Next Issue
Volume 42, 2020
Previous Issue
Volume 42, ECSOC-23
proceedings-logo

Journal Browser

Journal Browser

Table of Contents

Proceedings, 2020, ECSA-6 2019

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessProceedings
Operational Amplifiers Revisited for Low Field Magnetic Resonance Relaxation Time Measurement Electronics
Proceedings 2020, 42(1), 1; https://doi.org/10.3390/ecsa-6-06645 (registering DOI) - 14 Nov 2019
Viewed by 90
Abstract
Advances in permanent magnet technology has seen more reports of sensor applications of low field magnetic resonance. Whilst most are either in the 10–20 MHz range or in the earth’s field, measurements at below 1 MHz are beginning to become more widespread. This [...] Read more.
Advances in permanent magnet technology has seen more reports of sensor applications of low field magnetic resonance. Whilst most are either in the 10–20 MHz range or in the earth’s field, measurements at below 1 MHz are beginning to become more widespread. This range is below the need for careful radio frequency electronics design but above the audio domain and represents an interesting cross over. Many commercial spectrometers do not include the pulse power amplifier, duplexer and preamplifier as these depend on the frequency range used. In this work we demonstrate that, with the current specifications of the humble operational amplifier, the most simple form of an inverting design using only two resistors and decoupling, can effectively provide this ‘front end’ electronics. The low powers used mean crossed Ge diodes provide an excellent duplexer and it is suitable for battery powered applications. Full article
Open AccessAbstract
Impedimetric Lectin-Based Biosensors for Cancer O-glycobiomarkers
Proceedings 2020, 42(1), 2; https://doi.org/10.3390/ecsa-6-06591 - 17 Jan 2020
Viewed by 215
Abstract
This work gathers and presents three lectin-based impedimetric biosensors for the selective detection of specific aberrant cancer-associated O-glycans, namely STn, Tn and T antigens. These truncated glycans are well-established pan-carcinoma biomarkers that are synthesized by tumour cells during protein glycosylation. Glycoproteins carrying [...] Read more.
This work gathers and presents three lectin-based impedimetric biosensors for the selective detection of specific aberrant cancer-associated O-glycans, namely STn, Tn and T antigens. These truncated glycans are well-established pan-carcinoma biomarkers that are synthesized by tumour cells during protein glycosylation. Glycoproteins carrying these aberrant glycans are then secreted into the blood stream, where they can be detected as cancer biomarkers. Detection of aberrant O-glycoproteins in serum can be successfully performed by using lectin biosensors, as lectins show high selectivity towards particular glycan structures. Lectins are immobilized on the sensor surface, maintaining intact their binding ability towards the glycans present in the sample. For these three biosensors, Sambucus nigra agglutinin, Vicia villosa agglutinin and Arachis hypogeae agglutinin were used as biorecognition elements, with specificity for STn, Tn and T antigens, respectively. The binding event between each lectin and the corresponding aberrant O-glycan was monitored by electrochemical impedance spectroscopy, measuring the increase in the biosensor’s impedance after incubating the samples. The increase in impedance was related to the lectin-glycan complex formation. The performance of the developed biosensors, prepared on screen printed gold electrodes, was evaluated, namely in what concerns selectivity, sensitivity, limit of detection, reproducibility and robustness. Furthermore, a thorough validation was carried out by analyzing serum samples from cancer patients and from healthy donors. Results showed that the three biosensors could efficiently discriminate between controls and patients. Moreover, by analyzing the same samples with the different biosensors, distinct glycosylation profiles could be observed. Full article
Open AccessProceedings
Method of Monitoring Cracks in a Metal Structure Based on Dual-Chip RFID Antenna Sensor
Proceedings 2020, 42(1), 3; https://doi.org/10.3390/ecsa-6-06553 (registering DOI) - 14 Nov 2019
Viewed by 50
Abstract
The microstrip patch antenna sensor is a novel sensor used for structural health monitoring which can measure a metal structure’s crack defects in a wireless manner. However, it is difficult to identify the reflected signal from the signal of an antenna sensor. The [...] Read more.
