Search Results (260)

Few studies have explored the holistic public health risk assessment associated with toxic elements (TEs) and their bioaccessibility in integrated urban environmental media including soils, vegetables, atmospheric particles, dust, etc. Urban industrial complex areas like Qingshan-Chemical District (QCD) in the Chinese Wuhan city, located within the Yangtze River Economic Belt, face increasing environmental exposure risks due to industrial activities. This study innovatively assessed the hierarchical risks of toxic metals in 4 environmental media (air PM, dust, soil, vegetables) from the QCD based on field sampling and chemical analysis, and developed an improved fuzzy health risk assessment model based on toxic metals’ in vitro bioaccessibilities of different exposure pathways and triangular fuzzy numbers for handling parameter uncertainties. The study found that the highest health risks were associated with ingestion, particularly from consuming homegrown vegetables. Carcinogenic risks for arsenic (As), lead (Pb), and cadmium (Cd) via ingestion exceeded the admissible threshold of 1.00 × 10⁻⁶, with As showing the highest risk ([1.92 × 10⁻³, 2.37 × 10⁻³]), followed by Cd ([2.98 × 10⁻⁵, 3.67 × 10⁻⁵]) and Pb ([7.92 × 10⁻⁷, 1.48 × 10⁻⁶]). Inhalation risks from soil, dust, and air particulates were below the threshold, indicating lower respiratory concerns. Dermal exposure, especially from soil and dust, posed elevated carcinogenic risks for As ([7.47 × 10⁻⁶, 8.06 × 10⁻⁶]). With the screened priority risk control toxic metals and pathways, the targeted measures including relocating vegetable planting areas, promoting cultivation of low-enrichment crops, building vegetation buffer zones around the industrial park, etc., were proposed. Full article

The result of accelerated development and technological progress is manifested through numerous changes in the labor market, primarily concerning the competencies of future employees. Many of those competencies have symmetrical character. The determinants that may influence the development of specific competencies are variable and dynamic, yet they share the characteristic of transcending temporal and spatial boundaries. In this paper we propose the use of a combination of Principal Component Analysis (PCA) and Fuzzy Analytic Hierarchy Process (FAHP) to rank 21st-century competencies that are developed independently of the formal educational process. Ability to organize and plan, appreciation of diversity and multiculturalism, and ability to solve problems appeared to be the highest-ranked competencies. The development of key competencies is symmetrical to the skills for the labor market. Also, the development of key competencies is symmetrical to the right selection of the quality of media content. The paper proves that the development of key competencies is symmetrical to the level of education of both parents. One of the key findings is that participants with higher levels of media literacy express more readiness for the contemporary labor market. Moreover, the family, particularly parents, exerts a highly significant positive influence on the development of 21st-century competencies. Parents with higher levels of education, in particular, provide a stimulating environment for learning, foster critical thinking, and encourage the exploration of diverse domains of knowledge. Full article

Urban industrial complexes have been expanding worldwide, reducing the spatial separation between agricultural, residential, and industrial zones, particularly in developing nations. Urban road dust contamination, a sensitive indicator of urban environmental quality, primarily originates in urbanization and industrialization. Its detrimental impacts on human health arise not only from particulate matter itself but also from toxic and harmful substances embedded within dust particles. Toxic metals in road dust can pose health risks through inhalation, ingestion and contact. To investigate the seasonal patterns, bioaccessibility levels and the potential human health risks linked to toxic metals (Cadmium (Cd), Nickel (Ni), Arsenic (As), Lead (Pb), Zinc (Zn), Copper (Cu), and Chromium (Cr)), 34 dust samples were collected from key roads in proximity to representative industrial facilities in Wuhan’s Qingshan District. The study found that the concentrations of Cd, Pb, and Cu in road dust were within the limits set by the national standard (GB 15618-2018), while Ni and As were not. Seasonally, Ni, As, Pb, Zn, and Cr exhibited higher concentrations during the summer than in other seasons, whereas Cd levels were lowest in spring and highest in autumn, the opposite of Cu. According to the Simplified Bioaccessibility Extraction Test (SBET), the average bioaccessibility rates of toxic metals were Cd > Zn > Cu > Ni > Cr > As > Pb. An improved health risk assessment model was developed, integrating metal enrichment, bioaccessibility, and parameter uncertainty. Results indicated that Cd, Ni, Zn, Cu, As, and Cr posed no significant non-carcinogenic risk. However, for children, the carcinogenic risks of Cd and As were relatively high, identifying them as priority control metals. Therefore, it is recommended to periodically monitor As and Cd and regulate their potential emission sources, especially in winter and spring. Full article

