Parkinson's disease (PD), one of whose symptoms is dysphonia, is a prevalent neurodegenerative disease. The use of outdated diagnosis techniques, which yield inaccurate and unreliable results, continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical field. To solve this issue, the study proposes using machine learning and deep learning

Cellular respiration is an important process performed by mitochondria. Nad complex is the major complex involved in this process and one of the main subunits in this complex is the nad7 (nad dehydrogenase subunit 7). In Hordeum vulgare subsp. spontaneum, four nad7 cDNAs are described at 500 mM salinity, 0 h, or control (GenBank accession no. MW433884), after 2 h (GenBank accession no. MW433885)

In machine learning, searching for the optimal feature subset from the original datasets is a very challenging and prominent task. The metaheuristic algorithms are used in finding out the relevant, important features, that enhance the classification accuracy and save the resource time. Most of the algorithms have shown excellent performance in solving feature selection problems. A recently

Background: Taurine-upregulated gene 1 (TUG1) is one of the long noncoding RNAs (lncRNAs) that plays a role in melanogenesis. MicroRNA-377 (miRNA-377) is a conserved noncoding RNA that regulates angiogenesis and promotes oxidative stress. Peroxisome proliferator-activated receptors (PPARs) are components of the nuclear hormone receptor superfamily. PPAR-γ activators stimulate melanogenesis

Introduction: The hyper-catabolic state is a devastating pathophysiological response to severe injury, infection or burns. Nandrolone decanoate (ND) is a potent anabolic steroid have many clinical indications, but not investigated in burn injuries yet. Patients and methods: A prospective randomized control study included 40 burned patients who were treated in Burn unit from burn injuries ranged

Measuring phase noise in oscillators is crucial in communication systems, vibration analysis, and frequency synthesizers. Traditionally, this measurement is done in frequency domain by estimating the ratio of the power density at an offset frequency from the carrier to the power of the carrier signal. This approach is hardware intensive and dependent on the the offset frequency, for which there

Enhancing the exploration and exploitation phases of the metaheuristic (MH) optimization algorithms is the key to avoiding local optima. The Manta ray foraging optimizer is a recently proposed MH optimizer. The MRFO showed a good performance in the simple optimization problems. However, it is trapped into the local optimum in the more elaborated ones due to the original algorithm's low capability

Fractional-order spiking neuron models can enrich model flexibility and dynamics due to the extra degrees of freedom. This paper aims to study the effects of applying four different numerical methods to two fractional-order spiking neuron models: the Fractional-order Leaky integrate-and-fire (FO-LIF) model and the Fractional-order Hodgkin–Huxley (FO-HH) model. Furthermore, some adjustments to

Modeling of soft robotics systems proves to be an extremely difficult task, due to the large deformation of the soft materials used to make such robots. Reliable and accurate models are necessary for the control task of these soft robots. In this paper, a data-driven approach using machine learning is presented to model the kinematics of Soft Pneumatic Actuators (SPAs). An Echo State Network (ESN)

In this study, we propose the possibility of generating several parallel and independent random bitstreams from the time-varying optical emission spectra of an atmospheric pressure air microplasma system. This is achieved by splitting the plasma arc emission into discrete wavelengths using an optical spectrometer and then monitoring the fluctuating intensities of each wavelength as an independent