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Natural Products as Geroprotective Modulators in Diabetic Nephropathy: A Mechanistic Framework Integrating Aging Hallmarks and the AMPK–SIRT1–Nrf2 Axis

Aging and Cancer, EarlyView.
Natural products target the aging kidney in diabetic nephropathy by restoring the AMPK–SIRT1–Nrf2 axis, reducing oxidative stress, inflammation, fibrosis, and cellular senescence while enhancing mitochondrial biogenesis and antioxidant defenses.
Sherif Hamidu, Latif Adams, Eunice Ampem‐Danso, Justice Kumi, Abigail Aning, Fatima Hamidu, Mustapha Abdul Mumin Mohammed, Ayuba Nii Darku Ankrah, Seth Kwabena Amponsah   +8 more
wiley   +1 more source

Detection and Classification of ADHD Using Deep Learning Based on EEG Signals

Xinyu Liu
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NONLINEAR SIGNAL CLASSIFICATION

International Journal of Bifurcation and Chaos, 2002
In this contribution, we show that the incorporation of nonlinear dynamical measures into a multivariate discrimination provides a signal classification system that is robust to additive noise. The signal library was composed of nine groups of signals.
P. E. Rapp, T. A. A. Watanabe, Philippe Faure, C. J. Cellucci   +3 more
openaire   +2 more sources

Classification of transient signals (acoustic signals)

ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003
The authors are concerned with the classification of transient signals. Spectral ratio distance measures operating on the parametric spectra of the transient signals are used to perform classification. Performance of the classification algorithm is studied analytically and experimentally using both synthetic and real data.
Khosrow Lashkari, Benjamin Friedlander, J. Abel, B. McQuiston   +3 more
openaire   +1 more source

Pattern Classification of Phylogeny Signals

Statistical Applications in Genetics and Molecular Biology, 2008
In this paper we propose the minimum entropy clustering (MEC) method for clustering genes based on their phylogenetic signals. This entropy based method will cluster two genes together when their concatenation can decrease the entropy. An integral feature of MEC is that it chooses the number of clusters automatically, which is a major advantage over ...
Xiaofei, Shi, Hong, Gu, Chris, Field
openaire   +2 more sources

Signal averaging and shape classification

Images of the Twenty-First Century. Proceedings of the Annual International Engineering in Medicine and Biology Society, 2003
Signal averaging in equal-shape and equal-width signal classes is discussed. The aim is to compare two similarity criteria associated with the same clustering algorithm; one derived from the distribution function method and the other derived from correlation.
Rix, Hervé, Thierry, Eric, Caminal, Pere, Jané, Raimon   +3 more
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Analysis and classification of snoring signals

ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
Snoring is a very common phenomenon with both social and clinical effects. The need for a reliable and effective monitoring and analyzing system, for the snoring signal, stems from the recent awareness of the severity of the problem and from the fact that surgical correction procedures are now available.
A. Cohen, A. Lieberman
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Supervised radar signal classification

2016 International Joint Conference on Neural Networks (IJCNN), 2016
This work investigates radar signal classification and source identification using three classification models: Neural Networks (NN), Support Vector Machines (SVM) and Random Forests (RF). The available large dataset consists of pulse train characteristics such as signal frequencies, type of modulation, pulse repetition intervals, scanning type, scan ...
Ivan Jordanov, Nedyalko Petrov, Alessio Petrozziello   +2 more
openaire   +1 more source