Search results for: pulse signal
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2146

Search results for: pulse signal

1126 Modified Gold Screen Printed Electrode with Ruthenium Complex for Selective Detection of Porcine DNA

Authors: Siti Aishah Hasbullah

Abstract:

Studies on identification of pork content in food have grown rapidly to meet the Halal food standard in Malaysia. The used mitochondria DNA (mtDNA) approaches for the identification of pig species is thought to be the most precise marker due to the mtDNA genes are present in thousands of copies per cell, the large variability of mtDNA. The standard method commonly used for DNA detection is based on polymerase chain reaction (PCR) method combined with gel electrophoresis but has major drawback. Its major drawbacks are laborious, need longer time and toxic to handle. Therefore, the need for simplicity and fast assay of DNA is vital and has triggered us to develop DNA biosensors for porcine DNA detection. Therefore, the aim of this project is to develop electrochemical DNA biosensor based on ruthenium (II) complex, [Ru(bpy)2(p-PIP)]2+ as DNA hybridization label. The interaction of DNA and [Ru(bpy)2(p-HPIP)]2+ will be studied by electrochemical transduction using Gold Screen-Printed Electrode (GSPE) modified with gold nanoparticles (AuNPs) and succinimide acrylic microspheres. The electrochemical detection by redox active ruthenium (II) complex was measured by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The results indicate that the interaction of [Ru(bpy)2(PIP)]2+ with hybridization complementary DNA has higher response compared to single-stranded and mismatch complementary DNA. Under optimized condition, this porcine DNA biosensor incorporated modified GSPE shows good linear range towards porcine DNA.

Keywords: gold, screen printed electrode, ruthenium, porcine DNA

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1125 Features of Normative and Pathological Realizations of Sibilant Sounds for Computer-Aided Pronunciation Evaluation in Children

Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

Abstract:

Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

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1124 Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena

Authors: Mohammad Zavid Parvez, Manoranjan Paul

Abstract:

A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, seizure, phase correlation, fluctuation, deviation.

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1123 An Assistive Robotic Arm for Defence and Rescue Application

Authors: J. Harrison Kurunathan, R. Jayaparvathy

Abstract:

"Assistive Robotics" is the field that deals with the study of robots that helps in human motion and also empowers human abilities by interfacing the robotic systems to be manipulated by human motion. The proposed model is a robotic arm that works as a haptic interface on the basis on accelerometers and DC motors that will function with respect to the movement of the human muscle. The proposed model would effectively work as a haptic interface that would reduce human effort in the field of defense and rescue. This can be used in very critical conditions like fire accidents to avoid causalities.

Keywords: accelerometers, haptic interface, servo motors, signal processing

Procedia PDF Downloads 403
1122 Particle Size Distribution Estimation of a Mixture of Regular and Irregular Sized Particles Using Acoustic Emissions

Authors: Ejay Nsugbe, Andrew Starr, Ian Jennions, Cristobal Ruiz-Carcel

Abstract:

This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250 microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated.

Keywords: acoustic emissions, particle sizing, process monitoring, signal processing

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1121 Integrated Lateral Flow Electrochemical Strip for Leptospirosis Diagnosis

Authors: Wanwisa Deenin, Abdulhadee Yakoh, Chahya Kreangkaiwal, Orawon Chailapakul, Kanitha Patarakul, Sudkate Chaiyo

Abstract:

LipL32 is an outer membrane protein present only on pathogenic Leptospira species, which are the causative agent of leptospirosis. Leptospirosis symptoms are often misdiagnosed with other febrile illnesses as the clinical manifestations are non-specific. Therefore, an accurate diagnostic tool for leptospirosis is indeed critical for proper and prompt treatment. Typical diagnosis via serological assays is generally performed to assess the antibodies produced against Leptospira. However, their delayed antibody response and complicated procedure are undoubtedly limited the practical utilization especially in primary care setting. Here, we demonstrate for the first time an early-stage detection of LipL32 by an integrated lateral-flow immunoassay with electrochemical readout (eLFIA). A ferrocene trace tag was monitored via differential pulse voltammetry operated on a smartphone-based device, thus allowing for on-field testing. Superior performance in terms of the lowest detectable limit of detection (LOD) of 8.53 pg/mL and broad linear dynamic range (5 orders of magnitude) among other sensors available thus far was established. Additionally, the developed test strip provided a straightforward yet sensitive approach for diagnosis of leptospirosis using the collected human sera from patients, in which the results were comparable to the real-time polymerase chain reaction technique.

