Abstract
Imbalanced learning is one of the most relevant problems in machine learning. However, it faces two crucial challenges. First, the amount of methods proposed to deal with such problem has grown immensely, making the validation of a large set of methods impractical. Second, it requires specialised knowledge, hindering its use by those without such level of experience. In this paper, we propose the Automated Imbalanced Classification method, ATOMIC. Such a method is the first automated machine learning approach for imbalanced classification tasks. It provides a ranking of solutions most likely to ensure an optimal approximation to a new domain, drastically reducing associated computational complexity and energy consumption. We carry this out by anticipating the loss of a large set of predictive solutions in new imbalanced learning tasks. We compare the predictive performance of ATOMIC against state-of-the-art methods using 101 imbalanced data sets. Results demonstrate that the proposed method provides a relevant approach to imbalanced learning while reducing learning and testing efforts of candidate solutions by approximately 95%.

Abstract

Abstract
This study aimed to assess the effectiveness of a structured intervention on the frequency of self-care behaviors with arteriovenous fistula (AVF) by patients on hemodialysis. This is a quasi-experimental study with pre- and post-measurements. Participants were assigned to an intervention group (IG) (n = 48) or to a control group (CG) (n = 41). IG patients were subject to a structured intervention on self-care with AVF (SISC-AVF) consisting of both a theoretical and a practical part. After SISC-AVF application, patients in the IG showed better overall self-care behaviors with AVF than patients in the CG (79.2% and 91.4%, respectively, p < .001) as well as better self-care concerning both the management of signs and symptoms (90.1% and 94.4% respectively, p = .004) and the prevention of complications (72.7% and 89.5%, respectively, p < .001). The study results suggest that the SISC-AVF had positive effects on patients in the IG.

Abstract
Aim Testing the validity and reliability of the Scale for the Environments Evaluation of Professional Nursing Practice (SEE-Nursing Practice). Background The environment of professional nursing practice is key to achieve better results for clients, nurses and institutions. Therefore, instruments enabling the assessment of all its attributes are required. Method Cross-sectional methodological study. The SEE-Nursing Practice, based on a previous qualitative study and literature review, was applied as a questionnaire. Exploratory and confirmatory factor analyses were used to assess construct validity. Results A total of 752 nurses participated in the study. Exploratory factor analysis of the SEE-Nursing Practice led to a factor solution with 93 items and three subscales. The Structure, Process and Outcome subscales, respectively, have 43, 37 and 13 items, loaded in 6 factors, 6 factors and 2 factors and explaining 62.6%, 59.2% and 67.4% of the total variance. Cronbach's alpha of the overall scale and of the 3 subscales was greater than 0.90. Confirmatory factor analysis showed a good fit. Conclusion SEE-Nursing Practice is a good valid and reliable instrument. Implications for nursing management The SEE-Nursing Practice enables assessing practice environments and is a tool for nursing managers in the definition of strategies ensuring favourable environments for nursing care quality.

Abstract
Background: Several guidelines recommend that patients with chronic kidney disease treated by haemodialysis (HD) take care of their own arteriovenous fistula (AVF). The dialysis nurse plays an important role in the development of such self-care behaviours. A very small number of instruments are available to assess self-care behaviours with AVF in Turkey. Objective: Cultural adaptation and psychometric testing of the Turkish version of the scale of assessment of self-care behaviours with arteriovenous fistula in haemodialysis (ASBHD-AVF) patients. Design: Cross-sectional validation study. Participants and Measurements: This study was conducted involving 160 patients in the Bolu region in Turkey. The guidelines provided by Sousa and Rojjanasrirat were taken into account in the scale translation, adaptation and validation process. Validity was analysed through content validity and construct validity. The latter was measured through principal component analysis with varimax rotation, considering only factor loadings of 0.30 or larger. Reliability analysis was based on internal consistency measured by Cronbach's alpha. Results: A two-factor structure was extracted explaining 59.01% of the total variance. Cronbach's alpha was 0.91, 0.85 and 0.84 for the overall scale, the self-care in prevention of complications subscale and the self-care in management of signs and symptoms subscale, respectively. Conclusions: The Turkish version of the scale of ASBHD-AVF patients is a reliable and valid instrument and can therefore be used.

Abstract
It is well known that conditional heteroscedasticity is exhibited by many economic and financial time series such as stock prices or returns. Empirical analysis is often based on a subseries obtained through systematically sampling from an underlying time series and we analyze how that can affect testing for heteroscedasticity. The results show the distribution of the test statistics is changed by systematic sampling, causing a serious power loss that increases with the sampling interval. Consequently, the tests often fail to reject the hypothesis of no conditional heteroscedasticity, leading to the wrong decision and missing the true nature of the data-generating process.