The microstrip patch antenna sensor is a novel sensor used for structural health monitoring which can measure a metal structure’s crack defects in a wireless manner. However, it is difficult to identify the reflected signal from the signal of an antenna sensor. The radio-frequency identification (RFID) antenna sensor, which combines RFID technology and the microstrip patch antenna sensor, can solve the measurement problems that are difficult to the conventional wireless testing technologies. In this study, a dual-chip RFID antenna sensor was designed. The influence of the wireless testing method on the monitoring results of crack defects was investigated by tests, including the wireless tests of resonant frequency and the crack sensitivity tests. The tests results revealed that the antenna sensor had good wireless testing performance with regard to the metal structure’s crack defects. Additionally, the maximum of wireless identification distance reached 1.96 m. Full article
Open AccessProceedings
Oxygen Sensors Based on Thin Films of Gallium Oxide Modified with Silicon
Proceedings 2020, 42(1), 4; https://doi.org/10.3390/ecsa-6-06549 (registering DOI) - 14 Nov 2019
Viewed by 52
Abstract
The results of an investigation of the electrical resistivity of Ga2O3 thin films modified with silicon under the influence of oxygen in the range of O2 from 9 to 100 vol. % and changes in the heating temperature of [...] Read more.
The results of an investigation of the electrical resistivity of Ga2O3 thin films modified with silicon under the influence of oxygen in the range of O2 from 9 to 100 vol. % and changes in the heating temperature of structures from 25 to 700 °C were presented. Thin films of Ga2O3 were obtained by RF magnetron sputtering of Ga2O3 targeted with pieces of Si on the target’s surface in oxygen–argon plasma. The possibility of developing selective oxygen sensors based on thin films Ga2O3 modified with silicon with a temperature of maximum response 400 °C was shown. Oxygen influence leads to a reversible increase in the samples’ resistance, due to the chemisorption of oxygen on the surface of thin Ga2O3 films. An increase in the response of sensors based on the thin polycrystalline films of gallium oxide modified with silicon is caused an increase in the adsorption centers for O, due to an increase in the surface inhomogeneity and the appearance of additional adsorption centers Si4+. Full article
Open AccessProceedings
Methanol, Ethanol, and Glycerol Oxidation by Graphite-Epoxy Composite Electrodes with Graphene-Anchored Nickel Oxyhydroxide Nanoparticles
Proceedings 2020, 42(1), 5; https://doi.org/10.3390/ecsa-6-06544 (registering DOI) - 14 Nov 2019
Viewed by 166
Abstract
In this work, a graphite-epoxy electrode with cyclic voltammetry electrodeposited reduced graphene oxide and nickel oxyhydroxide nanoparticles was prepared by decomposition in NaOH alkaline solution of cyclic voltammetry electrodeposited nickel hexacyanoferrate. FE-SEM studies were performed to confirm the NiOOH nanoparticle; the average size [...] Read more.
In this work, a graphite-epoxy electrode with cyclic voltammetry electrodeposited reduced graphene oxide and nickel oxyhydroxide nanoparticles was prepared by decomposition in NaOH alkaline solution of cyclic voltammetry electrodeposited nickel hexacyanoferrate. FE-SEM studies were performed to confirm the NiOOH nanoparticle; the average size of the NiOOH nanoparticles was 61 ± 16 nm and EDX was applied to analyze chemical composition. To verify the performance of the prepared electrode, it was used in the electrooxidation of alcohols in alkaline medium by cyclic voltammetry. By performing different calibration experiments of methanol, ethanol, and glycerol, it was possible to extract some information about the electrode in the presence of alcohols. The LOD for methanol, ethanol, and glycerol were 2.16 mM, 2.73 mM and 0.09 mM, respectively, with sensitivity values of 1.32 µA mM−1, 1.80 µA mM−1 and 24.60 µA mM−1, respectively. Multivariate inspection of the data using Principal Component Analysis (performed with the ClustVis online tool) demonstrated the potential ability to discriminate between the different alcohols, whereas the explained variance with the first two components was as high as 89.7%. Full article
Open AccessProceedings
Dynamic Monitoring of Multi-Concentrated Silica Nanoparticles Colloidal Environment with Optical Fiber Sensor
Proceedings 2020, 42(1), 6; https://doi.org/10.3390/ecsa-6-06546 (registering DOI) - 14 Nov 2019
Viewed by 92
Abstract
Colloids are metastable suspensions of particles dispersed in a base fluid, with high scientific and industrial importance, but the monitoring of these systems still demands expensive and large instrumentation. In this research, the measurement of concentration gradients in colloidal silica samples using an [...] Read more.
