ABSTRACT
Q-rung orthopair fuzzy sets have been proven to be highly effective at handling uncertain data and have gained importance in decision-making processes. Torra's hesitant fuzzy model, on the other hand, offers a more generalized approach to fuzzy sets. Both of these frameworks have demonstrated their efficiency in decision algorithms, with numerous scholars contributing established theories to this research domain. In this paper, recognizing the significance of these frameworks, we amalgamated their principles to create a novel model known as Q-rung orthopair hesitant fuzzy sets. Additionally, we undertook an exploration of Aczel-Alsina aggregation operators within this innovative context. This exploration resulted in the development of a series of aggregation operators, including Q-rung orthopair hesitant fuzzy Aczel-Alsina weighted average, Q-rung orthopair hesitant fuzzy Aczel-Alsina ordered weighted average, and Q-rung orthopair hesitant fuzzy Aczel-Alsina hybrid weighted average operators. Our research also involved a detailed analysis of the effects of two crucial parameters: λ, associated with Aczel-Alsina aggregation operators, and N, related to Q-rung orthopair hesitant fuzzy sets. These parameter variations were shown to have a profound impact on the ranking of alternatives, as visually depicted in the paper. Furthermore, we delved into the realm of Wireless Sensor Networks (WSN), a prominent and emerging network technology. Our paper comprehensively explored how our proposed model could be applied in the context of WSNs, particularly in the context of selecting the optimal gateway node, which holds significant importance for companies operating in this domain. In conclusion, we wrapped up the paper with the authors' suggestions and a comprehensive summary of our findings.
ABSTRACT
OBJECTIVE: The causes of failure after an initial Gamma procedure were studied, along with imaging and clinical outcomes, in a series of 140 patients with cerebral arteriovenous malformations (AVMs) treated with repeat Gamma Knife surgery (GKS). METHODS: Causes of initial treatment failure included inaccurate nidus definition in 14 patients, failure to fill part of the nidus as a result of hemodynamic factors in 16, recanalization of embolized AVM compartments in 6, and suboptimal dose (<20 Gy) in 23. Nineteen patients had repeat GKS for subtotal obliteration of AVMs. In 62 patients, the AVM failed to obliterate despite correct target definition and adequate dose. At the time of retreatment, the nidus volume ranged from 0.1 to 6.9 cm3 (mean, 1.4 cm3), and the mean prescription dose was 20.3 Gy. RESULTS: Repeat GKS yielded a total angiographic obliteration in 77 patients (55%) and subtotal obliteration in 9 (6.4%). In 38 patients (27.1%), the AVMs remained patent, and in 16 patients (11.4%), no flow voids were observed on magnetic resonance imaging. Clinically, 126 patients improved or remained stable, and 14 experienced deterioration (8 resulting from a rebleed, 2 caused by persistent arteriovenous shunting, and 4 related to radiation-induced changes). CONCLUSION: By using repeat GKS, we achieved a 55% angiographic cure rate. Although radiation-induced changes as visualized on magnetic resonance imaging occurred in 48 patients (39%), only 4 patients (3.6%) developed permanent neurological deficits. These findings may be useful in deciding the management of AVMs in whom total obliteration after initial GKS was not achieved.