Keywords: leptospirosis, electrochemical detection, lateral flow immunosensor, point-of-care testing, early-stage detection

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1120 Least Support Orthogonal Matching Pursuit (LS-OMP) Recovery Method for Invisible Watermarking Image

Authors: Israa Sh. Tawfic, Sema Koc Kayhan

Abstract:

In this paper, first, we propose least support orthogonal matching pursuit (LS-OMP) algorithm to improve the performance, of the OMP (orthogonal matching pursuit) algorithm. LS-OMP algorithm adaptively chooses optimum L (least part of support), at each iteration. This modification helps to reduce the computational complexity significantly and performs better than OMP algorithm. Second, we give the procedure for the invisible image watermarking in the presence of compressive sampling. The image reconstruction based on a set of watermarked measurements is performed using LS-OMP.

Keywords: compressed sensing, orthogonal matching pursuit, restricted isometry property, signal reconstruction, least support orthogonal matching pursuit, watermark

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1119 Merits and Demerits of Participation of Fellow Examinee as Subjects in Observed Structured Practical Examination in Physiology

Authors: Mohammad U. A. Khan, Md. D. Hossain

Abstract:

Background: Department of Physiology finds difficulty in managing ‘subjects’ in practical procedure. To avoid this difficulty fellow examinees of other group may be used as subjects. Objective: To find out the merits and demerits of using fellow examinees as subjects in the practical procedure. Method: This cross-sectional descriptive study was conducted in the Department of Physiology, Noakhali Medical College, Bangladesh during May-June’14. Forty-two 1st year undergraduate medical students from a selected public medical college of Bangladesh were enrolled for the study purposively. Consent of students and authority was taken. Eighteen of them were selected as subjects and designated as subject-examinees. Other fellow examinees (non-subject) examined their blood pressure and pulse as part of ‘observed structured practical examination’ (OSPE). The opinion of all examinees regarding the merits and demerits of using fellow examinee as subjects in the practical procedure was recorded. Result: Examinees stated that they could perform their practical procedure without nervousness (24/42, 57.14%), accurately and comfortably (14/42, 33.33%) and subjects were made available without wasting time (2/42, 4.76%). Nineteen students (45.24%) found no disadvantage and 2 (4.76%) felt embracing when the subject was of opposite sex. The subject-examinees narrated that they could learn from the errors done by their fellow examinee (11/18, 61.1%). 75% non-subject examinees expressed their willingness to be subject so that they can learn from their fellows’ error. Conclusion: Using fellow examinees as subjects is beneficial for both the non-subject and subject examinees. Funding sources: Navana, Beximco, Unihealth, Square & Acme Pharma, Bangladesh Ltd.

Keywords: physiology, teaching, practical, OSPE

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1118 Geomatic Techniques to Filter Vegetation from Point Clouds

Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

Abstract:

More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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1117 Fractional-Order Modeling of GaN High Electron Mobility Transistors for Switching Applications

Authors: Anwar H. Jarndal, Ahmed S. Elwakil

Abstract:

In this paper, a fraction-order model for pad parasitic effect of GaN HEMT on Si substrate is developed and validated. Open de-embedding structure is used to characterize and de-embed substrate loading parasitic effects. Unbiased device measurements are implemented to extract parasitic inductances and resistances. The model shows very good simulation for S-parameter measurements under different bias conditions. It has been found that this approach can improve the simulation of intrinsic part of the transistor, which is very important for small- and large-signal modeling process.

