Modeling tumor growth using fractal calculus: Insights into tumor dynamics.

Important concepts like fractal calculus and fractal analysis, the sum of squared residuals, and Aikaike's information criterion must be thoroughly understood in order to correctly fit cancer-related data using the proposed models. The fractal growth models employed in this work are classified in three main categories: Sigmoidal growth models (Logistic, Gompertz, and Richards models), Power Law growth model, and Exponential growth models (Exponential and Exponential-Lineal models)". We fitted the data, computed the sum of squared residuals, and determined Aikaike's information criteria using Matlab and the web tool WebPlotDigitizer. In addition, the research investigates "double-size cancer" in the fractal temporal dimension with respect to various mathematical models.

Modeling Predictors of Medication Waste Reduction Intention in Algeria: Extending the Theory of Planned Behavior.

COVID-19 caused an increase in the demand for medications, which led to an increase in pharmaceutical waste and there is no doubt that this contributes to environmental pollution. Hence, it became necessary to search for how to protect and improve the environment by encouraging the behavior of medication waste reduction. Accordingly, this study aims to investigate the factors affecting intentions to reduce medication waste. Considering this, we develop an extended theory of planned behavior (TPB) framework by incorporating the constructs of moral obligation, environmental awareness, and medication waste risk perception. Using the convenience sampling method and based on a self-administered questionnaire, a total of 225 usable responses were collected in five Algerian cities. The results showed that positive attitudes (ß = 0.316, p < 0.001), moral obligation (ß = 0.291, p < 0.001), environmental awareness (ß = 0.227, p < 0.001), perceived behavior control (PBC) (ß = 0.151, p = 0.001), greater perceived risks (ß = 0.127, p < 0.001), and subjective norm (ß = 0.096, p < 0.05) significantly and positively influence the medication waste minimization intention. Furthermore, our analyses revealed that the extended TPB model explained 73.40% of the intention variance. In conclusion, we have explored the intentions, and there may be a gap between intent and actual behavior. Therefore, we recommend future studies to examine the factors affecting the actual behavior of medication waste reduction and to investigate environmental ethics and religious commitment as predictors of waste reduction intentions.