Obtained cumulative probability ogives provide clear evaluations of stock biomass and fishing mortality trends in all four stock‐management types, leading to actionable information on probable current status and future trends. Using these probability ogives, we developed decision trees that lead to qualitative scores on the exploitation status of un‐assessed stocks. [ABSTRACT FROM AUTHOR]

The Fukushima accident showed that the safety of multiple nuclear power plants (NPPs) at the same site could be jeopardized simultaneously. Since then, many studies have focused on developing strategies to prevent the spread of multi-unit accidents, with numerous countries establishing strategies to use mobile equipment. However, mobile equipment strategies are inherently accompanied by a high degree of uncertainty regarding operation success and duration because multiple organizations and personnel interact in various ways during multi-unit accident situations. Furthermore, supplementing current fixed equipment with additional mobile equipment requires extra resources. Therefore, cross-tie strategies that use currently installed fixed equipment can provide additional means to manage site risk with relatively few additional costs. This study proposes a multi-unit probabilistic safety assessment–based risk evaluation framework for utilizing cross-tie systems in NPPs and a modeling methodology to quantify the effectiveness of the cross-tie strategies. A case study was conducted to evaluate the risk reduction from using cross-tie strategies for emergency diesel generators and alternate AC diesel generators, which are power systems utilized in multi-unit loss of offsite power initiating events. It is expected that the developed framework and methodology can be utilized for other types of cross-tie strategies as well.

Advanced driver-assistance systems (ADASs), such as forward collision warning (FCW), are widely used and, in some countries, have been made mandatory for commercial vehicles. In practical applications, however, FCW systems produce many false alarms. Using scenario and driving behavior data collected from naturalistic driving study data of trucks, a variable threshold evaluation method was proposed to determine the factors correlating with false alarms. A total of 450 collision avoidance events were divided based on driving characteristics into three groups with k-means clustering. Responsibility-sensitive safety (RSS) model’s parameters were calibrated with the driving behavior characteristics and scenarios to evaluate the truck FCW system’s alarm accuracy. The evaluation of the results of truck FCW system based on RSS model found 47 false alarm alarms in the 450 events, a false alarm rate of 11.19%. When the following distance was close (20 m), the false alarm rate reached more than 30%. The minimum time to collision (TTC) in the close distance driving clusters (DCs) (5.81 s) was lower than that in long distance DCs (7.68 s and 9.46 s). Braking force in the low-speed DCs (deceleration at −0.16 g and −0.55 g) was lower than in high-speeded DC (deceleration = −1.21 g). The FCW system does not conform to the driver's reaction time and braking characteristics in different scenarios, and is the main reason for false alarms. This is more obviously reflected in low-speed short distance and high-speed long-distance scenarios.

Reviews the development process of the evaluation of water inrush risk from coal seam floor. Then the system of risk evaluation is put forward: indexes (establishment of index system), methods (selection of evaluation methods) and tools (innovation of handling tools), and the three steps are summarized. The study indicates that the development of index system is no longer the expansion of factor sets, but the treatment of non-linear relationship among factors, as well as the simplification of the two basic factor sets: mining and geological conditions. The existing methods are divided into three categories according to the logic of data processing. Based on the basic information of the data, the first type is to consider, sort, and synthesize three effects of the original data on the evaluated object: size, height, advantages and disadvantages, thus forming the evaluation result. The second type includes assessment, analysis, expansion and extension of the data, then the potential information is discovered to form the final result. The third type is to organize data sets with the same indexes, and find common information among data through related processing technology to obtain the result. The development direction of future evaluation methods covers two aspects. On the one hand, it aims to inherit the water inrush coefficient method and improve its poor performance in thick, extremely thick, and extremely thin water-resisting layers. On the other hand, it aims to innovate new methods of machine learning, then develop and apply them and their combined models. Besides,three goals that the processing tool needs to achieve are proposed:build a three-dimensional model of a mine,the realization of dynamic demonstration,positioning,quantitation and probability.The problems faced by the three parts are discussed and specific solutions are elaborated.On the basis of the above,the research prospect of all links of water inrush risk evoluation system from coal seam is globally clarified.