To address the impact of the dynamic evolution of flood disaster chains and decision-makers’ (DMs’) risk preference heterogeneity on group decision-making, this study proposes a social network group decision-making method that integrates the evolutionary trend of the flood disaster chain with DMs’ risk preferences. First, a Bayesian network is constructed to quantify the disaster chain’s evolution, dynamically adjusting DMs’ evaluation values. Second, DMs’ risk preference types are identified based on the evaluation values, and a bounded confidence (BC) model, incorporating risk preferences, self-confidence and trust networks, is developed to promote consensus formation. Then, the optimal alternative is selected through weighted aggregation and used to update the Bayesian network dynamically during implementation. Finally, the effectiveness and superiority of the proposed method are verified using the flood disaster chain from the “7∙20” extreme rainfall disaster in Zhengzhou, Henan Province, China. The results show that risk-seeking DMs reduce BC values and resist consensus, whereas risk-averse DMs enlarge BC values and accelerate convergence. Moreover, worsening flood disaster chain trends drive DMs to update the optimal alternative. These findings show that the method captures both dynamic disaster evolution and behavioral heterogeneity, providing realistic and adaptive decision support in flood emergency scenarios. Full article

This study focuses on the numerical analysis of heat transfer in biological tissue. The proposed model is formulated using the Pennes equation for a two-dimensional cylindrical domain. The tissue undergoes laser irradiation, where internal heat sources are determined based on the Beer–Lambert law. Moreover, key parameters—such as the perfusion rate and effective scattering coefficient—are modeled as functions dependent on tissue damage. In addition, a fuzzy heat source associated with magnetic nanoparticles is also incorporated into the model to account for magnetothermal effects. A novel aspect of this work is the introduction of uncertainty in selected model parameters by representing them as triangular fuzzy numbers. Consequently, the entire Finite Pointset Method (FPM) framework is extended to operate with fuzzy-valued quantities, which—to the best of our knowledge—has not been previously applied in two-dimensional thermal modeling of biological tissues. The numerical computations are carried out using the fuzzy-adapted FPM approach. All calculations are performed due to the fuzzy arithmetic rules with the application of α-cuts. This fuzzy formulation inherently captures the variability of uncertain parameters, effectively replacing the need for a traditional sensitivity analysis. As a result, the need for multiple simulations over a wide range of input values is eliminated. The findings, discussed in the final Section, demonstrate that this extended FPM formulation is a viable and effective tool for analyzing heat transfer processes under uncertainty, with an evaluation of α-cut widths and the influence of the degree of fuzziness on the results also carried out. Full article

To broaden the informational scope of existing fuzzy frameworks and enhance their flexibility in representing and processing uncertainty, we propose a novel p,q-rung triangular orthopair fuzzy number (p,q-RTOFN). To enhance the aggregation capability of fuzzy data, we develop a p,q-rung triangular orthopair fuzzy weighted power Bonferroni mean (p,q-RTOFWPBM) operator that integrates the strengths of the Bonferroni mean and power average operators. We formally establish its theorems, proofs, and key properties, including symmetry and idempotency. Furthermore, we extend the complex proportional assessment (COPRAS) method to the p,q-RTOF environment, resulting in a p,q-RTOF-PBM-COPRAS model. This model effectively incorporates both positive and negative evaluation information under uncertainty, thereby reducing information loss and improving decision accuracy. A case study on urban smart farm selection confirms the feasibility and superiority of the proposed approach. This study introduces the p,q-RTOFN framework with extended informational scope, develops a hybrid p,q-RTOFWPBM operator, and incorporates these advances into an extended COPRAS method to achieve more accurate multi-criteria decision-making under uncertainty. Full article

Strategic fleet renewal represents a fundamental challenge for small and medium-sized enterprises (SMEs) and public entities seeking to align their operational objectives with sustainable mobility practices. This paper proposes a hybrid decision support model based on fuzzy logic, combining the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with the Fleet Renewal Priority Index (FRPI). The model evaluates and prioritizes different vehicle alternatives based on multiple economic, environmental, and operational criteria, including total cost of operation, CO₂ emissions, maintenance, autonomy, infrastructure compatibility, and energy independence. The criteria are evaluated by linguistic judgments converted into triangular fuzzy numbers (TFN), allowing uncertainty and subjectivity to be addressed. A simulated case study illustrates the application of the model, identifying the vehicles most aligned with a sustainability and efficiency strategy, as well as those that present a greater urgency for replacement. The results demonstrate the potential of the approach to support rational, transparent and sustainable decisions in fleet modernization. Full article

