Articles
Results in Engineering (25901230)pp. 71-82
The purpose of this study is to present a comprehensive framework for analyzing contagious diseases. The primary objective is to determine whether the outbreak dynamics of a contagious disease follow a constant or variable non-integer order. The methodology involves a three-phase process: selecting an appropriate model, estimating its parameters, and identifying the order of derivation. To address this, the SEIAR non-integer order dynamic model is employed, enhancing the precision of disease spread estimation. A heuristic approach is proposed for parameter estimation using a Genetic Optimization Algorithm, which evaluates all possible scenarios for the order and suggests parameter sets that perform well across these scenarios. Subsequently, an adaptive identification method is introduced to estimate the variable order of the model while keeping the parameters constant. The approach is validated on the Delta and Omicron variants of the Coronavirus epidemic in Iran. The variable-order model achieves a Mean Absolute Percentage Error (MAPE) of 0.80 % for the Delta variant and 0.51 % for the Omicron variant, significantly outperforming the best constant-order models with MAPEs of 0.92 % and 1.32 %, respectively. These results demonstrate the model's superior accuracy in predicting the epidemic's progression. These findings significantly contribute to the understanding and management of contagious diseases. Evidence is provided that the pandemic in Iran follows a variable non-integer order dynamic model, supporting the hypothesis that disease outbreaks exhibit variable non-integer order behavior due to their inherent complexity. The proposed framework can be generalized to other diseases and regions, offering a robust tool for epidemic analysis and decision-making. © 2025
Journal of Mathematical Analysis and Applications (10960813)543(2)
In this paper, we first compute the Banaś modulus of smoothness of Lp(μ), which gives a solution to the problem posed by Banaś in 1986 (see Problem 4 of Banas (1986) [1]). Then, we introduce and calculate Gao Pythagorean constant of Lp(μ), which extends and improves some main results of Gao (2006) [3]. © 2024 Elsevier Inc.
Pezeshki L.,
Sadeghian, H.,
Mohebbi A.,
Keshmiri m., M.,
Haddadin S.,
Amini harandi, A.,
László, S. IEEE Transactions on Automation Science and Engineering (15455955)pp. 13298-13309
Recent studies underscore the importance of the patient’s active contribution and voluntary effort in enhancing therapy outcomes in physical rehabilitation. This paper presents an adaptive control scheme to implement active robotic rehabilitation. The primary goal is to dynamically regulate robotic assistance based on the patient’s performance and individual conditions, encouraging active participation, and effective therapy. To achieve this, a Lyapunov-based adaptive algorithm is developed that dynamically adjusts the admittance parameters by balancing the error and effort minimization. A novel performance index based on human energy input enables real-time identification of the intended human sharing role. This index is used as an adaptive rate in the proposed algorithm to enhance the control system’s dynamic responsiveness to changes in human performance. The proposed approach achieves two main rehabilitation objectives. First, it encourages active and safe human participation. Second, it enhances the therapy by providing personalized assistance, tailored to individual abilities and conditions, and thus reduces the need for therapist intervention. The performance of the proposed approach is illustrated in experimental studies. The results demonstrate the adaptability of the algorithm, ensuring compliant and safe interaction and effective task completion. © 2004-2012 IEEE.
Applied Neuropsychology: Adult (23279095)
Executive functions are frequently impaired in individuals with epilepsy. Understanding the patterns of these dysfunctions is essential for effective management of epileptic patients. To comprehend these patterns, we aimed to investigate executive function performance in adult epileptic patients. Thirty adults with epilepsy, along with fifty healthy controls matched for age, gender, and education were administered standard performance-based executive tasks, including Digit Span Forward and Backward, Trail Making Test A and B, Design Fluency Regular and Irregular, and Semantic Verbal Fluency. Results indicated that Digit Span Forward and Backward tests were the most frequently impaired, with 80% and 90% of patients showing impairments, respectively. The Semantic Verbal Fluency task had the lowest frequency of impairment, with a 30% prevalence among patients. Additionally, a higher frequency of seizures significantly predicted longer completion times for Trail Making Test A (beta = 0.281, p = 0.030) and Trail Making Test B (beta = 0.586, p = 0.001), as well as lower total executive function scores (beta = −0.429, p = 0.000). No significant associations were found between executive function and age of onset or number of antiepileptic drugs. Our results indicate that adult epileptic patients display substantial executive dysfunction, particularly in working memory and cognitive flexibility and highlight the detrimental effect of inadequately controlled epilepsy and high seizure frequency on exacerbating these impairments. This underscores the importance of regular executive function assessments in the management of epileptic patients, tailored to individual needs and performance levels, to optimize care and improve quality of life. © 2025 Taylor & Francis Group, LLC.
