Treatment Indications of Carbon Solution-Assisted Nd: YAG Laser According to Patient Satisfaction: A Retrospective Study.

INTRODUCTION: Carbon solution-assisted Nd:YAG lasers were previously used in enlarged pores; hair removal; acne and acne scars; and facial rejuvenation. OBJECTIVES: The aim of this study is to determine the patient satisfaction for different treatment indications of carbon solution-assisted 1064 nm Nd:YAG lasers. METHODS: This is a retrospective study that included the patients who were treated with carbon solution-assisted 1064 nm Nd:YAG laser with any indication in a private dermatology practice. A pre-prepared carbon solution was applied 30 minutes before the laser treatment with the following parameters: a spot size of 8mm, fluence of 1.3 J/cm2 and a frequency of 8Hz. Patient satisfaction was assessed with GAIS. RESULTS: A total of 272 patients were included; of these 70 patients had acne lesions, 135 patients had melasma, 27 patients had post-inflammatory hyperpigmentation, 17 patients had ephelides and 23 patients had solar lentigines. The mean patient satisfaction for solar lentigo patients (4.35/5) was greater than for that of acne patients (4.26/5) which was greater than that of ephelide patients (3.94/5) which was greater than that of melasma patients (3.67/5) which was greater than that of post inflammatory hyperpigmentation patients (2.30/5) CONCLUSIONS: This study revealed that carbon solution-assisted 1064 nm Nd:YAG laser therapy is effective in the treatment of solar lentigo, acne vulgaris, ephelides and melasma. However, it fails to provide therapeutic efficacy in post inflammatory hyperpigmentation.

New cosine similarity and distance measures for Fermatean fuzzy sets and TOPSIS approach.

The most straightforward approaches to checking the degrees of similarity and differentiation between two sets are to use distance and cosine similarity metrics. The cosine of the angle between two n-dimensional vectors in n-dimensional space is called cosine similarity. Even though the two sides are dissimilar in size, cosine similarity may readily find commonalities since it deals with the angle in between. Cosine similarity is widely used because it is simple, ideal for usage with sparse data, and deals with the angle between two vectors rather than their magnitude. The distance function is an elegant and canonical quantitative tool to measure the similarity or difference between two sets. This work presents new metrics of distance and cosine similarity amongst Fermatean fuzzy sets. Initially, the definitions of the new measures based on Fermatean fuzzy sets were presented, and their properties were explored. Considering that the cosine measure does not satisfy the axiom of similarity measure, then we propose a method to construct other similarity measures between Fermatean fuzzy sets based on the proposed cosine similarity and Euclidean distance measures and it satisfies the axiom of the similarity measure. Furthermore, we obtain a cosine distance measure between Fermatean fuzzy sets by using the relationship between the similarity and distance measures, then we extend the technique for order of preference by similarity to the ideal solution method to the proposed cosine distance measure, which can deal with the related decision-making problems not only from the point of view of geometry but also from the point of view of algebra. Finally, we give a practical example to illustrate the reasonableness and effectiveness of the proposed method, which is also compared with other existing methods.

Fermatean fuzzy ELECTRE multi-criteria group decision-making and most suitable biomedical material selection.

