Artificial intelligence-based approaches for modeling the effects of spirulina growth mediums on total phenolic compounds.

Spirulina is a microalga and its phenolic compound is affected by growth mediums. In this study, Artificial intelligence (AI) based models, namely the Adaptive-Neuro Fuzzy Inference System (ANFIS) and Multilayer perceptron (MLP) models, and Step-Wise-Linear Regression (SWLR) were used to predict total phenolic compounds (TPC) of the spirulina algae. Spirulina productivity (P), extraction yield (EY), total flavonoids (TF), percent of flavonoid (%F) and percent of phenols (%P) are considered as input variables with the corresponding TPC as an output variable.

Reliability and validity of the Salford-Scott Nursing Values Questionnaire in Turkish.

Background: Developing professional values among nursing students is important because values are a significant predictor of the quality care that will be provided, the clients' recognition, and consequently the nurses' job satisfaction. The literature analysis showed that there is only one validated tool available in Turkish that examines both the personal and the professional values of nursing students.

Objective: The aim of this study was to assess the reliability and validity of the Salford-Scott Nursing Values Questionnaire in Turkish.

Think globally, act locally: understanding sexual harassment from a cross-cultural perspective.

Objectives: Sexual harassment in medical education has been studied in the Americas, Europe and Asia; however, little is known about sexual harassment in Middle Eastern cultures. Our initial aim was to describe the sexual harassment of female doctors-in-training by male patients and their relatives in Turkey. During our analysis of data, we expanded our objectives to include the formulation of a framework that can provide a theoretical background to enhance medical educators' understanding of sexual harassment across cultures.