scholarly journals Modeling of blood microcirculation, heat and mass transfer in human tissues

2018 ◽  
pp. 58-61
Author(s):  
N. Kizilova ◽  
A. Korobov
Keyword(s):  
Binary Tree ◽  
Flow Distribution ◽  
Biological Tissues ◽  
Homogeneous Distribution ◽  
Monitoring Systems ◽  
Energy Costs ◽  
Minimal Energy ◽  
Blood Microcirculation ◽  
Computer Based ◽  
Optimal Values

A mathematical model of the structure of the blood vessels system which provides blood microcirculation in the superficial tissues of human, namely the skin, to provide blood supply as a fluid, which heats / cools, and determines thermoregulation in changes of ambient temperature and overheating / supercooling is proposed. The model is based on data from current studies of the structure of microcirculatory beds based on microCT technologies. The microvascular system is modeled as a fractal binary tree optimized for uniform supply of a nutrient fluid (blood for biological tissues) due to the homogeneous distribution of capillaries, optimal values for diameters, lengths and branching angles in bifurcations of tubes that provide flow distribution with minimal energy costs. The model has been developed to use in computer-based monitoring systems for the planning of physiotherapy procedures for different diseases.

Prediction of Blood Flow Distribution in Liver Radioembolization Using Convolutional Neural Networks

2020 ◽  
Author(s):  
Amirtahà Taebi ◽  
Catherine T. Vu ◽  
Emilie Roncali
Keyword(s):  
Blood Flow ◽  
Cfd Simulation ◽  
Mean Squared Error ◽  
Flow Distribution ◽  
Homogeneous Distribution ◽  
Blood Flow Distribution ◽  
Cfd Simulations ◽  
Squared Error ◽  
Network Output ◽  
Yttrium 90

Abstract We have developed a new dosimetry approach, called CFDose, for liver cancer radioembolization based on computational fluid dynamics (CFD) simulation in the hepatic arterial tree. Although CFDose overcomes some of the limitations of the current dosimetry methods such as the unrealistic assumption of homogeneous distribution of yttrium-90 in the liver, it suffers from the expensive computational cost of CFD simulations. To accelerate CFDose, we introduce a deep learning model to predict the blood flow distribution between the liver segments in a patient with hepatocellular carcinoma. The model was trained with the results of CFD simulations under different outlet boundary conditions. The model consisted of convolutional, average pooling and transposed convolution layers. A regression layer with a mean-squared-error loss function was utilized at the network output to estimate the arterial outlet blood flow. The mean-squared error and prediction accuracy were calculated to measure model performance. Results showed that the average difference between the CFD results and predicted flow data was less than 2.45% for all the samples in the test dataset. The proposed model thus estimated the blood flow distribution with high accuracy significantly faster than a CFD simulation. The network output can be used to estimate the yttrium-90 dose distribution in the liver in future studies.

scholarly journals Reference Breast Phantoms for Low-Cost Microwave Imaging

2020 ◽  
Vol 14 (4) ◽  
pp. 411-415
Author(s):  
Emine Avşar Aydin ◽  
Selin Yabaci Karaoğlan
Keyword(s):  
Breast Cancer ◽  
Low Cost ◽  
Microwave Frequency ◽  
Biological Tissues ◽  
Microwave Imaging ◽  
Vector Network Analyzers ◽  
Network Analyzers ◽  
Computer Based ◽  
Breast Phantoms ◽  
Inverse Radon Transform

Microwave imaging provides an alternative method for breast cancer screening and the diagnosis of cerebrovascular accidents. Before a surgical operation, the performance of microwave imaging systems should be evaluated on anatomically detailed anthropomorphic phantoms. This paper puts forward the advances in the development of breast phantoms based on 3D printing structures filled with liquid solutions that mimic biological tissues in terms of complex permittivity in a wide microwave frequency band. In this paper; four different experimental scenarios were created, and measurements were performed, and although there are many vector network analyzers on the market, the miniVNA used in this study has been shown to have potential in many biomedical applications such as portable computer-based breast cancer detection studies. We especially investigated the reproducibility of a particular mixture and the ability of some mixes to mimic various breast tissues. Afterwards, the images similar to the experimentally created scenarios were obtained by implementing the inverse radon transform to the obtained data.

