We study the influence of a dissipation process on diffusion dynamics triggered by fluctuations with long-range correlations. We make the assumption that the perturbation process involved is of the same kind as those recently studied numerically and theoretically, with a good agreement between theory and numerical treatment. As a result of this assumption the equilibrium distribution departs from the ordinary canonical distribution. The distribution tails are truncated, the distribution border is signaled by sharp peaks, and, in the weak dissipation limit, the central distribution body becomes identical to a truncated Levy distribution.
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http://dx.doi.org/10.1103/physreve.61.4801 | DOI Listing |
JMIR Med Educ
January 2025
College of Medicine, Alfaisal University, Takhasussi street, Riyadh, 11533, Saudi Arabia, 966 559441589.
Background: There has been a rise in the popularity of ChatGPT and other chat-based artificial intelligence (AI) apps in medical education. Despite data being available from other parts of the world, there is a significant lack of information on this topic in medical education and research, particularly in Saudi Arabia.
Objective: The primary objective of the study was to examine the familiarity, usage patterns, and attitudes of Alfaisal University medical students toward ChatGPT and other chat-based AI apps in medical education.
JCO Glob Oncol
January 2025
Department of Public Health, Myungsung Medical College, Addis Ababa, Ethiopia.
Purpose: To analyze survival and its predictors among patients with hepatocellular carcinoma (HCC) receiving transarterial chemoembolization (TACE) in Ethiopia.
Materials And Methods: We conducted a retrospective cohort study among patients who received TACE for HCC at MCM Hospital from December 1, 2016, to December 31, 2022. Data were extracted from patients' medical records, and vital status was ascertained from the patients' charts or by phone call to the next of kin.
JCO Glob Oncol
January 2025
Department of Global Pediatric Medicine, St Jude Children's Research Hospital, Memphis, TN.
Purpose: The academic field of global pediatric oncology is expanding as cancer becomes increasingly recognized as a global health priority for children and adolescents. Here, we aimed to explore the representation of authors, the geographic distribution of research, and the research approaches being used in global pediatric oncology.
Methods: Articles published in () and on the topic of global pediatric oncology were analyzed.
Proc Natl Acad Sci U S A
February 2025
Computer Science, School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134.
As knowledge accumulates in science and society in a distributed fashion, erroneous derivations can be introduced into the corpus of knowledge. Such derivations can compromise the validity of any units of knowledge that rely on them in the future. Can societal knowledge maintain some level of integrity given simple distributed error-checking mechanisms? In this paper, we investigate the following formulation of the question: assuming that a constant fraction of the new derivations is wrong, is it possible for simple error-checking mechanisms that apply when a new unit of knowledge is derived to maintain the integrity of the corpus of knowledge? This question was introduced by Ben-Eliezer et al.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, Liaoning, China.
To address the susceptibility of conventional vector control systems for permanent magnet synchronous motors (PMSMs) to motor parameter variations and load disturbances, a novel control method combining an improved Grasshopper Optimization Algorithm (GOA) with a variable universe fuzzy Proportional-Integral (PI) controller is proposed, building upon standard fuzzy PI control. First, the diversity of the population and the global exploration capability of the algorithm are enhanced through the integration of the Cauchy mutation strategy and uniform distribution strategy. Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima.
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