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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]

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]

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]

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.)

Copyright of Journal of Anhui Agricultural Sciences is the property of Journal of Anhui Agricultural Sciences 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.)

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]

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 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]

Copyright of Research of Soil & Water Conservation is the property of Institute of Soil & Water Conservation, Chinese Academy of Sciences & Ministry of Water Resources 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 methodical advancement of the Energy Internet Marketing Service System across each network province in accordance with the blueprint, the company's marketing business development has ushered into the digital era, thereby necessitating elevated benchmarks for the system's security, reliability, cost-effectiveness, agility, and operational efficiency. Through an exhaustive scrutiny encompassing marketing business dynamics, technical architecture intricacies, and system operational modalities, the imperative arises for the replacement of the Oracle database and the advocacy for a feasibility study exploring the migration to a localized database system. Within this framework, the grid marketing service system's domestic database migration project confronts myriad challenges and risks. To ensure the seamless implementation of the project, this paper embarks from the vantage point of the project's specific context, amalgamating well-established risk management paradigms and methodologies. Leveraging the trapezoidal fuzzy number and material element topology computational model, potential risk factors are methodically discerned. Subsequently, the project's overall risk landscape is meticulously charted through the lens of this model, culminating in the formulation of targeted risk response strategies and a comprehensive feasibility assessment predicated upon the weighted ranking of risk factors. Ultimately, an array of corresponding risk response measures are delineated, spanning organizational, managerial, scheduling, and technical domains, thereby ensuring the seamless, steadfast, and efficacious implementation of the project, poised to furnish resolute support for its sustained operation post-migration. The research findings of this paper not only provide robust assurance for the feasibility of the migration project concerning the homegrown database system of the grid marketing service system but also offer invaluable theoretical insights and pragmatic wisdom poised to enrich the execution of analogous endeavors. [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]

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]

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]

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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

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]

Copyright of Water Conservancy Science & Techonlogy & Economy is the property of Water Conservancy Science & Technology & Economy 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.)

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]

Artisanal and Small-scale Gold Mining (ASGM) is a source of supply in many areas of the world, especially in developing countries. This is often carried out illegally using toxic substances such as mercury. Mercury, due to its chemical–physical properties and the transport factors involved between the different environmental matrices, can percolate through soil and from surface water to groundwater. The objective of this study was to conduct a human health risk assessment. For this purpose, a screening of mercury concentrations was carried out, collecting 67 water samples at selected points, and a risk assessment was performed applying both a deterministic and a probabilistic approach. A deterministic approach is a specific analysis based on determining the values of the risk quotient (HQ) and the risk index (HI) for each receptor category (adults and children) and scenario (residential and recreational) considered; a probabilistic approach is based on stochastic simulation techniques and the evaluation of the statistical quantities. There was found to be a discrepancy between the results provided by the two approaches, with the deterministic approach suggesting a more worrisome picture. However, in general, the results showed a greater exposure in the provinces of El Oro and Esmeraldas, and a greater vulnerability of child receptors. [ABSTRACT FROM AUTHOR]

Copyright of China Harbour Engineering is the property of Editorial Office of China Harbour Engineering 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.)

Copyright of World Regional Studies is the property of World Regional Studies 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.)

Fifty-one surface sediment samples from Dongshan Bay, China, were analyzed for heavy metals to evaluate their distribution, pollution status, and controlling factors. The enrichment factor is suggestive of the potential pollution status, ranging from minimal to moderate enrichment, for Pb, As, Zn, and Hg, with one site showing significant enrichment in As. A principal component analysis and the geochemical characteristics indicate that heavy metal concentrations are mainly influenced by clay minerals and Fe oxides, while Pb and Hg levels are also closely linked to the absorption of Mn oxides. Potential pollution is primarily from aquaculture (Cd, Zn, Cu, Pb) and industrial and domestic discharges. Approximately 270 tons of heavy metals were estimated to have been deposited in Dongshan Bay in 2021, highlighting the potential impact of human activities on coastal sediment quality. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Due to diminishing ice shelves in the Arctic, no doubt caused by climate change, previously unnavigable marine spaces are opening up, which in turn may provide new maritime routes. The shipping and maritime industry may capitalise on these routes more in the future as they provide shorter sailing times, and may assist with increasing oil and gas exploration and extraction in the region. However, increased maritime expansion in the Arctic comes with a number of unique risks and hazards for the insured and insurer. This opinion therefore seeks to discuss the implications of the multitude of risks that are associated with Arctic shipping from a marine insurance perspective and to highlight some of the gaps in existing regulatory frameworks. It is argued that marine insurers require improved data and risk management methodologies in order to better calculate the premiums of Hull & Machinery (H&M) and Protection & Indemnity (P&I) insurance policies for ships travelling through the Arctic. Until such time as these risks can be adequately assessed, evaluated, and managed by insurers; which of course is extremely difficult, due to the extreme environment, the unpredictability of climate change, a lack of key data, and the complexity of the various scenarios that can unfold in the Arctic environment, the practical viability of Arctic shipping remains doubtful. To date, insurers have paid out more in ship damage that has occurred in the Arctic than they have collected in premiums, which in itself is problematic. This situation may change in the future if Arctic shipping grows, and if it does the insurance market will no doubt, need to respond. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of 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.)