scholarly journals A monitoring system for evaluation of COVID-19 infection risk

2021 ◽  
Vol 2069 (1) ◽  
pp. 012192
Author(s):  
Jevgenis Telicko ◽  
Daniels Dagis Vidulejs ◽  
Andris Jakovics
Keyword(s):  
Artificial Intelligence ◽  
Risk Evaluation ◽  
Medical Personnel ◽  
Infection Risk ◽  
Measured Data ◽  
Monitoring Systems ◽  
Risk Of Infection ◽  
Review Of The Literature ◽  
Indirect Measurements ◽  
Computer Based

Abstract Monitoring systems allow operators to accomplish the greatest comfort indoors, but, as a rule, the available parameters are not enough to analyse the epidemiological threat in buildings. Due to the pandemic and increasing incidence of the disease, there is a need for monitoring systems that can provide the necessary information to analyse the risk of infection. With timely notification of people about the risks, such a system could not only increase safety in buildings, but also save crucial resources such as the work of medical personnel. This paper presents an example of real-world implementation of a cheap and scalable system to indicate risks and inform people inside. To achieve this, an appropriate set of sensors and communication protocols was selected, and processing of indirect measurements with artificial intelligence (AI) algorithms was carried out on an embedded Jetson Nano computer. Based on the experiments and a review of the literature, the necessary parameters for measurements were selected. Detailed analysis of measured data for risk evaluation is provided in [1].

scholarly journals MINIMIZATION OF NONRESONANT EFFECTS IN A SCALABLE ISING SPIN QUANTUM COMPUTER

2004 ◽  
Vol 02 (03) ◽  
pp. 379-392 ◽  
Author(s):  
G. P. BERMAN ◽  
D. I. KAMENEV ◽  
V. I. TSIFRINOVICH
Keyword(s):  
Magnetic Field ◽  
External Magnetic Field ◽  
Quantum Computer ◽  
One Dimensional ◽  
Ising Spin ◽  
Spin Quantum ◽  
Computer Based ◽  
Frequency Offsets ◽  
Optimal Values ◽  
Large Frequency

The errors caused by the transitions with large frequency offsets (nonresonant transitions) are calculated analytically for a scalable solid-state quantum computer based on a one-dimensional spin chain with Ising interactions between neighboring spins. Selective excitations of the spins are enabled by a uniform gradient of the external magnetic field. We calculate the probabilities of all unwanted nonresonant transitions associated with the flip of each spin with nonresonant frequency and with flips of two spins: one with resonant and one with nonresonant frequencies. It is shown that these errors oscillate with changing gradient of the external magnetic field. Choosing the optimal values of this gradient allows us to decrease these errors by 50%.

scholarly journals Predicting the minimal energy costs of human walking

1991 ◽  
Vol 23 (4) ◽  
pp. 491???498 ◽  
Author(s):  
KENNETH G. HOLT ◽  
JOSEPH HAMILL ◽  
ROBERT O. ANDRES
Keyword(s):  
Human Walking ◽  
Energy Costs ◽  
Minimal Energy

Monitoring of Electrical Parameters into Island Grid Integrating Renewable Energy Sources

2013 ◽  
Vol 368-370 ◽  
pp. 346-349 ◽  
Author(s):  
Adrian Oprea ◽  
Florin Dragomir ◽  
Otilia Elena Dragomir ◽  
Nicolae Olariu ◽  
Liviu Olteanu
Keyword(s):  
Renewable Energy ◽  
Energy Supply ◽  
Renewable Energy Sources ◽  
Monitoring Systems ◽  
Optimal Timing ◽  
Electrical Parameters ◽  
Security Of Supply ◽  
Computer Based ◽  
Real Time Information ◽  
Time Information