Translation abstract Safety assessment of buildings constructed in large, slow moving landslidesLarge slow moving landslides (SMLS) with typical deformation rates in a range of some mm to several dm per year and volumes of several 100,000 m3 to more than 100 mio. of m3 are common phenomenon in Alpin regions. Settlement areas, infrastructural buildings, bridges, tunnels, water reservoirs as well as protective structures are influenced in many cases by such SMLS. Whereas small landslides can be stabilized by support measures in a way that factors of safety acc. to standards can be proofed, this is often not possible for large landslides due to technical and economical reasons. In this paper, alternative verification procedures and assessment methods for building constructions in such SMLS and possible discrepancies to requirements of actual standards are discussed. Based on previous experience with practical examples, specific assessment criteria for an assessment of the use of settlement areas and structural facilities in SMLS are given depending on the change in the safety factor ΔFOS, the changes in movement rates, sensitivity analyses and the observation method. [ABSTRACT FROM AUTHOR]

The realization of a harmonious relationship between the natural environment and economic development has always been the unremitting pursuit of traditional mineral resource-based cities. With rich reserves of iron and coal ore resources, Laiwu has become an important steel production base in Shandong Province in China, after several decades of industrial development. However, some serious environmental problems have occurred with the quick development of local steel industries, with ground subsidence and consequent secondary disasters as the most representative ones. To better evaluate possible ground collapse risk, comprehensive approaches incorporating the common deformation monitoring with small-baseline subset (SBAS)-synthetic aperture radar interferometry (InSAR) technique, environmental factors analysis, and risk evaluation are designed here with ALOS PALSAR and Sentinel-1 SAR observations. A retrospect on the ground deformation process indicates that ground deformation has largely decreased by around 51.57% in area but increased on average by around −5.4 mm/year in magnitude over the observation period of Sentinel-1 (30 July 2015 to 22 August 2022), compared to that of ALOS PALSAR (17 January 2007 to 28 October 2010). To better reveal the potential triggering mechanism, environmental factors are also utilized and conjointly analyzed with the ground deformation time series. These analysis results indicate that the ground deformation signals are highly correlated with human industrial activities, such underground mining, and the operation of manual infrastructures (landfill, tailing pond, and so on). In addition, the evaluation demonstrates that the area with potential collapse risk (levels of medium, high, and extremely high) occupies around 8.19 km2, approximately 0.86% of the whole study region. This study sheds a bright light on the safety guarantee for the industrial operation and the ecologically friendly urban development of traditional steel production industrial cities in China. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to reveal the temporal and spatial evolution characteristics of mountain torrent disaster risk and its influencing mechanism on the Loess Plateau over the past 30 years, and to provide a scientific basis for the development of comprehensive prevention and control strategies for mountain torrent disasters on the Loess Plateau. [Methods] Based on the data of rainfall, vegetation cover, population density and so on, the risk assessment system of mountain torrent disaster was established. By integrating GIS and analytic hierarchy process (AHP), the mountain torrent disaster risks on the Loess Plateau in 1990 and 2020 were comprehensively evaluated based on the risk distribution map of each driving factor. [Results (1) The high-risk areas were mainly distributed in the southwest, south and east of the Loess Plateau. These areas had the characteristics of high rainfall intensity, dense population, developed economy and large cultivated land area. (2) During the period from 1990 to 2020, the overall risks of mountain torrent disasters on the Loess Plateau increased, showing that the areas with high risk expanded to its surroundings on the original basis, among which the southeast of Shanxi Province, the northwest of Qinghai Province and the northeast of Inner Mongolia were the most obvious. [Conclusion] The increased rainfall intensity, population density and GDP are the main driving factors on the increase of mountain torrent disaster risks in the past 30 years. It is necessary to continuously strengthen the prevention and control of mountain torrent disasters caused by extreme rainfall. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For the current coal spontaneous combustion fire risk evaluation method has the problems of single evaluation dimension, incomplete evaluation index and unreliable evaluation results. However, the coal spontaneous combustion fire risk evaluation can effectively guide coal mine fire prevention and control. Therefore, a multi-indicator quantitative risk evaluation method combining analytic hierarchy process (AHP) and linear interpolation for different periods of coal spontaneous combustion is proposed as a way to improve the rationality of coal spontaneous combustion fire risk evaluation. The continuous segmental evaluation model was established based on the factors that influence the three periods of coal spontaneous combustion (Latent Period, Self-heating Period and Combustion Period). The latent period evaluation model was established based on the fire-prone nature of coal, coal seam occurrence, mining technology, and fire prevention measures. The self-heating period evaluation model was established based on the degree of self-heating of coal, absolute CO generation, and Graham index. The combustion period, there was already a spontaneous combustion fire, directly set the fire risk score to 0. The score could fully reflect the level of coal spontaneous combustion fire risk. The higher the score, the relatively smaller the risk of coal spontaneous combustion, and vice versa, the relatively larger. According to this risk evaluation model, the risk of coal spontaneous combustion in the 2−2 coal seam of a coal mine in Shaanxi Province was evaluated. The result shows that the level of coal spontaneous combustion risk of 2−2 coal seam in this coal mine is in a safer state, and this result is consistent with the actual situation. The multi-indicator quantitative evaluation of different periods of coal spontaneous combustion effectively improves the accuracy of fire risk evaluation. Therefore, the evaluation model has certain theoretical guidance for the control of coal spontaneous combustion risk in coal mines. [ABSTRACT FROM AUTHOR]