Colloids are metastable suspensions of particles dispersed in a base fluid, with high scientific and industrial importance, but the monitoring of these systems still demands expensive and large instrumentation. In this research, the measurement of concentration gradients in colloidal silica samples using an optical fiber sensor is reported. Silica nanoparticles (measuring 189 nm) were sedimented in test tubes for creating environments with different concentrations. The fiber probe was immersed in the assessed liquid, resulting in an increase in the dispersion of the reflected light intensity, which is caused by the particles Brownian motion. Therefore, the quasi-elastic light scattering phenomenon related to the diffusivity can be analyzed, providing information about the concentration gradients of the nanosystem with a straightforward, in situ, and non-destructive approach. Full article
Open AccessProceedings
A Thermal Sensor-Based Decision Support System for the Identification of Roof Leaks and Cracks
Proceedings 2020, 42(1), 7; https://doi.org/10.3390/ecsa-6-06695 (registering DOI) - 14 Nov 2019
Viewed by 82
Abstract
The leaks in roofs and cracks in walls of buildings are common and need immediate attention. The roof leaks or cracks lead to water seepage which results in structural damage to the ceiling wall. In this work, the roof leaks or cracks are [...] Read more.
The leaks in roofs and cracks in walls of buildings are common and need immediate attention. The roof leaks or cracks lead to water seepage which results in structural damage to the ceiling wall. In this work, the roof leaks or cracks are identified using the proposed thermal sensor-based decision support system. Further, the thermal camera is interfaced with a handy single on-board computer. The supervised machine learning algorithm is coded inside the single on-board computer and the thermal images captured using the thermal camera is utilized for the fault identification. Further, the trained network is tested using a new set of thermal images for the identification of faults. Results demonstrate that the proposed system is efficient in locating and the identification of faults. Since the single on-board has an inbuilt Wi-Fi, the decision support can be stored in the cloud server with a specific unique Uniform Resource Locator (URL) address. Also, by accessing the appropriate URL, the decision support system can be accessed from remote locations. Full article
Open AccessProceedings
Stochastic Mechanical Characterization of Polysilicon MEMS: A Deep Learning Approach
Proceedings 2020, 42(1), 8; https://doi.org/10.3390/ecsa-6-06574 (registering DOI) - 14 Nov 2019
Viewed by 47
Abstract
Deep Learning strategies recently emerged as powerful tools for the characterization of heterogeneous materials. In this work, we discuss an approach for the characterization of the mechanical response of polysilicon films that typically constitute the movable structures of micro-electro-mechanical systems (MEMS). A dataset [...] Read more.
Deep Learning strategies recently emerged as powerful tools for the characterization of heterogeneous materials. In this work, we discuss an approach for the characterization of the mechanical response of polysilicon films that typically constitute the movable structures of micro-electro-mechanical systems (MEMS). A dataset of microstructures is digitally generated and a neural network is trained to provide the appropriate scattering in the values of the overall stiffness (in terms of the Young’s modulus) of the grain aggregate. Since results are framed within a stochastic procedure, the aim of the learning strategy is not to accurately reproduce the microstructure-informed response of the polysilicon film, but instead to provide a fast tool to be used at the device level for Monte Carlo analysis of the relevant performance indices. Accuracy of the proposed approach is assessed for very small samples of the polycrystalline aggregate to check if size effects are correctly captured. Full article
Open AccessProceedings
Zeolite-Based Fast-Responding Sensors for Respiratory Rate Monitoring
Proceedings 2020, 42(1), 9; https://doi.org/10.3390/ecsa-6-06628 (registering DOI) - 14 Nov 2019
Viewed by 74
Abstract
Wearable electrical sensors based on zeolites can be used for breath monitoring. The high silicon content of clinoptilolite makes this type of zeolite very adequate for fabricating sensitive water sensors. In addition to sensitivity, response fastness also represents a sensor characteristic of fundamental [...] Read more.