Renewable energy source (RES) enables us to diversify our energy supply. This increases our security of supply and improves European competitiveness creating new industries, jobs, economic growth and export opportunities, whilst also reducing our greenhouse gas emissions. The monitoring systems are widely used in RES applications in order to collect data regarding the installed system performance, for evaluation purposes. In this article, the development of a computer-based system for RES systems monitoring is described. This article proposes a tool dedicated to real-time information of electricity and thus implicitly the optimal timing for use of electricity. The proposed system consists for measuring electrical parameters (photovoltaics voltage and current etc.).

scholarly journals Energy efficiency analysis of air dehumidification methods that determine safe microclimatic working conditions

2021 ◽  
pp. 2-12
Author(s):  
Viktor V. Deryushev ◽  
Evgeniy E. Kosenko ◽  
Vera V. Kosenko ◽  
Mikhail A. Krivchuk ◽  
Ilya V. Deryushev ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Working Conditions ◽  
Energy Costs ◽  
Minimal Energy ◽  
Comparative Efficiency ◽  
Operating Modes ◽  
Efficiency Assessment ◽  
Adsorption Of Water ◽  
Adsorption Of Water Vapor ◽  
Efficiency Indicators

Introduction. The article deals with the issues related to provision of air humidity parameters required for non-hazardous operation of various technical facilities. Problem Statement. The paper considers analytical methods for energy efficiency assessment of adsorption and condensation methods of air dehumidification, which provide safe microclimatic working conditions, and the influence of the operating modes of dehumidifying plants on the parameters of the microclimate. Theoretical Part. As indicators of the energy efficiency of each of the methods, it is proposed to use the energy costs that are minimally necessary for the implementation of ideal physical dehumidification processes and per unit mass of water units emitted from air. This ensures safe and comfortable microclimatic working conditions with minimal energy costs. The ratio of the specific energy costs of the condensation and adsorption methods shows their comparative efficiency. An electronic Id-diagram was used to determine the air parameters in the implemented dehumidification processes (cooling, condensation and adsorption of water vapor). Conclusion. Analytical dependences are obtained for the analyzed energy efficiency indicators that provide safe and comfortable microclimatic working conditions with minimal energy costs. Numerical estimates were carried out according to the most probable modes of dehumidification processes and air parameters. The parametric restrictions on the implementation of the adsorption dehumidification method are justified, in which it becomes energetically more profitable. The conditions under which it is possible to implement a combined dehumidification method to ensure safe microclimatic working conditions are determined.

scholarly journals Deep Learning Assisted Automatic Methodology for Implanted MIMO Antenna Designs on Large Ground Plane

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 47
Author(s):  
Lida Kouhalvandi ◽  
Ladislau Matekovits ◽  
Ildiko Peter
Keyword(s):  
Biomedical Applications ◽  
Deep Neural Network ◽  
Ground Plane ◽  
Biological Tissues ◽  
Design Parameters ◽  
Mimo Antenna ◽  
Mimo Antennas ◽  
Multiple Input ◽  
Layout Generation ◽  
Optimal Values

This paper provides a novel methodology for designing implanted multiple-input and multiple-output (MIMO) antennas in the automatic fashion. The proposed optimization consists of two sequential phases for firstly configuring the geometry of an implanted MIMO antenna and then sizing the design parameters through the hierarchy top-down optimization (TDO) and regression deep neural network (DNN), respectively. It tackles the difficulty in constructing the structure of antennas and also provides optimal values for the determined variables, sufficiently. This methodology results in valid electromagnetic (EM)-verified post-layout generation that is ready-to-fabricate. The effectiveness of the proposed optimization-oriented method is verified by designing and optimizing the implanted MIMO antenna in the frequency band of 4.34–4.61 GHz and 5.86–6.64 GHz suitable for medical applications at the emerging wireless band. For our design, we employ the actual biological tissues as bone, liquid (%1 sodium chloride, %40 sugar in distilled water), and plexiglass surroundings with a bio-compatible substrate, as aluminium oxide on a large ground plane, that is suitable to be used in a particular biomedical applications involving smart implants.

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