Trapezoidal-valued intuitionistic fuzzy numbers (TrVIFNs) are the real generalizations of intuitionistic fuzzy numbers, interval-valued intuitionistic fuzzy numbers, and triangular intuitionistic fuzzy numbers, which effectively model real-life problems that consist of imprecise and incomplete data. This study incorporates the Aczel-Alsina aggregation operators (which consist of parameter-based flexibility) for solving any group of decision-making problems modeled in a trapezoidal-valued intuitionistic fuzzy (TrVIF) environment. In this study, we first define new operations on TrVIFNs based on the Aczel-Alsina operations. Secondly, we introduce new trapezoidal-valued intuitionistic fuzzy aggregation operators, such as the TrVIF Aczel-Alsina weighted averaging operator, the TrVIF Aczel-Alsina ordered weighted averaging operator, and the TrVIF Aczel-Alsina hybrid averaging operator, and we discuss their fundamental mathematical properties by examining various theorems. This study also includes a new algorithm named ‘three-stage multi-criteria group decision-making’, where we obtain the criteria weights using the newly proposed TrVIF-MEREC method. Additionally, we introduce a new modified algorithm called TrVIF-WASPAS to solve the multi-criteria decision-making (MCDM) problem in the trapezoidal-valued intuitionistic fuzzy environment. Then, we apply this proposed method to solve a model case study problem involving location selection for a wind power plant project. Then, we discuss the proposed algorithm’s sensitivity analysis by changing the criteria weights concerning different parameter values. Finally, we compare our proposed methods with various existing methods, like some subclasses of TrVIFNs such as IVIFWA, IVIFWG, IVIFEWA, and IVIFEWG, and also with some MCGDM methods of TrVIFNs, such as the Dombi aggregation operator-based method in TrVIFNs and the TrVIF-Topsis method-based MCGDM, to show the efficacy of our proposed algorithm. This study has many advantages, as it consists of a total ordering principle in ranking alternatives in the newly proposed TrVIF-MCGDM techniques and TrVIF-WASPAS MCDM techniques for the first time in the literature. Full article

We introduce I-fp convergence (ideal convergence in fuzzy paranormed spaces) and develop its core theory, including stability results and an equivalence to $I^{*}$-fp convergence under the AP Property. Building on this foundation, we design an adaptive base-stock policy for a single-echelon inventory system in which weekly demand is expressed as triangular fuzzy numbers while holiday or promotion weeks are treated as ideal-small anomalies. The policy is updated by a simple learning rule that can be implemented in any spreadsheet, requires no optimisation software, and remains insensitive to tuning choices. Extensive simulation confirms that the method simultaneously lowers cost, reduces average inventory and raises service level relative to a crisp benchmark, all while filtering sparse demand spikes in a principled way. These findings position I-fp convergence as a lightweight yet rigorous tool for blending linguistic uncertainty with anomaly-aware decision making in supply-chain analytics. Full article

Against the backdrop of the energy revolution, global energy demands are rising. Solar–wind hybrid energy storage plants (SWHESPs) are undoubtedly a research hotspot in this field for enhancing energy efficiency. However, the primary challenge in constructing SWHESPs is site selection. This paper aims to comprehensively investigate the site selection process for SWHESPs and determine the optimal site scientifically and objectively by considering various aspects, including technology, society, environment, and economy. This study employs a literature review and the Delphi method to establish the site selection index system of SWHESPs. The triangular fuzzy number (TFN) is used in relative similarity as an objective weight, while the Decision-Making Test and Evaluation Laboratory (DEMATEL) is used as a subjective weight. The comprehensive weights are computed using the Lagrange optimization method. Additionally, the options are ranked and evaluated using Geographic Information System (GIS) and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods based on prospect theory. The study also performs comparative and sensitivity analyses to confirm the effectiveness of the proposed methods. Proper siting can optimize the efficiency of resource use, which not only helps achieve more efficient use of clean energy but also promotes local economic development and job creation. Full article

This paper presents a novel formulation of Ordered Fuzzy Numbers (OFNs), referred to as Vectorial Ordered Fuzzy Numbers (vOFNs). In contrast to the traditional definition based on a pair of functions, the vOFN framework employs a pair of vectors, offering a more concise and structurally coherent representation. This reformulation addresses the key limitations of classical OFNs, such as non-convexity and difficulties in handling curvilinear boundaries during multiplication and division. The vOFN model retains compatibility with commonly used fuzzy number types—triangular, trapezoidal, and singleton—and preserves directional properties that are essential for modeling fuzzy trends. Furthermore, it simplifies comparison operations and supports a complete algebraic structure. Due to its mathematical consistency, low computational complexity, and ease of implementation, the vOFN framework is well-suited for applications in intelligent systems, particularly in domains that require reasoning under uncertainty. Full article