Wearable electrical sensors based on zeolites can be used for breath monitoring. The high silicon content of clinoptilolite makes this type of zeolite very adequate for fabricating sensitive water sensors. In addition to sensitivity, response fastness also represents a sensor characteristic of fundamental importance for breath monitoring. Here, the response fastness of a clinoptilolite-based water sensor has been evaluated by measuring the current intensity behavior upon exposition to a constant humidity atmosphere (75%). In particular, the clinoptilolite surface has been biased with a sinusoidal signal (20 Vpp, 5 kHz), and the true-RMS current intensity value has been recorded during exposition to the constant humidity atmosphere. Since current intensity is proportional to the adsorbed water concentration (only hydrated cations are charge carriers) a kinetic analysis has been possible. The clinoptilolite dehydration kinetics in a dry atmosphere have been evaluated too. According to this kinetic analysis, water adsorption is described by a Lagergren pseudo-first-order model with a rate constant of (58.6 ± 0.9)·10−4 min−1, while desorption in dry air follows a first-order kinetic model with a specific rate of (202.7 ± 0.3)·10−4 min−1 at 25 °C. Full article
Open AccessProceedings
Tool Condition Monitoring in Grinding Operation Using Piezoelectric Impedance and Wavelet Transform
Proceedings 2020, 42(1), 10; https://doi.org/10.3390/ecsa-6-06589 (registering DOI) - 14 Nov 2019
Viewed by 79
Abstract
The purpose of the present study is to monitor tool condition in a grinding operation through the electromechanical impedance (EMI) using wavelet analysis. To achieve this, a dressing experiment was conducted on an industrial aluminum oxide grinding wheel by fixing a stationary single-point [...] Read more.
The purpose of the present study is to monitor tool condition in a grinding operation through the electromechanical impedance (EMI) using wavelet analysis. To achieve this, a dressing experiment was conducted on an industrial aluminum oxide grinding wheel by fixing a stationary single-point diamond tool. The proposed approach was verified experimentally at various dressing tool conditions. The signals obtained from an EMI data acquisition system, composed of a piezoelectric diaphragm transducer attached to the tool holder, were processed using discrete wavelet transform. The approximation and detail coefficients obtained from wavelet decomposition were used to estimate tool condition using the correlation coefficient deviation metric (CCDM). The results show excellent performance in tool condition monitoring by the proposed technique, which effectively contributes to modern machine tool automation. Full article
Open AccessProceedings
Robotic Plug-in Combined Charging System with Improved Robustness
Proceedings 2020, 42(1), 11; https://doi.org/10.3390/ecsa-6-06550 (registering DOI) - 14 Nov 2019
Viewed by 36
Abstract
This paper describes the development of an algorithm robotic plug-in of a charging system for mobile platform. In the first chapter, there is a short overview of possibilities of automatic plug-in system, including proprietary industrial solution. In the main part, there is a [...] Read more.
This paper describes the development of an algorithm robotic plug-in of a charging system for mobile platform. In the first chapter, there is a short overview of possibilities of automatic plug-in system, including proprietary industrial solution. In the main part, there is a description of the system based on UR robot with build-in force torque sensors and Intel RealSense Camera. This camera combines IR depth lens with regular RGB camera and six DOF inertial sensor, which is used in our application too. The conventional solution of this problem is usually based on RGB image processing in various state of the art, from simple pattern matching, neural network, or genetic algorithm to complex AI solution. The quality of the solution mostly depends on robustness of image processing. In our cases, we use simple sensor fusion. Thanks to multiple information and constrain of values, we can assume, if the algorithm is proceeding successfully or not. The system uses the internal parameters of the robotic arm, e.g., end-effector position and orientation and force-torque information in tool center point. The next information is RGB camera image and camera depth image, and the inertial unit build in camera. The other important information is the location of the vehicle inlet on the mobile platform, where the shape of mobile platform is considered as a constrain for image processing. The system is validated only on a physical model with CCS type 2 plug and vehicle inlet, because the mobile platform is under construction by another team. Full article
Open AccessProceedings
Use of Optical Fiber Sensor for Monitoring the Degradation of Ac-Dex Biopolymeric Nanoparticles
Proceedings 2020, 42(1), 12; https://doi.org/10.3390/ecsa-6-06535 (registering DOI) - 14 Nov 2019
Viewed by 113
Abstract
Abstract: Acetalated dextran (Ac-Dex) is a promising pH-sensitive biocompatible and biodegradable polymer for nanomedicine applications. In this work, Ac-Dex nanoparticles were synthesized by two different solvent evaporation methods, the single nanoemulsion and the double nanoemulsion. The Ac-Dex particles were characterized by scanning [...] Read more.