ELECTRE is a family of multi-criteria decision analysis techniques, which has the ability to provide as much as possible precise and suitable set of actions or alternatives to the underlying problem by eliminating the alternatives, which are outranked by others. Group decision-making is an effective process to provide the most appropriate solution to real-world decision-making scenarios by considering and merging the expert opinions of multiple individuals on the problem. The aim of this study is to present an extended version of the ELECTRE I model called the Fermatean fuzzy ELECTRE I method for of multi-criteria group decision-making with Fermatean fuzzy human assessments. The method proposed in this study has the possibility to solve multi-criteria group decision-making problems by using the Fermatean fuzzy decision matrix obtained in Fermatean fuzzy number form in the evaluations made with the available alternatives based on expert opinions. First, the mathematical description of the multi-criteria group decision-making problem with Fermatean fuzzy information has been given. Then, the proposed Fermatean fuzzy ELECTRE I method to deal with the problem has been presented. After the determination of the relative importance degree of experts, the Fermatean fuzzy aggregated averaging operator is employed to merge the individual Fermatean fuzzy decision matrices produced by the experts into the aggregated Fermatean fuzzy decision matrix. Next, for pairwise comparison of available alternatives with respect to considered criteria, the concepts of Fermatean fuzzy strong, midrange, and weak concordance and discordance sets are based on the approach of score function and accuracy function defined for Fermatean fuzzy numbers. Afterward, Fermatean fuzzy concordance and discordance matrices are defined, constructed by concordance and discordance indices. Finally, Fermatean fuzzy effective concordance and discordance matrices are computed to obtain Fermatean fuzzy aggregated outranking matrix, indicating abstract information on dominations of suitable alternatives to the others. The proposed method will be used in material selection in distinct implementations, exclusively in biomedical applications where the prosthesis materials should have similar characteristics to human tissues. Since biomedical materials are used in various parts of the human body for many different purposes, in this study, material selection will be made using the method presented for the femoral component of the hip joint prosthesis for orthopedists and practitioners who will choose biomaterials.

Focused radiofrequency and ultrasound for face and neck rejuvenation: A retrospective evaluation of 158 patients.

BACKGROUND: Radiofrequency is a commonly used method to non-invasively tighten the skin that can be safely applied to any skin type. AIMS: The aim of our study was to evaluate the safety and efficacy of the focused radiofrequency and ultrasound hybrid device for face and neck rejuvenation, in terms of improvement of facial wrinkles and jaw sagging. METHODS: A total of 158 patients had undergone four weekly sessions of focused radiofrequency and ultrasound to face and neck area. Photodocumentation was obtained before first visit and two weeks after last visit. An independent, blinded dermatologist evaluated the severity of wrinkles and sagging of seven different anatomical regions on a validated scale of 0-4 (0: no lines/sagging, 1: mild, 2: moderate, 3: severe, 4: very severe) before and after the procedure. Patients rated their satisfaction with the result of the treatment on a scale of 1-5 (1: dissatisfied, 2: poorly satisfied 3: satisfied, 4: very satisfied, 5: perfectly satisfied). RESULTS: For seven anatomical regions, statistically significant reduction was observed in mean wrinkle/sagging scores (p = < 0.001). Patients were satisfied with the effects of the procedure, with a mean satisfaction score of 4.61 ± 0.55. CONCLUSIONS: Our findings demonstrate that combined focused radiofrequency and ultrasound is an effective and safe method for the rejuvenation of different sub-areas of the face and neck with high patient satisfaction scores.

The novel VIKOR methods for generalized Pythagorean fuzzy soft sets and its application to children of early childhood in COVID-19 quarantine.

In this work, the new VIKOR methods are established using the generalized Pythagorean fuzzy soft sets (GPFSSs). For GPFSSs, the distance measures such as Hamming, Euclidean, and generalized are given. Further, the basic characteristics of these distance measures are examined. Fuzzy and soft sets are strong instruments for uncertainty. This strongness has been demonstrated by the GPFSS combining Pythagorean fuzzy sets and soft sets and applied to imprecise and ambiguous information. In this context, new remoteness index-based methods have been proposed, which are dissimilar from available VIKOR methods. The displaced and fixed ideals positive and negative Pythagorean fuzzy values (PFV) were defined. Thus, based on this definition, displaced positive ideal remoteness indices, negative ideal remoteness indices, and fixed positive ideal, negative ideal remoteness indices were discussed. Two different weights are used here: weights based on OF preference information and precise weights calculated with the expectation score function. The VIKOR method given here provides a different way from canonical VIKOR methods: rank candidate alternatives and determining a compromise solution based on different preference structures. The processes principles of the newly defined GPFSSs VIKOR methods are given by four algorithms. An example of these algorithms is given with the behavioral development and cognitive development of the children of Early Childhood children in the COVID-19 quarantine.

Fibonacci statistical convergence and Korovkin type approximation theorems.

The purpose of this paper is twofold. First, the definition of new statistical convergence with Fibonacci sequence is given and some fundamental properties of statistical convergence are examined. Second, we provide various approximation results concerning the classical Korovkin theorem via Fibonacci type statistical convergence.