The psychological factors of experts play a special role in the process of decision-making, especially in some situations that experts are not completely rational. Traditional decision-making methods always just focus on the aggregation of positive preference information, which do not take the negative attribute information into account at the same time. The probabilistic dual hesitant fuzzy set (PDHFS) is one of the latest fuzzy sets, which can depict experts' positive and negative preference information with the corresponding probability at the same time. Therefore, to manage the applications with incomplete rationality and two opposite kinds of uncertain preference information, this paper considers the influence of psychological behavior on decision-making results and introduces an interactive method based on the prospect theory. Taking the advantages of PDHFSs in group decision-making problems, we propose the distance measure of PDHFSs, based on which an improved TODIM (TOmada deDecisão Iterativa Multicritério) method under the probabilistic dual hesitant fuzzy environment is also developed. Meanwhile, we provide the specific implementation process of the proposed method. The proposed improved TODIM is applied to the risk evaluation of Arctic geopolitics. We also make a comparison with the traditional aggregation method of PDHFSs. The difference among alternatives obtained by the proposed TODIM method with prospect theory is much greater than the traditional aggregation methods without prospect theory. This paper highlights the benefits and advantages of the proposed TODIM method that is developed based on the prospect theory and probabilistic dual hesitant fuzzy distance measure. [ABSTRACT FROM AUTHOR]

Copyright of Science Technology & Engineering is the property of Chinese Society of Technology Economics 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.)

Numerous countries are implementing building-integrated photovoltaic (BIPV) technology to enhance the energy performance of buildings, as new energy sources have attracted global interest. BIPV residential programs are an essential method to alleviate energy stress and promote energy transition in buildings; however, the high level of technology and capital investment required have hampered their marketization. Although certain obstacles have been examined by researchers, there remains a lack of studies concerning risk assessment in the context of the development of BIPV residential projects. Therefore, this study strives to develop a risk assessment model for the development of these projects. First, a risk evaluation index system is proposed by identifying and analyzing the risks associated with the development of BIPV residential projects, following the lines of risk identification–risk analysis–risk evaluation–risk management. Second, the DEMATEL-ANP-gray cluster analysis was utilized to construct the development risk assessment model. Finally, a case study demonstrates that the methodology proposed in this study can effectively solve the issues associated with correlating risk factors and the quantification of the magnitude of risks in the development of BIPV residential projects. This study will serve as a valuable reference for architect-urban developers and engineer contractors to formulate risk governance countermeasures for BIPV residential projects as it provides a framework for assessing the risk associated with their development. [ABSTRACT FROM AUTHOR]

The complexity and uncertainty of construction projects contribute to low efficiency in the construction industry. This research applied the Takt-time planning method to optimize the construction working process, and proposed a risk control framework based on Value at Risk (VaR) and Conditional Value at Risk (CVaR) approaches to explore and predict a project schedule and cost performance under different scenarios. This research selected a high-rise residential building project for a case study and collected 1672 productivity data samples. Arena Simulation models were established based on 90 combinations of labor assignments to assess Takt-time planning strategies' impact on project performance in four scenarios. The VaR and CVaR evaluations at 75% and 90% confidence levels were compared to balance project benefits and risks. Without any overtime or additional workers, this research found a Takt-time planning method that can reduce the project duration by 20.2% and labor costs by 2.1% at the same time, using a labor assignment of 12 bar placers, 12 carpenters, and 5 pipefitters. The findings can assist construction managers to achieve a shorter duration, reduced cost, and safer work environment, which will be very effective and beneficial to improve project overall performance. [ABSTRACT FROM AUTHOR]