Abstract: Acetalated dextran (Ac-Dex) is a promising pH-sensitive biocompatible and biodegradable polymer for nanomedicine applications. In this work, Ac-Dex nanoparticles were synthesized by two different solvent evaporation methods, the single nanoemulsion and the double nanoemulsion. The Ac-Dex particles were characterized by scanning electron microscopy and the synthesis of highly homogeneous spherical particles was verified. Then, an optical fiber sensor based on quasi-elastic light scattering and comprised of only single-mode optical fibers and standard telecommunication devices showed sensitivity regarding the nanoparticles concentrations and was used for monitoring their degradation over 12 h under pH and temperature conditions of cancerous tissues. The results revealed a well-controlled degradation pattern, corroborating the suitability of the modified polymer to the release of active compounds in a sustainable manner and also demonstrating the applicability of the sensor for the in situ evaluation of the degradation. Full article
Open AccessProceedings
Rapid, Wide-Range, and Low-Cost Determination of Formaldehyde Based on Porous Silica Gel Plate by Digital Image Colorimetry
Proceedings 2020, 42(1), 13; https://doi.org/10.3390/ecsa-6-06542 (registering DOI) - 14 Nov 2019
Viewed by 46
Abstract
A porous silica gel plate impregnated with a colorimetric reagent, 4-amino-3-penten-2-one (Fluoral-P) has been fabricated for the first time to determinate formaldehyde. The reaction of formaldehyde and Fluoral-P produced a yellow product 3,5-diacetyl-1,4-dihydrolutidine (DDL), which was further photographed by a smartphone. A good [...] Read more.
A porous silica gel plate impregnated with a colorimetric reagent, 4-amino-3-penten-2-one (Fluoral-P) has been fabricated for the first time to determinate formaldehyde. The reaction of formaldehyde and Fluoral-P produced a yellow product 3,5-diacetyl-1,4-dihydrolutidine (DDL), which was further photographed by a smartphone. A good linear relationship has been found between the intensity of blue component from the digital image and formaldehyde concentration in the range of 0–50 mg L−1 with low detection limit of 2.2 ± 0.1 mg L−1. A good precision in the range of 0.59–7.75%RSD and an accuracy with the relative error of +3.7% from control samples are also obtained. These results demonstrate that our developed low-cost sensor, together with digital image colorimetry, has potential for sensitively and quickly measuring formaldehyde. Full article
Open AccessProceedings
Physiological Impact of Vibration and Noise in an Open-Air Magnetic Resonance Imager: Analysis of a PPG Signal of an Examined Person
Proceedings 2020, 42(1), 14; https://doi.org/10.3390/ecsa-6-06631 (registering DOI) - 14 Nov 2019
Viewed by 55
Abstract
The paper represents a preliminary analysis of the physiological and psychological impact of vibration and acoustic noise on a person examined by a low-field magnetic resonance imaging (MRI) tomograph. First, a methodology for the measurement of different signals of a tested person was [...] Read more.
The paper represents a preliminary analysis of the physiological and psychological impact of vibration and acoustic noise on a person examined by a low-field magnetic resonance imaging (MRI) tomograph. First, a methodology for the measurement of different signals of a tested person was found. The main investigation consists of a parallel heart rate and blood pressure measurement using a photoplethysmographic (PPG) optical sensor and standard portable blood pressure monitors. The recorded PPG signal is filtered and processed to obtain a clean waveform used to determine an instantaneous heart rate. Different types of portable blood pressure monitors are tested and compared to choose the best one for further experiments. Full article
Open AccessProceedings
Human Activity Recognition Based on Deep Learning Techniques
Proceedings 2020, 42(1), 15; https://doi.org/10.3390/ecsa-6-06539 (registering DOI) - 14 Nov 2019
Viewed by 123
Abstract
Deep learning techniques are being widely applied to Human Activity Recognition (HAR). This paper describes the implementation and evaluation of a HAR system for daily life activities using the accelerometer of an iPhone 6S. This system is based on a deep neural network [...] Read more.