Keywords: fractional-order modeling, GaNHEMT, si-substrate, open de-embedding structure

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1116 Investigating the Effects of Data Transformations on a Bi-Dimensional Chi-Square Test

Authors: Alexandru George Vaduva, Adriana Vlad, Bogdan Badea

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In this research, we conduct a Monte Carlo analysis on a two-dimensional χ2 test, which is used to determine the minimum distance required for independent sampling in the context of chaotic signals. We investigate the impact of transforming initial data sets from any probability distribution to new signals with a uniform distribution using the Spearman rank correlation on the χ2 test. This transformation removes the randomness of the data pairs, and as a result, the observed distribution of χ2 test values differs from the expected distribution. We propose a solution to this problem and evaluate it using another chaotic signal.

Keywords: chaotic signals, logistic map, Pearson’s test, Chi Square test, bivariate distribution, statistical independence

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1115 Electrochemical Sensor Based on Poly(Pyrogallol) for the Simultaneous Detection of Phenolic Compounds and Nitrite in Wastewater

Authors: Majid Farsadrooh, Najmeh Sabbaghi, Seyed Mohammad Mostashari, Abolhasan Moradi

Abstract:

Phenolic compounds are chief environmental contaminants on account of their hazardous and toxic nature on human health. The preparation of sensitive and potent chemosensors to monitor emerging pollution in water and effluent samples has received great consideration. A novel and versatile nanocomposite sensor based on poly pyrogallol is presented for the first time in this study, and its electrochemical behavior for simultaneous detection of hydroquinone (HQ), catechol (CT), and resorcinol (RS) in the presence of nitrite is evaluated. The physicochemical characteristics of the fabricated nanocomposite were investigated by emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS), and Brunauer-Emmett-Teller (BET). The electrochemical response of the proposed sensor to the detection of HQ, CT, RS, and nitrite is studied using cyclic voltammetry (CV), chronoamperometry (CA), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The kinetic characterization of the prepared sensor showed that both adsorption and diffusion processes can control reactions at the electrode. In the optimized conditions, the new chemosensor provides a wide linear range of 0.5-236.3, 0.8-236.3, 0.9-236.3, and 1.2-236.3 μM with a low limit of detection of 21.1, 51.4, 98.9, and 110.8 nM (S/N = 3) for HQ, CT and RS, and nitrite, respectively. Remarkably, the electrochemical sensor has outstanding selectivity, repeatability, and stability and is successfully employed for the detection of RS, CT, HQ, and nitrite in real water samples with the recovery of 96.2%–102.4%, 97.8%-102.6%, 98.0%–102.4% and 98.4%–103.2% for RS, CT, HQ, and nitrite, respectively. These outcomes illustrate that poly pyrogallol is a promising candidate for effective electrochemical detection of dihydroxybenzene isomers in the presence of nitrite.

Keywords: electrochemical sensor, poly pyrogallol, phenolic compounds, simultaneous determination

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1114 A Stepwise Approach for Piezoresistive Microcantilever Biosensor Optimization

Authors: Amal E. Ahmed, Levent Trabzon

Abstract:

Due to the low concentration of the analytes in biological samples, the use of Biological Microelectromechanical System (Bio-MEMS) biosensors for biomolecules detection results in a minuscule output signal that is not good enough for practical applications. In response to this, a need has arisen for an optimized biosensor capable of giving high output signal in response the detection of few analytes in the sample; the ultimate goal is being able to convert the attachment of a single biomolecule into a measurable quantity. For this purpose, MEMS microcantilevers based biosensors emerged as a promising sensing solution because it is simple, cheap, very sensitive and more importantly does not need analytes optical labeling (Label-free). Among the different microcantilever transducing techniques, piezoresistive based microcantilever biosensors became more prominent because it works well in liquid environments and has an integrated readout system. However, the design of piezoresistive microcantilevers is not a straightforward problem due to coupling between the design parameters, constraints, process conditions, and performance. It was found that the parameters that can be optimized to enhance the sensitivity of Piezoresistive microcantilever-based sensors are: cantilever dimensions, cantilever material, cantilever shape, piezoresistor material, piezoresistor doping level, piezoresistor dimensions, piezoresistor position, Stress Concentration Region's (SCR) shape and position. After a systematic analyzation of the effect of each design and process parameters on the sensitivity, a step-wise optimization approach was developed in which almost all these parameters were variated one at each step while fixing the others to get the maximum possible sensitivity at the end. At each step, the goal was to optimize the parameter in a way that it maximizes and concentrates the stress in the piezoresistor region for the same applied force thus get the higher sensitivity. Using this approach, an optimized sensor that has 73.5x times higher electrical sensitivity (ΔR⁄R) than the starting sensor was obtained. In addition to that, this piezoresistive microcantilever biosensor it is more sensitive than the other similar sensors previously reported in the open literature. The mechanical sensitivity of the final senior is -1.5×10-8 Ω/Ω ⁄pN; which means that for each 1pN (10-10 g) biomolecules attach to this biosensor; the piezoresistor resistivity will decrease by 1.5×10-8 Ω. Throughout this work COMSOL Multiphysics 5.0, a commercial Finite Element Analysis (FEA) tool, has been used to simulate the sensor performance.

