Abstract
Considering the beauty industry’s potential for further expansion and the mismatch between the attitudes of consumers and their buying behavior, brands should comprehend the factors that influence consumers’ intention to purchase environmentally friendly cosmetics. As such, the present study examined what encourages consumers of environmentally friendly cosmetics to choose these products. To answer the main objective of the work, the elaborated literature review aimed at identifying the factors that influence the buying of environmentally friendly cosmetics. Thus, the following were found: environmental consciousness, certification labels, brand trust, quality expectation, lifestyle, advertising, willingness to pay the price, ethical concerns and social and financial equity, physical health considerations, and knowledge of the product. The study was conducted using exploratory research with a qualitative approach. Data was collected from eight interviews, and it was identified that factors such as environmental consciousness, lifestyle, willingness to pay the price, quality expectations, ethical concerns and social and financial equity, as well as physical health considerations and knowledge of the product are the most significant determinants in the intention to buying environmentally friendly cosmetics. One of the aims of the investigation was to distinguish between the notions of green, traditional, organic, and natural cosmetics. As a result, it was found that there is a lack of clarification of the green cosmetic concept in literature, as well as a lack of standardization of criteria used by multiple systems to define different cosmetics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
In today's world, the idea of sustainable fashion is gaining traction. Finding a link between pricing and the purchase of sustainable clothes is the aim of this study. Regression models and t-tests of two independent samples (two-tailed tests) were applied by means of the application of a questionnaire. The study found that consumers' willingness to pay for price increases is related with non-linear (quadratic or exponential) product pricing. The results of this study suggest that consumers are willing to pay higher prices for sustainable clothing. Through an understanding of the relationship between price and consumer behavior, businesses can more effectively align their pricing strategies with the demands of environmentally conscious consumers. © 2024, IGI Global. All rights reserved.

Abstract
Purpose: To evaluate the outcomes and durability of drug -eluting stents (DESs) for the treatment of hemodialysis access outflow stenosis. Material and Methods: A single -center retrospective analysis was conducted of all patients with hemodialysis vascular access outflow stenosis treated with a paclitaxel-coated DES (Eluvia; Boston Scientific, Marlborough, Massachusetts) between January 2020 and July 2022. A total of 34 DESs were implanted to treat outflow stenosis in 32 patients. Primary target lesion patency after stent deployment was the main outcome. Comparison between the time interval free from target lesion reintervention (TLR) after previous plain balloon angioplasty (PBA) and that after stent deployment for the same target lesion was considered a secondary outcome. Results: The primary patency at 6, 12, and 18 months was 63.1%, 47.6%, and 41.7%, respectively. The secondary patency rate was 100% at 18 months. The median time interval free from TLR increased from 4.1 to 11.9 months (P < .001). No adverse events were observed during the median follow-up period of 387 days. Conclusions: The patency rates after use of DES for hemodialysis access outflow stenosis were comparable with results for drug -coated balloons and stent grafts, addressing recoil and minimizing the risk of jailing by a covered stent.

Abstract
IntroductionWilson's disease (WD) is associated with a variety of movement disorders and progressive neurological dysfunction. The aim of this study was to correlate baseline brain magnetic resonance imaging (MRI) features with clinical phenotype and long-term outcomes in chronically treated WD patients.MethodsPatients were retrospectively selected from an institutional database. Two experienced neuroradiologists reviewed baseline brain MRI. Functional assessment was performed using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) scale, and disease severity was classified using the Global Assessment Scale for Wilson's Disease (GASWD).ResultsOf 27 patients selected, 14 were female (51.9%), with a mean (standard deviation [SD]) age at onset of 19.5 (7.1) years. Neurological symptoms developed in 22 patients (81.5%), with hyperkinetic symptoms being the most common (70.4%). Baseline brain MRI showed abnormal findings in 18 cases (66.7%), including T2 hyperintensities in 59.3% and atrophy in 29.6%. After a mean (SD) follow-up of 20.9 (11.0) years, WD patients had a mean score of 19.2 (10.2) on WHODAS 2.0 and 6.4 (5.7) on GASWD. The presence of hyperkinetic symptoms correlated with putaminal T2 hyperintensities (p = 0.003), putaminal T2 hypointensities (p = 0.009), and mesencephalic T2 hyperintensities (p = 0.009). Increased functional disability was associated with brain atrophy (p = 0.007), diffusion abnormalities (p = 0.013), and burden of T2 hyperintensities (p = 0.002). A stepwise regression model identified atrophy as a predictor of increased WHODAS 2.0 (p = 0.023) and GASWD (p = 0.007) scores.ConclusionsAtrophy and, to a lesser extent, deep T2 hyperintensity are associated with functional disability and disease severity in long-term follow-up of WD patients.

Abstract
Wind power is becoming an important source of electrical energy production. In an onshore wind farm (WF), the electrical energy is collected at a substation from different wind turbines through electrical cables deployed over ground ditches. This work considers the WF layout design assuming that the substation location and all wind turbine locations are given, and a set of electrical cable types is available. The WF layout problem, taking into account its lifetime and technical constraints, involves selecting the cables to interconnect all wind turbines to the substation and the supporting ditches to minimize the initial investment cost plus the cost of the electrical energy that is lost on the cables over the lifetime of the WF. It is assumed that each ditch can deploy multiple cables, turning this problem into a more complex variant of previously addressed WF layout problems. This variant turns the problem best fitting to the real case and leads to substantial gains in the total cost of the solutions. The problem is defined as an integer linear programming model, which is then strengthened with different sets of valid inequalities. The models are tested with four WFs with up to 115 wind turbines. The computational experiments show that the optimal solutions can be computed with the proposed models for almost all cases. The largest WF was not solved to optimality, but the final relative gaps are small.

Abstract
In recent years, as a result of population growth and the strong demand for energy resources, there has been an increase in greenhouse gas emissions. Thus, it is necessary to find solutions to reduce these emissions. This will make the use of electric vehicles (EV) more attractive and reduce the high dependency on internal combustion vehicles. However, the integration of electric vehicles will pose some challenges. For example, it will be necessary to increase the number of fast electric vehicle charging stations (FEVCS) to make electric mobility more attractive. Due to the high power levels involved in these systems, there are voltage drops that affect the voltage profile of some nodes of the distribution networks. This paper presents a methodology based on a genetic algorithm (GA) that is used to find the optimal location of charging stations that cause the minimum impact on the grid voltage profile. Two case studies are considered to evaluate the behavior of the distribution grid with different numbers of EV charging stations connected. From the results obtained, it can be concluded that the GA provides an efficient way to find the best charging station locations, ensuring that the grid voltage profile is within the regulatory limits and that the value of losses is minimized.