The evaluation of typhoon disaster risk is a widely discussed global topic. Currently, the index system method has become a common approach for the evaluation of typhoon disaster risk. However, the indices within the system are calculated independently, and subjective human factors significantly influence the assignment of index weights. The existing studies lack purely quantitative assessment methods, which makes the studies less precise and more difficult for other researchers to replicate. To bridge this gap, this study employs emergy analysis methods based on thermodynamics to develop a typhoon disaster risk evaluation index system for China's coastal zone. Without the interference of weights and other human factors, the system contains various quantitative indices, including aggregate impelling energy, typhoon intensity emergy, adaptability emergy, the vulnerability index, and the integrated typhoon hazard index. Subsequently, these indices and socio-economic data were spatialized, and the evaluation of typhoon disaster risk was conducted at the city grid level in the coastal zone of China. The findings reveal that the high-risk areas for typhoon disasters in China are concentrated in prefecture-level cities along the southeast coast. The typhoon disaster risk index is higher in the southern region compared to the northern region, with a decreasing trend in the distribution of the integrated typhoon hazard index from coastal to inland areas. The aim of this study is to use a new quantitative evaluation method (emergy) to evaluate typhoon disasters. It also serves as a theoretical foundation and technical support for national and local governments in the formulation of policies for disaster prevention and reduction. [ABSTRACT FROM AUTHOR]

The green supply chain of agricultural products (GSCAP) is a key link for rural revitalization and sustainable development in China. However, it faces various risks from internal and external environments that threaten its performance and stability. This paper proposes a novel framework and system for identifying and evaluating the main risks in the GSCAP from the perspective of agricultural enterprises. The framework combines social network analysis (SNA) and an improved technique for order preference by similarity to an ideal solution (TOPSIS) method. SNA is used to analyze the correlations and influences among different types of risks, while the improved TOPSIS method is used to rank the risks of different GSCAPs and identify the key risks in each supply chain. The framework and system are verified by a case study of CDYBIT, a leading platform of food safety big data service in China. The results show that the supermarket supply chain has the highest risk, followed by the group catering supply chain, and the five‐star hotel supply chain has the lowest risk. The main risk factors for each supply chain are also discussed, and some suggestions for risk management are provided. This paper contributes to the literature by providing a comprehensive and systematic risk assessment framework and system for the GSCAP, which can help agricultural enterprises improve their risk awareness and response capabilities. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Inorganic Analytical Chemistry / Zhongguo Wuji Fenxi Huaxue is the property of Beijing Research Institute of Mining & Metallurgy Technology Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The ever-increasing needs of the working population have led to the development of various branches of industry, an increase in the number of employees, and a rise in the number of work-related accidents. The welder occupation is one of the most sought after occupations in Europe, according to the EURopean Employment Services (EURES) statistics. Taking into account the work system in which welders conduct their activity (uncomfortable working positions, splashes, high temperatures, mechanical factors, gases and fumes, magnetic fields due to electric current), the paper presents the risk factors identified for the welder occupation, based on the occupational injury and illness risk assessments. Following the analysis of 25 risk assessments, carried out by the assessment team that must include qualified evaluators, process specialists, the workers' representative, occupational health and safety responsible at various industrial economic agents, a total of 70 main risk factors of occupational accidents and diseases were identified for the welder occupation. Risk factors were classified according to four main work components: worker, workload, work environment, and means of production. To reflect the importance of the identified risk factor, the number of organizations that considered that the risk was likely to occur but also the possibility that the risk was above the acceptable limit, calculated using the National Institute for Research and Development for Labor Protection "Alexandru Darabont" (INCDPM) method, a method often used in Romania, was identified from the analyzed assessments. Finally, a prevention and protection plan was drawn up with regard to the risks identified for the welder occupation, the final aim of which was to respectively reduce the probability of occurrence with the severity of the risks identified. [ABSTRACT FROM AUTHOR]