Keywords: biosensor, microcantilever, piezoresistive, stress concentration region (SCR)

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1113 Design and Simulation of Low Cost Boost-Half- Bridge Microinverter with Grid Connection

Authors: P. Bhavya, P. R. Jayasree

Abstract:

This paper presents a low cost transformer isolated boost half bridge micro-inverter for single phase grid connected PV system. Since the output voltage of a single PV panel is as low as 20~50V, a high voltage gain inverter is required for the PV panel to connect to the single-phase grid. The micro-inverter has two stages, an isolated dc-dc converter stage and an inverter stage with a dc link. To achieve MPPT and to step up the PV voltage to the dc link voltage, a transformer isolated boost half bridge dc-dc converter is used. To output the synchronised sinusoidal current with unity power factor to the grid, a pulse width modulated full bridge inverter with LCL filter is used. Variable step size Maximum Power Point Tracking (MPPT) method is adopted such that fast tracking and high MPPT efficiency are both obtained. AC voltage as per grid requirement is obtained at the output of the inverter. High power factor (>0.99) is obtained at both heavy and light loads. This paper gives the results of computer simulation program of a grid connected solar PV system using MATLAB/Simulink and SIM Power System tool.

Keywords: boost-half-bridge, micro-inverter, maximum power point tracking, grid connection, MATLAB/Simulink

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1112 Electro-oxidation of Catechol in the Presence of Nicotinamide at Different pH

Authors: M. A. Motin, M. A. Aziz, M. Hafiz Mia, M. A. Hasem

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The redox behavior of catechol in the presence of nicotinamide as nucleophiles has been studied in aqueous solution with various pH values and different concentration of nicotinamide using cyclic voltammetry and differential pulse voltammetry. Cyclic voltammetry of catechol in buffer solution (3.00 < pH < 9.00) shows one anodic and corresponding cathodic peak which relates to the transformation of catechol to corresponding o-benzoquinone and vice versa within a quasi reversible two electron transfer process. Cyclic voltammogram of catechol in the presence of nicotinamide in buffer solution of pH 7, show one anodic peak in the first cycle of potential and on the reverse scan the corresponding cathodic peak slowly decreases and new peak is observed at less positive potential. In the second cycle of potential a new anodic peak is observed at less positive potential. This indicates that nicotinamide attached with catechol and formed adduct after first cycle of oxidation. The effect of pH of catechol in presence of nicotinamide was studied by varying pH from 3 to 11. The substitution reaction of catechol with nicotimamide is facilitated at pH 7. In buffer solution of higher pH (>9), the CV shows different pattern. The effect of concentration of nicotinamide was studied by 2mM to 100 mM. The maximum substitution reaction has been found for 50 mM of nicotinamide and of pH 7. The proportionality of the first scan anodic and cathodic peak currents with square root of scan rate suggests that the peak current of the species at each redox reaction is controlled by diffusion process. The current functions (1/v-1/2) of the anodic peak decreased with the increasing of scan rate demonstrated that the behavior of the substitution reaction is of ECE type.