Gold mining activity is a source of supply in many areas of the world, and especially in developing countries, it is practiced illegally and by applying unsafe techniques. Particularly in Ecuador, artisanal and small-scale gold mining (ASGM) is widespread, and it is based on the use of toxic substances, such as mercury (Hg), in gold recovery. Hg is a heavy metal that is water-insoluble, which, once mobilized, poses a threat to both the environment and human health. This study analyzes Hg concentrations in the six provinces of Napo, Sucumbíos, Orellana, Pastaza, Morona Santiago, and Zamora Chinchipe of the Ecuadorian Amazon region to conduct a human health risk assessment. Significant differences in Hg levels were found between provinces, but concentrations were below MPL imposed by Ecuadorian regulations everywhere. Nevertheless, a worrisome picture emerges, especially with regard to the most vulnerable receptors represented by the child population. There are multiple factors of incidence that may affect the possible future development of the phenomenon, and with reference to the social, economic, and environmental context of the region, it can be concluded that it may be appropriate to plan further investigation to arrive at a more comprehensive assessment. The results of this study can be used by decision makers to plan further investigation and to implement monitoring networks, risk mitigation strategies, and groundwater protection measures. [ABSTRACT FROM AUTHOR]

Copyright of Power Generation Technology is the property of Power Generation Technology 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.)

With the increasing proportion of renewable energy, the power system inertia decreases, and the operation uncertainty rises. It brings concerns about the system frequency and operational reliability. However, the impacts of the power system frequency performance on the reliability parameters of generation units have not been fully investigated. This paper studies the frequency performance and the operational reliability co-evaluation for power systems considering wind turbines. Firstly, a power system frequency regulation model is established considering the regulation capability of wind turbines. Then, the cluster of equivalent wind turbines is incorporated into the frequency regulation architecture of thermal power units, which accelerates the analysis of frequency performance. Then, the frequency performance of the power system with the participation of wind turbines under the operation uncertainty and the unit random faults is quantitatively analyzed. A frequency-dependent generator reliability parameter model is derived. Next, a multi-time scale co-evaluation framework is proposed to realize the co-evaluation of frequency performance and operational reliability. Case studies are carried out on the modified IEEE RTS-79 system and a provincial power system. Results show that compared with the existing research, the proposed method can obtain the frequency performance and reliability results efficiently. [ABSTRACT FROM AUTHOR]

Monitoring and assessing coastal subsidence is crucial to mitigating potential disaster risks associated with rising sea levels. Nansha District in Guangzhou City, representing global coastal soft-soil urban areas, faces significant challenges related to ground subsidence. However, the current understanding of the status, causative factors, and risk (includes subsidence susceptibility and vulnerability) assessment of ground subsidence in Nansha District is unclear. To address this gap, we utilized the SBAS-InSAR technique, analyzing 49 Sentinel-1A images from December 2015 to June 2019, for systematic ground subsidence monitoring. Subsequently, we assessed subsidence risk using a comprehensive index method and a risk matrix. Our findings indicate that subsidence velocity primarily ranged from −40 to −5 mm/a, with a spatial pattern of increasing subsidence from inland to coastal areas. The cumulative subsidence process unfolded in four distinct stages. The genesis of land subsidence was linked to an endogenous geological context dominated by soft-soil deposition, influenced by external factors such as surface loading and groundwater extraction. High-risk zones were concentrated in key engineering development areas, transportation pipeline trunk lines, and densely populated regions, demanding special attention. This study provides a foundational resource for disaster prevention and control strategies in Nansha District and similar coastal cities. [ABSTRACT FROM AUTHOR]