The metaverse network economy is built on the blockchain protocol network and occurs in the metaverse virtual space by the virtual digital avatar. This is a series of economic activities that produce, exchange, distribute and consume digital products, and interact, integrate and promote with the real economy in real space. The network economic system of the metaverse is gradually formed in the process of adapting to the development of digital economy. While these products and services bring convenience, they are accompanied by more complex and diverse economic risks. Based on transformer serialization analysis, this paper proposes an analytical method of economic risk mechanism of metacosmic network to complete the evaluation of economic risk. First, this work proposes an improved transformer (ITransformer). The probabilistic sparse self-attention (PSSA) and self-attention distillation (SAD) are proposed to improve the performance. This can mine more discriminative temporal features. Secondly, this work designed a dual-stream ITransformer (DSIT) to evaluate the economic risks of the metaverse network via ITransformer. This can process the global and local features in the metaverse economic data with high performance. Finally, this work has performed massive experiments on dual-stream ITransformer pipeline. Experimental results verify the effectiveness and feasibility of DSIT. [ABSTRACT FROM AUTHOR]

In view of the problem that mountain tunnel construction is prone to collapse risk and disaster accidents, this paper proposes a fuzzy comprehensive evaluation method based on CRITIC and D-AHP combined weighting, which can effectively improve the accuracy of mountain tunnel collapse risk evaluation and reduce construction risks. This method combines the improved subjective weighting method D-number analytic hierarchy process and the more scientific and reasonable objective weighting method CRITIC method for combined weighting and uses game theory to optimize the weights, which improves its accuracy compared to traditional evaluation methods and makes up for the lack of subjective and objective weighting of a single evaluation method. The results show that the introduction of the D-number theory can reduce the impact of an uncertain environment on the evaluation results. The risk levels of the sample sections are all between three and four, which is consistent with the actual situation of the project, indicating that the evaluation model is feasible. [ABSTRACT FROM AUTHOR]

To steadily promote the reform of sales electricity prices, China has innovatively proposed to carry out grid enterprises' agency power purchase business (GEAPPB) as a transitional scheme for industrial and commercial users to enter the power market in the future. However, because the GEAPPB covers a wide range of users and involves complex business processes, the risks throughout the process of the GEAPPB will affect the organization and operation of the business. This paper proposes a GEAPPB risk assessment technique. First, a risk evaluation index system containing 10 indicators is designed based on the characteristics and development process of GEAPPB. Second, a risk assessment model based on the fuzzy full consistency method (FUCOM-F) and gray relational analysis (GRA)-improved MARCOS is constructed. Finally, seven grid enterprises in China are taken as examples to verify the validity and scientificity of the model. The results show that improving the accuracy of power forecasting, optimizing the agency power purchase strategy, and strengthening demand response management are the key schemes to reduce the risk of GEAPPB. Compared with the other three evaluation models, the proposed model has good applicability and effectiveness for the risk evaluation of GEAPPB. [ABSTRACT FROM AUTHOR]