Keywords: redox interaction, catechol, nicotinamide, substituion reaction, pH effect

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1111 Advancements in Smart Home Systems: A Comprehensive Exploration in Electronic Engineering

Authors: Chukwuka E. V., Rowling J. K., Rushdie Salman

Abstract:

The field of electronic engineering encompasses the study and application of electrical systems, circuits, and devices. Engineers in this discipline design, analyze and optimize electronic components to develop innovative solutions for various industries. This abstract provides a brief overview of the diverse areas within electronic engineering, including analog and digital electronics, signal processing, communication systems, and embedded systems. It highlights the importance of staying abreast of advancements in technology and fostering interdisciplinary collaboration to address contemporary challenges in this rapidly evolving field.

Keywords: smart home engineering, energy efficiency, user-centric design, security frameworks

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1110 Melatonin Improved Vase Quality by Delaying Oxidation Reaction and Supplying More Energies in Cut Peony (Paeonia Lactiflora cv. Sarah)

Authors: Tai Chen, Caihuan Tian, Xiuxia Ren, Jingqi Xue, Xiuxin Zhang

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The herbaceous peony has become increasingly popular worldwide in recent years, especially as a cut flower with great economic value. However, peony has a very short vase life, only 3-5 d usually, which seriously affects its commodity value. In this study, we used the cut peony (Paeonia lactiflora cv. Sarah) as a material and found that melatonin treatment significantly improved its postharvest performance. In the control group, its vase life was 4.8 d, accompanied by petal dropping at last; melatonin treatment (40 μM) increased this time to 6.9 d without petal dropping at the end. Further study showed that melatonin treatment significantly increased the activity of antioxidant enzymes as well as reduced sugar content in petals, whereas the starch content in petals decreased. These results indicated that melatonin treatment may delay the oxidation reaction caused by aging, which also provides extra energy for maintaining flowering. Through full-length transcriptome sequencing, a total of 2819 differentially expressed genes (DEGs) between control and melatonin treatment groups were identified. KEGG enrichment analysis showed that these DEGs were mainly involved in three pathways, including melatonin synthesis, starch and sucrose conversion, and plant disease resistance. After the RT-qPCR verification, we identified three DEGs, named PlBAM3, PlWRKY22 and PlTIP1, and they should play major roles in melatonin-improved postharvest performance. One possible reason is that PlBAM3 caused maltose production (by starch degradation), maintained the proline biosynthesis, and then alleviated oxidative stress. Another reason is that both PlBAM3 and PlWRKY22 are key drought resistance regulators, which have the ability to alleviate osmotic stress and improve water absorption, which may also help to improve the postharvest quality of cut peony. In addition, PlTIP1 is involved in the sugar signal pathway, indicating sugar may also as a signal substance during this process. Our work may give new ideas for developing new ways to prolong the vase life of cut peony and improve its commodity value eventually.

Keywords: cut peony, melatonin, vase life, oxidation reaction, energy supply, differentially expressed genes

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1109 Cluster-Based Multi-Path Routing Algorithm in Wireless Sensor Networks

Authors: Si-Gwan Kim

Abstract:

Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: clustering, multi-path, routing protocol, sensor network

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1108 Quantile Coherence Analysis: Application to Precipitation Data

Authors: Yaeji Lim, Hee-Seok Oh

Abstract:

The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

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1107 ICAM-2, A Protein of Antitumor Immune Response in Mekong Giant Catfish (Pangasianodon gigas)

Authors: Jiraporn Rojtinnakorn

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ICAM-2 (intercellular adhesion molecule 2) or CD102 (Cluster of Differentiation 102) is type I trans-membrane glycoproteins, composing 2-9 immunoglobulin-like C2-type domains. ICAM-2 plays the particular role in immune response and cell surveillance. It is concerned in innate and specific immunity, cell survival signal, apoptosis, and anticancer. EST clone of ICAM-2, from P. gigas blood cell EST libraries, showed high identity to human ICAM-2 (92%) with conserve region of ICAM N-terminal domain and part of Ig superfamily. Gene and protein of ICAM-2 has been founded in mammals. This is the first report of ICAM-2 in fish.

