Per- and Polyfluoroalkyl Substances (PFAS) are characterized by strong carbon–fluorine bond formation. Those strong C–F bond formations justify the applicability of PFAS as a strong performer across industrial applications, due to their comprehensive properties, including resistance to water, heat, and chemicals, which lead to gradual accumulation and cause adverse health impacts. The complex behavior of PFAS in soil with different physicochemical characteristics has resulted in a lack of studies that utilize the molecular-level behavior in soil for further modelling purposes, which is important for a strong foundation for remediation measures. Therefore, this study focuses on elucidating theoretical, novel descriptions to fulfill the above-identified requirements. The developed paradigm, “Hydrophobically Driven Paradigm”, explains the strong attachment of PFAS to soil and the building of the PFAS-soil interface, employing the soil–water partitioning coefficient for clay soil from the literature. After confirming the strong attachment of PFAS to soil particles, the molecular-level interactions between PFAS and soil particles were explained by the framework, “System Retention Framework,” based on PFAS Zeta Potential (ZP) calculations derived under electrokinetic principles to describe the molecular-level retention behavior of PFAS. ZP values for two long-chain and short-chain PFAS were calculated using Henry’s and Nernst-Einstein equations. Results highlight that PFAS with higher ZP values have higher retention, while lower ZP values exhibit lower retention, in soil, confirming that the paradigm and framework can be used to define charge-driven interactions, followed by hydrophobically energized strong attractions, which are readily available for describing PFAS molecular-level behavior for future modelling with system contaminants.
Career selection is a multi-criteria decision-making problem that can be challenging, especially when uncertainties are involved. To tackle such a problem, several decision-making techniques have been used to compare and rank the alternatives. Pythagorean Fuzzy Sets (PyFS), which are used to describe uncertainty, have also been used by some researchers in attempts to solve decision making applications. This paper introduces PyFS in type-2 Fuzzy Environments as type-2 PyFS (T2PyFS) to handle the uncertainty of a decision making problem more appropriately. Unlike conventional PyFS, T2PyFS incorporates secondary membership functions that capture higher-order uncertainty and hesitation in expert judgments, thereby providing a more realistic and flexible modeling framework. We define several arithmetic operations and algebraic properties related to it, and propose its level sets, we investigate related properties. We also develop the Hamming and Euclidean distance of our T2PyFS, and design three decision making algorithms based on the level sets, max-min-max composition and distance measure. Along the lines of academic performance, we apply the proposed decision making algorithms to quantify and compare the different criteria and alternatives systematically. Finally, we conclude this study with a comparative analysis of the proposed algorithms.
Recently, the world has been living in a situation of constant uncertainty and insecurity. Russia’s aggression against Ukraine has entered its fifth year; the conflict between Israel and Hamas has been going on for more than two years; there is also long-standing tension between China and Taiwan, etc. So, it would not be wrong to say that we live in the presence of the constant threat of global war. This is especially true of the countries of Eastern Europe, and even more so of the Baltic states living in the neighbourhood of aggressive Russia. Under such conditions, these states should be ready for a defensive war. And here a whole series of theoretical–philosophical questions arise. What kind of war is moral and just? What are the prerequisites and conditions for such a war? What are the rules, norms, and principles for waging it? In the pursuit of answers, it is imperative to keep in view a historical perspective, thereby facilitating the acquisition of insights from past missteps. A pertinent exemplar of this perspective is the theory of the just war as expounded by the scholars of modern scholasticism during the fifteenth to eighteenth centuries. The most prominent proponents of this theory were Francisco de Vitoria (1480–1546), a member of the Dominican Order, and Francisco Suárez (1548–1617), a member of the Society of Jesus. These scholars built upon the philosophical contributions of St. Augustine and St. Thomas Aquinas, adapting them to the emerging geopolitical landscape of the New World, which was being explored and colonised during this period. The fundamental rights of nations and states, as well as the conditions, rules and principles of their defence in a just war (bellum justum), were established by their works, which were published prior to Hugo Grotius’s treatises. In fact, most of these principles and rules remain relevant in the contemporary world, where war is an inseparable element of everyday reality. This article focuses specifically on these issues, as well as their applicability in the contemporary context of troubled times.
Micromobility has emerged as a major global trend in urban transportation. However, it has also led to a rise in accidents, largely attributed to improper usage and inadequate safety precautions. This paper presents a model developed for the dynamic analysis of an in-wheel suspension system for micromobility vehicles, along with proposals for its improvement. The model accounts for challenges related to urban infrastructure, particularly variation in various obstacle types and heights on cycle road pavement, using the city of Vilnius (Lithuania) as a case study. The research paper additionally evaluates factors affecting rider safety and risk, with a primary focus on in-plane dynamics. The dynamic analysis demonstrates that the in-wheel suspension system enhances riding safety across simulated variations. These findings help identify critical vertical dynamic risks for micromobility in urban area and offer insights for future city’s road infrastructure planning.
Criminal investigations frequently consist of handling inadequate and ambiguous data, which can hamper the accuracy of crime investigation and profiling. This study presents innovative methods, based on the q-Rung Orthopair Fuzzy Set, to boost crime linkage investigation. By developing novel separation, distance, and entropy measures derived from the q-Rung Orthopair Fuzzy Set, we offer an effective technique that advances data differentiation and improves the accuracy of distance assessments. These methods efficiently address uncertainty and ambiguity, providing a dependable outline for explaining difficult challenges in forensic examinations. Comprehensive comparative analysis, runtime analysis, and case studies endorse the applicability of q-Rung Orthopair Fuzzy Set approaches in tasks, predominantly those concerning ambiguous data. Furthermore, the incorporation of expert valuations advances the trustworthiness of outcomes, indicating the importance of interdisciplinary association in decision-making methods. This study highlights the potential of q-Rung Orthopair Fuzzy Set-based methods to significantly contribute to applied sciences, offering new insights into how they can be applied to real-world, data-driven problems like forensic investigations.