Deep learning techniques are being widely applied to Human Activity Recognition (HAR). This paper describes the implementation and evaluation of a HAR system for daily life activities using the accelerometer of an iPhone 6S. This system is based on a deep neural network including convolutional layers for feature extraction from accelerations and fully-connected layers for classification. Different transformations have been applied to the acceleration signals in order to find the appropriate input data to the deep neural network. This study has used acceleration recordings from the MotionSense dataset, where 24 subjects performed 6 activities: walking downstairs, walking upstairs, sitting, standing, walking and jogging. The evaluation has been performed using a subject-wise cross-validation: recordings from the same subject do not appear in training and testing sets at the same time. The proposed system has obtained a 9% improvement in accuracy compared to the baseline system based on Support Vector Machines. The best results have been obtained using raw data as input to a deep neural network composed of two convolutional and two max-pooling layers with decreasing kernel sizes. Results suggest that using the module of the Fourier transform as inputs provides better results when classifying only between dynamic activities. Full article
Open AccessProceedings
The Influence of Annealing on Optical and Humidity Sensing Properties of Poly(Vinyl Alcohol-Co-Vinyl Acetal) Thin Films
Proceedings 2020, 42(1), 16; https://doi.org/10.3390/ecsa-6-06555 (registering DOI) - 14 Nov 2019
Viewed by 61
Abstract
Hydrophobically modified poly(vinyl alcohol)s of varied copolymer composition were tested as active media for optical sensing of humidity. Copolymer thin films were deposited on silicon substrate using water-methanol solution in a volume ratio of 20:80 and concentration of 1 wt%. Films were subjected [...] Read more.
Hydrophobically modified poly(vinyl alcohol)s of varied copolymer composition were tested as active media for optical sensing of humidity. Copolymer thin films were deposited on silicon substrate using water-methanol solution in a volume ratio of 20:80 and concentration of 1 wt%. Films were subjected to low (60 °C) and moderate (180 °C) temperature annealing in order to study the temperature influence on optical and humidity sensing properties. Refractive index, extinction coefficient along with thickness of the films were determined by non-linear minimization of the goal function comprising measured and calculated reflectance spectra at normal light incidence. The humidity sensing ability of the films was studied through reflectance measurements at different humidity levels in the range 5–95 %RH. The influence of temperature annealing on optical and sensing properties was demonstrated and discussed. Full article
Open AccessProceedings
Structural Health Monitoring for Condition Assessment Using Efficient Supervised Learning Techniques
Proceedings 2020, 42(1), 17; https://doi.org/10.3390/ecsa-6-06538 (registering DOI) - 14 Nov 2019
Viewed by 55
Abstract
Pattern recognition can be adopted for structural health monitoring (SHM) based on statistical characteristics extracted from raw vibration data. Structural condition assessment is an important step of SHM, since changes in the relevant properties may adversely affect the behavior of any structure. It [...] Read more.
Pattern recognition can be adopted for structural health monitoring (SHM) based on statistical characteristics extracted from raw vibration data. Structural condition assessment is an important step of SHM, since changes in the relevant properties may adversely affect the behavior of any structure. It looks therefore necessary to adopt efficient and robust approaches for the classification of different structural conditions using features extracted from the said raw data. To achieve this goal, it is essential to correctly distinguish the undamaged and damage states of the structure; the aim of this work is to present and compare classification methods using feature selection techniques to classify the structural conditions. All of the utilized classifiers need a training set pertinent to the undamaged/damaged conditions of the structure, as well as relevant class labels to be adopted in a supervised learning strategy. The performance and accuracy of the considered classification methods are assessed through a numerical benchmark concrete beam. Full article
Open AccessProceedings
Different Approaches to FT-IR Microspectroscopy on X-ray Exposed Human Cells
Proceedings 2020, 42(1), 18; https://doi.org/10.3390/ecsa-6-06536 (registering DOI) - 14 Nov 2019
Viewed by 67
Abstract
Fourier-Transform Infrared microspectroscopy (μFT-IR) has been usefully applied in the analysis of the complex biological processes occurring during X-ray radiation-cell interaction. Different experimental approaches are available for FT-IR spectra collection (transmission, attenuated total reflection (ATR), and transflection modes) from cells samples. Recently, some [...] Read more.