As a geological barrier for high-level radioactive waste (HLW) disposal in China, granite is crucial for blocking nuclide migration into the biosphere. However, the high uncertainty associated with the 3D geological system, such as the stochastic discrete fracture networks in granite, significantly impedes practical safety assessments of HLW disposal. This study proposes a Monte Carlo simulation (MCS)-based simulation framework for evaluating the long-term barrier performance of nuclide migration in fractured rocks. Statistical data on fracture geometric parameters, on-site hydrogeological conditions, and relevant migration parameters are obtained from a research site in Northwestern China. The simulation models consider the migration of three key nuclides, Cs-135, Se-79, and Zr-93, in fractured granite, with mechanisms including adsorption, advection, diffusion, dispersion, and decay considered as factors. Subsequently, sixty MCS realizations are performed to conduct a sensitivity analysis using the open-source software OpenGeoSys-5 (OGS-5). The results reveal the maximum and minimum values of the nuclide breakthrough time Tt (12,000 and 3600 years, respectively) and the maximum and minimum values of the nuclide breakthrough concentration Cmax (4.26 × 10−4 mSv/a and 2.64 × 10−5 mSv/a, respectively). These significant differences underscore the significant effect of the uncertainty in the discrete fracture network model on long-term barrier performance. After the failure of the waste tank (1000 years), nuclides are estimated to reach the outlet boundary 6480 years later. The individual effective dose in the biosphere initially increases and then decreases, reaching a peak value of Cmax = 4.26 × 10−4 mSv/a around 350,000 years, which is below the critical dose of 0.01 mSv/a. These sensitivity analysis results concerning nuclide migration in discrete fractured granite can enhance the simulation and prediction accuracy for risk evaluation of HLW disposal. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the increasing demand for coal resources and the unreasonable arrangement of subsequent working faces, mining activities in isolated working faces are more likely to induce coal burst accidents. In this study, the minimum distance principle is utilized as the risk assessment indicator and the quantitative theory is introduced to evaluate coal burst risk in isolated working faces. Through a case study in 1,304 isolated working face of Yangcheng Coal Mine, the key factors affecting the risk of coal burst were identified, and a three-dimensional coal burst risk assessment model was constructed to evaluate the risk of the isolated working face. The results show that as the working face advances, the abutment pressure and elastic strain energy density in front of the working face increase to the peak value in a positive exponential relationship at first and then decrease to in situ stress, which presents an upward convex trend. Under different excavation steps, the concentration coefficient of the peak stress gradually increases. The influence range of the abutment pressure of the working face gradually increases. Compared with one-dimensional and two-dimensional evaluation functions, the three-dimensional function significantly improves the accuracy of risk assessment and successfully identifies strong coal and gas outburst risks. Additionally, the model not only enhances the precision of risk assessment but also quantifies the assessment parameters.

Microplastics (MPs) have attracted increasing attention worldwide owing to their widespread presence and potential risks to terrestrial and marine ecosystems. Estimating the pollution status and risk levels of MPs in coastal ecosystems is necessary; however, these are poorly understood in coastal megacities. Here, the abundance and characteristics of MPs in seawater, marine sediment, marine organisms, and beaches in the Shenzhen coastal ecosystems and land sources (river and sewage outfall) were simultaneously investigated, and the annual MPs load of rivers and MP-induced ecological risks were evaluated. The results showed that MPs pollution was prevalent in Shenzhen coastal ecosystems, with the average abundances of 2.40 ± 2.48 items/m3, 404.21 ± 431.48 items/kg, 1.66 ± 1.96 items/individual, and 1648.99 ± 1908.19 items/kg in seawater, marine sediment, marine organisms, and beach sands, respectively. The detected MPs were predominantly fibrous/granular, transparent/white, < 1 mm in size, and polyethylene terephthalate/polyethylene/polystyrene. The spatial distribution patterns of marine MPs are influenced mainly by anthropogenic activities and freshwater inflows (rivers and sewage outfalls). Pollution hotspots of MPs were identified in the Pearl River Estuary, which has a high population, gross domestic product, and river and wastewater discharge. Furthermore, the negative correlation between the abundance of MPs in seawater and salinity indicates that freshwater inflow carrying MPs to the sea is an important source of marine MPs pollution. It has been estimated that approximately 8320 billion MPs particles, weighing 274.55 tons, flow into the Shenzhen coast annually through river input. Based on the MPs polymer types and quantities, the ecological risk of MPs pollution in the Shenzhen coastal ecosystem is moderate and deserves further attention. These findings deepen the understanding of MPs pollution, sources, and ecological risks in the southern coastal region of China, and are helpful for employing effective management strategies to control marine MPs pollution.

This research investigates the ecological impacts of heavy metals in downstream river sediments with a focus on carbon emission efficiency in agriculture under the environmental regulation context. In this study, thirty sediment samples have been taken from the downstream region of the Shichuanhe River located in Xi'an, Shaanxi province, China, to analyze the availability of heavy metals. The results show that there are high ecological impacts in relation to the heavy metals and that impacts the carbon emission efficiency in agriculture directly. The analysis has also found the importance of significant environmental regulations in the management of such risks. This research has offered a unique angle on the relationship between heavy metal pollution and agricultural carbon release and has given important information on the improvement of environmental control measures. The implications highlight the need for the implementation of measures to enhance the policies that will help to prevent the ecological threats that are connected with heavy metals in the agricultural areas and, thus, improve the management of the environment.