Hydrogen is a potential source of imminent clean energy in the future, with its transportation playing a crucial role in allowing large-scale deployment. The challenge lies in selecting an effective, sustainable, and scalable transportation alternative. This study develops a multi-criteria decision-making (MCDM) framework based on the intuitionistic fuzzy analytic hierarchy process (IF-AHP) to evaluate land-based hydrogen transportation alternatives across Canada. The framework includes uncertainty and decision-maker hesitation through the application of triangular intuitionistic fuzzy numbers (TIFNs). Seven factors, their subsequent thirty-three subfactors, and three alternatives to hydrogen transportation were identified through a literature review. Pairwise comparison was aggregated among factors, subfactors, and alternatives from three decision makers using an intuitionistic fuzzy weighted average, and priority weights were computed using entropy-based weight. The results show that safety and economic efficiency emerged as the most influential factors in the evaluation of hydrogen transportation alternatives, followed by environmental impact, security, and social impact and public health in ascending order. Among the alternatives, tube truck transport obtained the highest overall weight (0.3551), followed by pipelines (0.3272) and rail lines (0.3251). The findings suggest that the tube ruck is currently the most feasible transport option for land-based hydrogen distribution that aims to provide a transition of Canada’s energy mix. Full article

To enhance the operational efficiency of container multimodal transportation and mitigate carbon emissions during freight transit, this study investigates carbon emission-conscious multimodal transportation route optimization models and solution methodologies. Addressing the path optimization challenges under uncertain conditions, triangular fuzzy numbers are employed to characterize transportation time uncertainty, while a scenario-based robust regret model is formulated to address freight price volatility. Concurrently, the temporal value attributes of cargo are incorporated by transforming transportation duration into temporal costs within the model framework. Through the implementation of four distinct low-carbon policies, carbon emissions are either converted into cost metrics or established as constraint parameters, thereby constructing an optimization model with total cost minimization as the objective function. For model resolution, fuzzy chance-constrained programming is adopted for defuzzification processing. Subsequently, a multi-strategy improved whale optimization algorithm (WOA) is developed to solve the formulated model. Numerical case studies are conducted to validate the proposed methodology through comparative analysis with conventional WOA implementations, demonstrating the algorithm’s enhanced computational efficiency. The experimental results confirm the model’s capability to adapt multimodal transportation schedules for cargo with varying temporal value attributes and effectively reduce CO₂ emissions under different carbon reduction policies. This research establishes a comprehensive decision-making framework that provides logistics enterprises with a valuable reference for optimizing low-carbon multimodal transportation operations. Full article

This study is organized to introduce the concept of center–radius $\left(cr\right)$-ordered fuzzy number-valued convex mappings. Based on this class of mappings, we have initiated the idea of fuzzy number-valued extended $cr$-ℏ convex mappings incorporating control mapping ℏ. Furthermore, several potential new classes of convexity will be provided to discuss its generic nature. Also, some essential properties, criteria, and detailed characterizations through Jensen’s and Hermite–Hadamard-like inequalities are provided, incorporating Riemann–Liouville fractional operators, which are defined by $\rho$-level mappings. To validate the proposed fractional bounds through simulations, we consider both triangular and trapezoidal fuzzy numbers. Our results are based on totally ordered fuzzy-valued mappings, which are new and generic. The under-consideration class also includes a blend of new classes of convexity, which are controlled by non-negative mapping ℏ. In previous studies, the researchers have focused on different partially ordered relations. Full article

The EVM method is an essential project management technique that compares the work done to the planned values (PVs) to identify project variances. However, the inherent uncertainties and possibilities in the project introduce uncertainty in the input data. Despite this importance, the input data for this method is often considered deterministic in most research, and several researchers have modeled it under fuzzy information. In this research, we developed a novel approach using a combined model of fuzzy numbers and grey numbers called interval grey triangular fuzzy (IGTF) numbers. This model is designed to manage the project’s fuzzy grey value, addressing the two pillars of fuzzy and grey uncertainty. The findings of the study indicate that by combining the grey degree of confidence with the triangular fuzzy number (TFN), the results are closer to the real world and more lenient. Finally, based on the estimation of the actual final cost of the project, managers are encouraged to use certainty in lowering costs concerning the value obtained by using the Z-number for the phases of the project. This research provides practical insights and a new model for managing sustainable project uncertainties using fuzzy and grey theories, offering a potential solution to this challenge. Full article