Aging and age-related ailments have emerged as critical challenges and great burdens within the global contemporary society.Addressing these concerns is an imperative task,with the aims of postponing the aging process...Aging and age-related ailments have emerged as critical challenges and great burdens within the global contemporary society.Addressing these concerns is an imperative task,with the aims of postponing the aging process and finding effective treatments for age-related degenerative diseases.Recent investigations have highlighted the significant roles of nicotinamide adenine dinucleotide(NAD+)in the realm of anti-aging.It has been empirically evidenced that supplementation with nicotinamide mononucleotide(NMN)can elevate NAD+levels in the body,thereby ameliorating certain age-related degenerative diseases.The principal anti-aging mechanisms of NMN essentially lie in its impact on cellular energy metabolism,inhibition of cell apoptosis,modulation of immune function,and preservation of genomic stability,which collectively contribute to the deferral of the aging process.This paper critically reviews and evaluates existing research on the anti-aging mechanisms of NMN,elucidates the inherent limitations of current research,and proposes novel avenues for anti-aging investigations.展开更多
Due to recent fluctuations in cryptocurrency prices,Ethereum has gained recognition as an investment asset.Given its volatile nature,there is a significant demand for accurate predictions to guide investment choices.T...Due to recent fluctuations in cryptocurrency prices,Ethereum has gained recognition as an investment asset.Given its volatile nature,there is a significant demand for accurate predictions to guide investment choices.This paper examines the most influential features of the daily price trends of Ethereum using a novel approach that combines the Random Forest classifier and the ReliefF method.Integrating the Adaptive Neuro-Fuzzy Inference System(ANFIS)and Short-Time Fourier Transform(STFT)results in high accuracy and performance metrics for Ethereum price trend predictions.This method stands out from prior research,primarily based on time series analysis,by enhancing pattern recognition across time and frequency domains.This adaptability leads to better prediction capabilities with accuracy reaching 76.56%in a highly chaotic market such as cryptocurrency.The STFT’s ability to reveal cyclical trends in Ethereum’s price provides valuable insights for the ANFIS model,leading to more precise predictions and addressing a notable gap in cryptocurrency research.Hence,compared to models in literature such as Gradient Boosting,Long Short-Term Memory,Random Forest,and Extreme Gradient Boosting,the proposed model adapts to complex data patterns and captures intricate non-linear relationships,making it well-suited for cryptocurrency prediction.展开更多
文摘Aging and age-related ailments have emerged as critical challenges and great burdens within the global contemporary society.Addressing these concerns is an imperative task,with the aims of postponing the aging process and finding effective treatments for age-related degenerative diseases.Recent investigations have highlighted the significant roles of nicotinamide adenine dinucleotide(NAD+)in the realm of anti-aging.It has been empirically evidenced that supplementation with nicotinamide mononucleotide(NMN)can elevate NAD+levels in the body,thereby ameliorating certain age-related degenerative diseases.The principal anti-aging mechanisms of NMN essentially lie in its impact on cellular energy metabolism,inhibition of cell apoptosis,modulation of immune function,and preservation of genomic stability,which collectively contribute to the deferral of the aging process.This paper critically reviews and evaluates existing research on the anti-aging mechanisms of NMN,elucidates the inherent limitations of current research,and proposes novel avenues for anti-aging investigations.
基金support from Wenzhou-Kean University Academy of Interdisciplinary Research for Sustainability(WKU-AIRs),China.
文摘Due to recent fluctuations in cryptocurrency prices,Ethereum has gained recognition as an investment asset.Given its volatile nature,there is a significant demand for accurate predictions to guide investment choices.This paper examines the most influential features of the daily price trends of Ethereum using a novel approach that combines the Random Forest classifier and the ReliefF method.Integrating the Adaptive Neuro-Fuzzy Inference System(ANFIS)and Short-Time Fourier Transform(STFT)results in high accuracy and performance metrics for Ethereum price trend predictions.This method stands out from prior research,primarily based on time series analysis,by enhancing pattern recognition across time and frequency domains.This adaptability leads to better prediction capabilities with accuracy reaching 76.56%in a highly chaotic market such as cryptocurrency.The STFT’s ability to reveal cyclical trends in Ethereum’s price provides valuable insights for the ANFIS model,leading to more precise predictions and addressing a notable gap in cryptocurrency research.Hence,compared to models in literature such as Gradient Boosting,Long Short-Term Memory,Random Forest,and Extreme Gradient Boosting,the proposed model adapts to complex data patterns and captures intricate non-linear relationships,making it well-suited for cryptocurrency prediction.