Amidst the global antimicrobial resistance (AMR) crisis, antibiotic resistance has permeated even the most remote environments. To understand the dissemination and evolution of AMR in minimally impacted ecosystems, the resistome and mobilome of wetlands across the Qinghai-Tibetan Plateau and its marginal regions were scrutinized using metagenomic sequencing techniques. The composition of wetland microbiomes exhibits significant variability, with dominant phyla including Proteobacteria, Actinobacteria, Bacteroidetes, and Verrucomicrobia. Notably, a substantial abundance of Antibiotic Resistance Genes (ARGs) and Mobile Genetic Elements (MGEs) was detected, encompassing 17 ARG types, 132 ARG subtypes, and 5 types of MGEs (Insertion Sequences, Insertions Sequences, Genomic Islands, Transposons, and Integrative Conjugative Elements). No significant variance was observed in the prevalence of resistome and mobilome across different wetland types (i.e., the Yellow River, other rivers, lakes, and marshes) (R=-0.5882, P=0.607). The co-occurrence of 74 ARG subtypes and 22 MGEs was identified, underscoring the pivotal role of MGEs in shaping ARG pools within the Qinghai-Tibetan Plateau wetlands. Metagenomic binning and analysis of assembled genomes (MAGs) revealed that 93 out of 206 MAGs harbored ARGs (45.15 %). Predominantly, Burkholderiales, Pseudomonadales, and Enterobacterales were identified as the primary hosts of these ARGs, many of which represent novel species. Notably, a substantial proportion of ARG-carrying MAGs also contained MGEs, reaffirming the significance of MGEs in AMR dissemination. Furthermore, utilizing the arg_ranker framework for risk assessment unveiled severe contamination of high-risk ARGs across most plateau wetlands. Moreover, some prevalent human pathogens were identified as potential hosts for these high-risk ARGs, posing substantial transmission risks. This study aims to investigate the prevalence of resistome and mobilome in wetlands, along with evaluating the risk posed by high-risk ARGs. Such insights are crucial for informing environmental protection strategies and facilitating the management of water resources on the Qinghai-Tibetan Plateau.

Salatiga City Disperinnaker, a government agency focusing on industry and labor, has developed the Salatiga Job Vacancy Information System (SIOLGA) to streamline its operations. As the SIOLGA application has recently completed its development phase, there arises a necessity for robust risk management to anticipate potential threats and vulnerabilities. Employing ISO 31000 standards, the research aims to mitigate risks effectively. The ISO 31000 framework encompasses risk identification, analysis, evaluation, and treatment phases. Through this process, the study identified 18 potential risks within the SIOLGA application, categorized into three levels: high, medium, and low. Specifically, there are 5 high-level risks, 10 medium-level risks, and 3 low-level risks. By implementing rigorous risk management strategies, the expectation is for the SIOLGA application to operate more efficiently and optimally, fulfilling its intended objectives.

Abstract Background Aortic intramural hematoma (IMH) is one of the typical entities of acute aortic syndrome and probably accounts for 5–25% of all cases. The ulcer-like projections (ULP), which are described as a focal, blood-filled pouch protruding into the hematoma of the aortic wall, are regarded as one of the high-risk imaging features of IMH and may cause initial medical treatment failure and death. Case presentation We present a case report of an acute type B IMH patient with impaired renal function and newly developed ULP in the acute phase. The 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MR) was performed to evaluate the condition of aortic hematoma. The 18F-FDG focal uptake along the aortic wall of the hematoma was normal compared to the background (SUVmax 2.17; SUVSVC 1.6; TBR 1.35). We considered the IMH stable in such cases and opted for medical treatment and watchful observation. Six months after discharge, the patient’s recovery was satisfactory, and aortic remodeling was ideal. Conclusions The 18F-FDG PET/MR is a novel tool to evaluate the risk of IMH patients and thus provides information for therapy selection.