Keywords: ICAM-2, CD102, Pangasianodon gigas, antitumor

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1106 A Sensitive Approach on Trace Analysis of Methylparaben in Wastewater and Cosmetic Products Using Molecularly Imprinted Polymer

Authors: Soukaina Motia, Nadia El Alami El Hassani, Alassane Diouf, Benachir Bouchikhi, Nezha El Bari

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Parabens are the antimicrobial molecules largely used in cosmetic products as a preservative agent. Among them, the methylparaben (MP) is the most frequently used ingredient in cosmetic preparations. Nevertheless, their potential dangers led to the development of sensible and reliable methods for their determination in environmental samples. Firstly, a sensitive and selective molecular imprinted polymer (MIP) based on screen-printed gold electrode (Au-SPE), assembled on a polymeric layer of carboxylated poly(vinyl-chloride) (PVC-COOH), was developed. After the template removal, the obtained material was able to rebind MP and discriminate it among other interfering species such as glucose, sucrose, and citric acid. The behavior of molecular imprinted sensor was characterized by Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS) techniques. Then, the biosensor was found to have a linear detection range from 0.1 pg.mL-1 to 1 ng.mL-1 and a low limit of detection of 0.12 fg.mL-1 and 5.18 pg.mL-1 by DPV and EIS, respectively. For applications, this biosensor was employed to determine MP content in four wastewaters in Meknes city and two cosmetic products (shower gel and shampoo). The operational reproducibility and stability of this biosensor were also studied. Secondly, another MIP biosensor based on tungsten trioxide (WO3) functionalized by gold nanoparticles (Au-NPs) assembled on a polymeric layer of PVC-COOH was developed. The main goal was to increase the sensitivity of the biosensor. The developed MIP biosensor was successfully applied for the MP determination in wastewater samples and cosmetic products.

Keywords: cosmetic products, methylparaben, molecularly imprinted polymer, wastewater

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1105 Molecular Profiles of Microbial Etiologic Agents Forming Biofilm in Urinary Tract Infections of Pregnant Women by RTPCR Assay

Authors: B. Nageshwar Rao

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Urinary tract infection (UTI) represents the most commonly acquired bacterial infection worldwide, with substantial morbidity, mortality, and economic burden. The objective of the study is to characterize the microbial profiles of uropathogenic in the obstetric population by RTPCR. Study design: An observational cross-sectional study was performed at a single tertiary health care hospital among 50 pregnant women with UTIs, including asymptomatic and symptomatic patients attending the outpatient department and inpatient department of Obstetrics and Gynaecology.Methods: Serotyping and genes detection of various uropathogens were studied using RTPCR. Pulse filed gel electrophoresis methods were used to determine the various genetic profiles. Results: The present study shows that CsgD protein, involved in biofilm formation in Escherichia coli, VIM1, IMP1 genes for Klebsiella were identified by using the RTPCR method. Our results showed that the prevalence of VIM1 and IMP1 genes and CsgD protein in E.coli showed a significant relationship between strong biofilm formation, and this may be due to the prevalence of specific genes. Finally, the genetic identification of RTPCR results for both bacteria was correlated with each other and concluded that the above uropathogens were common isolates in producing Biofilm in the pregnant woman suffering from urinary tract infection in our hospital observational study.

Keywords: biofilms, Klebsiella, E.coli, urinary tract infection

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1104 Evaluation of Random Forest and Support Vector Machine Classification Performance for the Prediction of Early Multiple Sclerosis from Resting State FMRI Connectivity Data

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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1103 Methotrexate Associated Skin Cancer: A Signal Review of Pharmacovigilance Center

Authors: Abdulaziz Alakeel, Abdulrahman Alomair, Mohammed Fouda

Abstract:

