The Spotlight Effect, defined as individuals' tendency to overestimate the extent to which others notice and evaluate them, has important implications for psychological functioning, social interaction, and performance in educational and sport environments. Despite previous studies have addressed the Spotlight Effect theoretically and empirically, no validated instrument has been specifically developed to assess this construct especially among students of Colleges of Physical Education and Sport Sciences. This study aimed to develop and validate a Spotlight Effect Scale and establishing normative levels for its interpretation. The descriptive survey approach was used, involving 555 students from Colleges of Physical Education and Sport Sciences across all stages of scale development. The final scale consists of 21 items representing three dimensions: cognitive, emotional, and behavioral, with seven items per dimension. Based on the theoretical framework adopted in the present study, the researchers hypothesized a three-component structure, and the factor analysis results were consistent with this proposed structure. The three components explained 58.754% of the total variance, with a KMO value of .895 and a significant Bartlett's test (p < .001). The scale demonstrated high internal consistency, with Cronbach's alpha of .950 for the total scale and ranging from .868 to .911 across the three dimensions. The findings indicate that the developed scale provides a valid and reliable standardized measure of the Spotlight Effect among university students in sport sciences and may support future research and educational and counseling applications. This serves one of the Sustainable Development Goals (quality education).
A simple, low cost and rapid flow injection turbidimetric method was developed and validated for mebeverine hydrochloride (MBH) determination in pharmaceutical preparations. The developed method is based on forming of a white, turbid ion-pair product as a result of a reaction between the MBH and sodium persulfate in a closed flow injection system where the sodium persulfate is used as precipitation reagent. The turbidity of the formed complex was measured at the detection angle of 180° (attenuated detection) using NAG dual&Solo (0-180°) detector which contained dual detections zones (i.e., measuring cells 1 & 2). The increase in the turbidity of the complex was directly proportional to the increase of the MBH concentration
... Show MoreA fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th
... Show MoreA recent study compared experimentally the hydraulic and thermal activity of twisted tape inserts for two types, metal foam twisted tape (MFTT) and traditional twisted tape (TTT), in a double pipe heat exchanger. The investigation goal of the innovatively designed MFTT is to enhance the heat transfer process, which provides a higher thermal enhancement factor over those of TTT under the same conditions. Heat transfer activity in terms of Nusselt number (
The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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