Background: Brucellosis is a zoonotic affliction instigated by bacteria belonging to the genus Brucella and is characterized by a diverse range of pervasiveness, multiple transmission routes, and serious hazards. It is imperative to amalgamate the current knowledge and identify gaps pertaining to the role of ticks in brucellosis transmission. Methods: We systematically searched China National Knowledge Infrastructure (CNKI), WanFang, Google Scholar, and PubMed on the topic published until April 23, 2022. The procedure was performed in accordance with the Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The selected articles were categorized across three major topic areas, and the potential data was extracted to describe evidence-practice gaps by two reviewers. Results: The search identified 83 eligible studies for the final analyses. The results highlighted the potential capacity of ticks in brucellosis transmission as evidenced by the detection of Brucella in 16 different tick species. The pooled overall prevalence of Brucella in ticks was 33.87% (range: 0.00–87.80%). The review also revealed the capability of Brucella to circulate in parasitic ticks' different developmental stages, thus posing a potential threat to animal and human health. Empirical evidence from in vitro rodent infection experiments has revealed that ticks possess the capability to transmit Brucella to uninfected animals (range: 45.00–80.00%). Moreover, significant epidemiological associations have been found between the occurrence of brucellosis in animals and tick control in rangelands, which further suggests that ticks may serve as potential vectors for brucellosis transmission in ruminants. Notably, a mere three cases of human brucellosis resulting from potential tick bites were identified in search of global clinical case reports from 1963 to 2019. Conclusions: It is imperative to improve the techniques used to identify Brucella in ticks, particularly by developing a novel, efficient, precise approach that can be applied in a field setting. Furthermore, due to the lack of adequate evidence of tick-borne brucellosis, it is essential to integrate various disciplines, including experimental animal science, epidemiology, molecular genetics, and others, to better understand the efficacy of tick-borne brucellosis. By amalgamating multiple disciplines, we can enhance our comprehension and proficiency in tackling tick-borne brucellosis. [ABSTRACT FROM AUTHOR]

The study used various indices of pollution to assess the level of soil contamination from Irasa Abattoir in Ado-Ekiti, Southwestern Nigeria. Samples of soil were collected at the surface, 15cm and 30cm depths from effluent, roasting and bone waste areas, so as to evaluate the influence of abattoir activities on the soil quality. The geo-accumulation index (Igeo) indicates uncontaminated to moderate contamination for the studied heavy metals, while the PLI > 1 revealed continuous deterioration of the studied sites. The potential ecological risk factor and risk index (RI) of the metals revealed low risk level. However, the study exposed the effect of wastes and other activities on the status of the soils. Therefore, there is need to monitor the deterioration level of the abattoir site. [ABSTRACT FROM AUTHOR]

The high profit of regional investment is often accompanied by high risks, and the prior assessment of investment risks is conducive to avoid investment risks. However, the traditional evaluation methods usually only focus on individual risk factors, and it is difficult to evaluate and manage risks on the whole. Therefore, the study introduces deep learning algorithm, first build regional investment risk evaluation index system, then according to the characteristics of risk evaluation, design based on deep learning regional investment risk evaluation model, the final use parameter based migration learning algorithm and composite correlation coefficient to improve the evaluation model, solve the problem of insufficient training samples. The test results showed that the randomly selected 50 test samples with two different risk assessment models were 0.80 and 0.86, the deep learning algorithm tested 0.84, and the transfer learning improved model tested was 0.92, with the highest accuracy. This shows that the deep learning regional investment risk evaluation model improved by transfer learning effectively solves the problem of insufficient training data and improves the accuracy of prediction evaluation. In the field of venture capital, the model can help investors to evaluate and predict investment risks more accurately and improve the effect of investment decisions. [ABSTRACT FROM AUTHOR]

Copyright of Geology & Exploration is the property of Geology & Exploration 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.)

Copyright of Rock & Mineral Analysis is the property of Editorial Board of Rock & Mineral Analysis 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.)

Elevators have become an integral part of modern buildings, and technological advances have enabled the monitoring of their operational status through sensor technology. In response to the development of the elevator industry and the need for practical elevator operation risk evaluation, this paper proposes an elevator risk evaluation method based on fuzzy theory and machine learning methods. The method begins by establishing an elevator operation risk evaluation index system. The traditional fuzzy comprehensive evaluation method is then employed to evaluate the risk levels of the 50 elevators studied. The collected index data and labels (fuzzy comprehensive evaluation results) are used as inputs to train the support vector machine (SVM) model. To optimize the SVM model, the maximum information coefficient method, enhanced by the correlation-based feature selection (MIC-CFS) method, is employed to select features for the index input to the SVM model. The improved gray wolf algorithm (IGWO) method optimizes the SVM. Finally, the model's performance is verified using new index data. The experimental results demonstrate that introducing machine learning methods for elevator risk evaluation saves time and effort while providing good accuracy compared to the traditional expert evaluation method. The optimization of the SVM model by IGWO and feature selection by the MIC-CFS method results in a more concise SVM model that converges faster during training, exhibits better stability, and achieves higher accuracy. [ABSTRACT FROM AUTHOR]