Evaluating Communication Performance in Rotating Electrical Machines Using RSSI Measurements and Artificial Intelligence.

This paper introduces a novel methodology for evaluating communication performance in rotating electric machines using Received Signal Strength Indication (RSSI) measurements coupled with artificial intelligence. The proposed approach focuses on assessing the quality of wireless signals in the complex, dynamic environment inside these machines, where factors like reflections, metallic surfaces, and rotational movements can significantly impact communication. RSSI is used as a key parameter to monitor real-time signal behavior, enabling a detailed analysis of communication reliability.

Editorial for the Special Issue on Piezoelectric Nanogenerators for Micro-Energy and Self-Powered Sensors.

Energy harvesting consists of scavenging energy from the surrounding environment knowing that this energy would be "lost" if not scavenged [...

Cardiac Cell Exposure to Electromagnetic Fields: Focus on Oxdative Stress and Apoptosis.

Exposure to electromagnetic fields (EMFs) is a sensitive research topic. Despite extensive research, to date there is no evidence to conclude that exposure to EMFs influences the cardiovascular system. In the present study, we examined whether 915 MHz EMF exposure affects myocardial antioxidative and apoptotic status in vitro and in vivo.

Physiologically Based Pharmacokinetic Modelling for Nicotine and Cotinine Clearance in Pregnant Women.

Physiologically based pharmacokinetic (PBPK) models for the absorption, disposition, metabolism and excretion (ADME) of nicotine and its major metabolite cotinine in pregnant women (p-PBPK) are rare. The aim of this short research report is to present a p-PBPK model and its simulations for nicotine and cotinine clearance. The maternal-placental-fetal compartments of the p-PBPK model contain a total of 16 compartments representing major maternal and fetal organs and tissue groups.

Prediction and detection of human epileptic seizures based on SIFT-MS chemometric data.

Although epilepsy is considered a public health issue, the burden imposed by the unpredictability of seizures is mainly borne by the patients. Predicting seizures based on electroencephalography has had mixed success, and the idiosyncratic character of epilepsy makes a single method of detection or prediction for all patients almost impossible. To address this problem, we demonstrate herein that epileptic seizures can not only be detected by global chemometric analysis of data from selected ion flow tube mass spectrometry but also that a simple mathematical model makes it possible to predict these seizures (by up to 4 h 37 min in advance with 92% and 75% of samples correctly classified in training and leave-one-out-cross-validation, respectively).

A quadratic linear-parabolic model-based EEG classification to detect epileptic seizures.

The two-point central difference is a common algorithm in biological signal processing and is particularly useful in analyzing physiological signals. In this paper, we develop a model-based classification method to detect epileptic seizures that relies on this algorithm to filter electroencephalogram (EEG) signals. The underlying idea was to design an EEG filter that enhances the waveform of epileptic signals.

A coupled one dimension and transmission line model for arterial flow simulation.

A broad choice of numerical schemes and methods currently exists for blood flow simulations. The results rely critically on the prescription of boundary conditions. The outflow boundary condition for a one-dimensional (1D) flow solver is usually prescribed via a Windkessel or lumped parameter model.

A computational model for hepatotoxicity by coupling drug transport and acetaminophen metabolism equations.

The spatial distributions of cytochrome P450 (CYP450) and glutathione (GSH) in liver lobules determine the heterogeneous hepatotoxicity of acetaminophen (APAP). Their interplay in conjunction with blood flow is not well understood. In this paper, we integrate a cellular APAP metabolism model with a sinusoidal blood flow to simulate the temporal-spatial patterns of APAP-induced hepatotoxicity.

UGT76G1 polymorphism in Stevia rebaudiana: New variants for steviol glycosides conjugation.

Steviol glycosides (SVglys) are secondary metabolites derived from terpenoids exhibiting high-sweetening properties produced in Stevia rebaudiana leaves. Their great diversity is due to the number, the position and the nature of glycosylations on the steviol aglycone. Steviol conjugation is mediated by uridine-diphosphate glycosyltransferases (UGTs).

Novel methods for segment-specific blood flow simulation for the liver.

One challenge for hepatic flow simulation is to divide the hepatic vasculature into individual Couinaud segments, and to simulate flow at both segmental and organ levels. We propose to integrate a segment simulation algorithm with the flow solver in a Constructive Constraint Optimisation (CCO) algorithm to address this problem. In this way blood flow simulations can be conducted for large segment-specific vasculatures as relevant to surgical procedures.

Roadmap for cardiovascular circulation model.

Computational models of many aspects of the mammalian cardiovascular circulation have been developed. Indeed, along with orthopaedics, this area of physiology is one that has attracted much interest from engineers, presumably because the equations governing blood flow in the vascular system are well understood and can be solved with well-established numerical techniques. Unfortunately, there have been only a few attempts to create a comprehensive public domain resource for cardiovascular researchers.

Fast blood-flow simulation for large arterial trees containing thousands of vessels.

Blood flow modelling has previously been successfully carried out in arterial trees to study pulse wave propagation using nonlinear or linear flow solvers. However, the number of vessels used in the simulations seldom grows over a few hundred. The aim of this work is to present a computationally efficient solver coupled with highly detailed arterial trees containing thousands of vessels.

Hierarchical traits distances explain grassland Fabaceae species' ecological niches distances.

Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.

Lactobacillus amylovorus inhibits the TLR4 inflammatory signaling triggered by enterotoxigenic Escherichia coli via modulation of the negative regulators and involvement of TLR2 in intestinal Caco-2 cells and pig explants.

Inflammation derived from pathogen infection involves the activation of toll-like receptor (TLR) signaling. Despite the established immunomodulatory activities of probiotics, studies relating the ability of such bacteria to inhibit the TLR signaling pathways are limited or controversial. In a previous study we showed that Lactobacillus amylovorus DSM 16698T, a novel lactobacillus isolated from unweaned pigs, protects the intestinal cells from enterotoxigenic Escherichia coli (ETEC) K88 infection through cytokine regulation.