Fourier-Transform Infrared microspectroscopy (μFT-IR) has been usefully applied in the analysis of the complex biological processes occurring during X-ray radiation-cell interaction. Different experimental approaches are available for FT-IR spectra collection (transmission, attenuated total reflection (ATR), and transflection modes) from cells samples. Recently, some problems have been raised about the role of transmitted and reflected components of the infrared beam in transflection mode. For this reason, we investigated two different transflection approaches for collecting spectra from cells exposed to X-ray. In the former approach, cells were grown on MirrIR slides, and for the second approach, cell pellets were prepared. In both cases, SH-SY5Y neuroblastoma cells were used. X-ray exposure was performed at doses of 2 and 4 Gy. Spectra were obtained by using both the approaches in the 600–4000 cm−1 spectral range from exposed and not-exposed samples. The main contributions from proteins, lipids, carbohydrates, and DNA were clearly evidenced in spectra obtained with the two different acquisition approaches. A comparison among them has been also reported. Full article
Open AccessProceedings
Fourier-Transform Infrared Microspectroscopy (FT-IR) Study on Caput and Cauda Mouse Spermatozoa
Proceedings 2020, 42(1), 19; https://doi.org/10.3390/ecsa-6-06537 (registering DOI) - 22 Jan 2020
Viewed by 113
Abstract
Fourier-Transform Infrared micro-spectroscopy (µFT-IR) was used for an in vitro investigation on spermatozoa (SPZ) samples separately collected from caput and cauda of mouse epididymis. SPZ are characterized by deep biochemical changes during the transit along the epididymis and they can constitute ideal candidates [...] Read more.
Fourier-Transform Infrared micro-spectroscopy (µFT-IR) was used for an in vitro investigation on spermatozoa (SPZ) samples separately collected from caput and cauda of mouse epididymis. SPZ are characterized by deep biochemical changes during the transit along the epididymis and they can constitute ideal candidates for a µFT-IR investigation, thanks to the ability of this technique in analyzing cells at a molecular level. Appreciable differences were reported in the infrared spectra from caput and cauda SPZ, and biochemical changes in protein, nucleic acid, lipid, and carbohydrate content of cells were evidenced. The present investigation indicates that µFT-IR can constitute a valuable tool for monitoring, in an easy and fast way, the changes suffered by SPZ during the transit along the epididymis. Full article
Open AccessProceedings
Identification of Electrical Faults in Underground Cables Using Machine Learning Algorithm
Proceedings 2020, 42(1), 20; https://doi.org/10.3390/ecsa-6-06714 (registering DOI) - 22 Jan 2020
Viewed by 121
Abstract
Transmission and distribution play a vital role in delivering electricity. The presence of any fault in these systems may stop the delivery of electricity, which may create a huge problem in today’s world. Hence, fault detection has become essential for delivering uninterrupted power [...] Read more.
Transmission and distribution play a vital role in delivering electricity. The presence of any fault in these systems may stop the delivery of electricity, which may create a huge problem in today’s world. Hence, fault detection has become essential for delivering uninterrupted power supply. In this work, a portable and intelligent system is designed, and the fault detection on underground transmission lines is done using a developed hardware system. Also, the proposed system has a thermal camera which is an 8 × 8 array of infrared thermal sensors interfaced with a system-on-chip device, which collects the real-time thermal images when connected to the device. Further, the thermal camera returns an array of 64 individual infrared temperature readings of the transmission line and locates the point of damage that might occur due to the aging of conductor insulation, physical force, etc. Also, 200 images with thermal information from the different instances and directions are utilized to train the adapted machine learning algorithm. The python software is utilized to code the machine learning algorithm inside the system-on-chip device. The convolutional neural network-based machine learning algorithm is adopted and validated using various performance metrics such as accuracy, sensitivity, specificity, precision, negative predicted value, and F1_score. Results demonstrate that the proposed hardware is highly capable of locating faults in underground transmission lines. Full article
Open AccessProceedings
Piezoelectric Sensor Signal Analysis after Interface Changes between the Sensor and the Structure under Monitoring
Proceedings 2020, 42(1), 21; https://doi.org/10.3390/ecsa-6-06552 (registering DOI) - 22 Jan 2020
Viewed by 114
Abstract
This study aims to show the influences of the sensor installation interface in the industrial environment. This contribution is focused on analyzing the response behavior of piezoelectric transducers subjected to successive installations, using digital signal processing and non-destructive structural health monitoring (SHM) techniques. [...] Read more.
This study aims to show the influences of the sensor installation interface in the industrial environment. This contribution is focused on analyzing the response behavior of piezoelectric transducers subjected to successive installations, using digital signal processing and non-destructive structural health monitoring (SHM) techniques. Tests were performed to simulate the installation conditions of a piezoelectric sensor, which was coupled to a holder carrying a steel body and submitted to successive reinstallations. Different signals were obtained for each installation, and the results can bring initial elucidations on the subject and pave the way for future studies. Full article
Previous Issue
Next Issue
Back to TopTop