In order to reduce the risk of water shortage of Qinhe River Basin, this paper took Qinhe River Basin as the research object, estimated the blue and green water resources in Qinhe River Basin from 2010 to 2016 based on the output results of the SWAT model, calculated the blue and green water scarcity index through the blue and green water footprint and the blue and green water availability, and quantitatively evaluated the blue and green water shortage situation in Qinhe River Basin by dividing four risk levels of blue and green water shortage. The results show that: a) The average annual blue water resources in Qinhe River Basin are 910 million m³, accounting for 12.0% of the total water resources, and the average annual green water resources are 6.69 billion m³, accounting for 88.0% of the total water resources, and the main component of water resources in Qinhe River Basin is green water resources; b) Under the annual scale, the blue water shortage index of most molecular basins in Qinhe River is greater than 1.0, and the risk level of blue water shortage is relatively serious risk, especially in Jiaozuo City in the downstream area; c) Under the annual scale, the index of green water scarcity in each subbasin of Qinhe River shows some differences, the average annual green water shortage index in most sub-basins is in the range of 0.5-1.0, and the green water shortage faces moderate risk; On the whole, the risk level of green water shortage is lower than that of blue water shortage. Based on the analysis of water shortage indexes of blue water and green water, it put forward suggestions on reducing the water safety risk of Qinhe River Basin. [ABSTRACT FROM AUTHOR]

Predictions under interventions are estimates of what a person's risk of an outcome would be if they were to follow a particular treatment strategy, given their individual characteristics. Such predictions can give important input to medical decision-making. However, evaluating the predictive performance of interventional predictions is challenging. Standard ways of evaluating predictive performance do not apply when using observational data, because prediction under interventions involves obtaining predictions of the outcome under conditions that are different from those that are observed for a subset of individuals in the validation dataset. This work describes methods for evaluating counterfactual performance of predictions under interventions for time-to-event outcomes. This means we aim to assess how well predictions would match the validation data if all individuals had followed the treatment strategy under which predictions are made. We focus on counterfactual performance evaluation using longitudinal observational data, and under treatment strategies that involve sustaining a particular treatment regime over time. We introduce an estimation approach using artificial censoring and inverse probability weighting that involves creating a validation dataset mimicking the treatment strategy under which predictions are made. We extend measures of calibration, discrimination (c-index and cumulative/dynamic AUCt) and overall prediction error (Brier score) to allow assessment of counterfactual performance. The methods are evaluated using a simulation study, including scenarios in which the methods should detect poor performance. Applying our methods in the context of liver transplantation shows that our procedure allows quantification of the performance of predictions supporting crucial decisions on organ allocation. [ABSTRACT FROM AUTHOR]

Scientific experiments cover a wide range of fields—from basic to applied scientific research. Chemical experiments are the basis for cultivating chemical knowledge in scientific experiments and are an important way to cultivate scientific thinking and methods. However, due to the toxicity or flammability of the chemical substances in the experiments, hazardous events often lead to personal injuries and environmental damage. Exactly assessing risk factors and reducing the risk of hazards to protect the experimenters and ensure environmental safety are crucial in chemical experiments. However, while the traditional risk evaluation method cannot consider the weight of risk evaluation criteria, it also cannot effectively address problems through hierarchical analysis, as well as imprecise and ambiguous information inherent in human cognition. Therefore, this paper proposed an approach based on failure mode and effects analysis (FMEA) to assess the risk of chemical experiments in a fuzzy information environment. The approach combines the typical analytic hierarchy process (AHP), the risk priority number (RPN) of FMEA, and the intuitionistic fuzzy set (IFS) methods to evaluate risks associated with chemical experiments and consider the damage recovery in chemical experiments. This study applied the case of a university chemistry experiment, "preparation of hydrogels", to validate the reasonableness and correctness of the proposed approach and compare its numerical verification results with those from the typical RPN, the AHP-RPN, and the AHP-fuzzy risk priority number (AHP-FRPN) methods. The finding demonstrates that the proposed method can more effectively address risk evaluation problems in chemical experiments than the other methods. This result serves as an important reference for reducing chemical experiment risk occurrences. [ABSTRACT FROM AUTHOR]

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The complexity of the wharf components and the harshness of the offshore construction environment increase the safety risk of hazards, which has highlighted the importance and urgency of safety risk management in high-pile wharf constructions. This paper established a visualized digital construction safety risk model for high-pile wharf based on a so-called FAHP method (the combination of fuzzy comprehensive evaluation (FCE) and analytic hierarchy process (AHP) methods). The construction safety risk indicators were constructed as the target layer, the principle layer and the scheme layer, and then the corresponding safety risk assessment algorithm was established. The physical, functional and safety risk assessment parameters of the component in the BIM model were employed to the safety risk assessment algorithm, and the risk assessment level of each sub-process was subsequently classified. The case study indicated that the high-pile wharf construction project included five elements in principle layer and 15 risk indicators in the scheme layer. Moreover, it was demonstrated that the sub-processes with the highest construction risk level were steel pipe pile sinking in wharf construction and steel pipe pile, steel sheath-immersed pile sinking and embedded rock pile construction in approaches to bridge construction with a risk level of III. In this way, the quantitative visualization of the construction safety risk was effectively realized, which facilitates the safety risk management of construction sites and timely warning and response to unexpected safety accidents. [ABSTRACT FROM AUTHOR]

The highly dynamic nature of the real-world environment poses significant challenges for electric bus system operations (EBSOs), which are prone to serious accidents due to their complexity and a wide variety of risk factors. The accidents are often the result of ignoring the most serious risk sources because of a lack of comprehensive risk assessments. Therefore, this paper proposes an improved failure mode and effects analysis (FMEA) multicriteria group decision-making model to ensure the reliability and safety of EBSOs. First, an expert group is invited to evaluate the risk failure modes (FMs) of the EBSOs and transform them into a normal wiggly hesitant fuzzy set (NWHFS) form. Because the risk assessment process involves a large number of team members with different backgrounds, the experts are grouped based on scoring function values using the K-medoids clustering technique. Then, the evaluation values of the expert group are integrated using the normal hesitant fuzzy weighted geometric (NWHFWG) aggregation operator to obtain the final aggregation matrix, and the weights of the three criteria of occurrence (O), severity (S) and detection (D) are determined for each FM via the CCSD method. Finally, considering the cross-correlation between factors within the system, the relationships between FMs are analyzed, and their impact and importance are quantified using the gray correlation-based DEMATEL method, followed by the final ranking of the FMs using regret theory and the PROMETHEE II methodology to achieve a rational allocation of resources. The results are analyzed with sensitivity and comparative analyses to illustrate the superiority of the model. [ABSTRACT FROM AUTHOR]

Proper and systematic management of food industry failures can improve the quality of products and save a lot on the costs of organizations and people's health. One of the conventional methods for risk assessment is the Failure Modes and Effects Analysis (FMEA) which is often performed in a phase or stage. Compared to the combined methods, this method is less accurate due to similar priorities of failure in the evaluation and the lack of consideration of the interaction between risks. The current research has applied an integrated approach based on two techniques, FMEA and Fuzzy Cognitive Map (FCM), in a multi-stage manner to increase assessment accuracy and ranking of failures. By considering the risks of an industry in an uncertain environment and the causal relationships between failures, this approach can evaluate the industry's risks better than conventional methods. In the research method, the initial prioritization of failures by the FMEA method is used as the input of the multi-stage FCM. The cause-and-effect relationship between the failures is determined by experts and the functional records of the processes, and the FCM is prepared. Since no research evaluates the risks of the malting industry step by step and considers the causal relationships between the risks, the present study has improved risk evaluation in the malting industry by using a multi-stage FCM. The ranking results with the proposed hybrid approach and its comparison with the conventional methods showed that the rating became more accurate, and the multiple priorities were improved. Managers of the malt beverage industry can make effective investment decisions to reduce or better control the risks of this industry by using the results of applying the proposed approach. [ABSTRACT FROM AUTHOR]

Subsea immersed tunnels, have large construction scale, multiple structural types, high environmental requirements, and difficult construction management. There are many safety risks throughout the entire construction phase of the project. Taking the entire construction process of the Dalian Bay Immersed Tunnel Project as the research background, based on the characteristics of project construction, the HSE management method for engineering construction based on coupled matrix decomposition system was adopted to establish a risk assessment model for subsea immersed tunnel construction. The construction risk sources and factors were analyzed in detail and depth. From the perspective of system, a comprehensive evaluation index system for HSE risks in immersed tunnel engineering project was constructed, and the fuzzy comprehensive evaluation method was put forward by combining with fuzzy mathematics, which can comprehensively evaluate the HSE risk of immersed tunnel engineering project. Further explore the causes of HSE risks of subsea immersed tunnel engineering projects from the root, and gain a deeper understanding and grasp of the connotation of HSE risks in construction of subsea immersed tunnel engineering projects. So as to improve the construction management level of subsea tunnel projects. [ABSTRACT FROM AUTHOR]