Introduction: Methotrexate (MTX) is an antimetabolite used to treat multiple conditions, including neoplastic diseases, severe psoriasis, and rheumatoid arthritis. Skin cancer is the out-of-control growth of abnormal cells in the epidermis, the outermost skin layer, caused by unrepaired DNA damage that triggers mutations. These mutations lead the skin cells to multiply rapidly and form malignant tumors. The aim of this review is to evaluate the risk of skin cancer associated with the use of methotrexate and to suggest regulatory recommendations if required. Methodology: Signal Detection team at Saudi Food and Drug Authority (SFDA) performed a safety review using National Pharmacovigilance Center (NPC) database as well as the World Health Organization (WHO) VigiBase, alongside with literature screening to retrieve related information for assessing the causality between skin cancer and methotrexate. The search conducted in July 2020. Results: Four published articles support the association seen while searching in literature, a recent randomized control trial published in 2020 revealed a statistically significant increase in skin cancer among MTX users. Another study mentioned methotrexate increases the risk of non-melanoma skin cancer when used in combination with immunosuppressant and biologic agents. In addition, the incidence of melanoma for methotrexate users was 3-fold more than the general population in a cohort study of rheumatoid arthritis patients. The last article estimated the risk of cutaneous malignant melanoma (CMM) in a cohort study shows a statistically significant risk increase for CMM was observed in MTX exposed patients. The WHO database (VigiBase) searched for individual case safety reports (ICSRs) reported for “Skin Cancer” and 'Methotrexate' use, which yielded 121 ICSRs. The initial review revealed that 106 cases are insufficiently documented for proper medical assessment. However, the remaining fifteen cases have extensively evaluated by applying the WHO criteria of causality assessment. As a result, 30 percent of the cases showed that MTX could possibly cause skin cancer; five cases provide unlikely association and five un-assessable cases due to lack of information. The Saudi NPC database searched to retrieve any reported cases for the combined terms methotrexate/skin cancer; however, no local cases reported up to date. The data mining of the observed and the expected reporting rate for drug/adverse drug reaction pair is estimated using information component (IC), a tool developed by the WHO Uppsala Monitoring Centre to measure the reporting ratio. Positive IC reflects higher statistical association, while negative values translated as a less statistical association, considering the null value equal to zero. Results showed that a combination of 'Methotrexate' and 'Skin cancer' observed more than expected when compared to other medications in the WHO database (IC value is 1.2). Conclusion: The weighted cumulative pieces of evidence identified from global cases, data mining, and published literature are sufficient to support a causal association between the risk of skin cancer and methotrexate. Therefore, health care professionals should be aware of this possible risk and may consider monitoring any signs or symptoms of skin cancer in patients treated with methotrexate.

Keywords: methotrexate, skin cancer, signal detection, pharmacovigilance

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1102 Fast Terminal Sliding Mode Controller For Quadrotor UAV

Authors: Vahid Tabrizi, Reza GHasemi, Ahmadreza Vali

Abstract:

This paper presents robust nonlinear control law for a quadrotor UAV using fast terminal sliding mode control. Fast terminal sliding mode idea is used for introducing a nonlinear sliding variable that guarantees the finite time convergence in sliding phase. Then, in reaching phase for removing chattering and producing smooth control signal, continuous approximation idea is used. Simulation results show that the proposed algorithm is robust against parameter uncertainty and has better performance than conventional sliding mode for controlling a quadrotor UAV.

Keywords: quadrotor UAV, fast terminal sliding mode, second order sliding mode t

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1101 Performance Analysis of Wireless Sensor Networks in Areas for Sports Activities and Environmental Preservation

Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Ítalo de Pontes Oliveira

Abstract:

This paper presents a analysis of performance the Received Strength Signal Indicator (RSSI) to Wireless Sensor Networks, with a finality of investigate a behavior of ZigBee devices operating into real environments. The test of performance was realize using two Series 1 ZigBee Module and two modules of development Arduino Uno R3, evaluating in this form a measurements of RSSI into environments like places of sports, preservation forests and water reservoir.

Keywords: wireless sensor networks, RSSI, Arduino, environments

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1100 Computational Tool for Surface Electromyography Analysis; an Easy Way for Non-Engineers

Authors: Fabiano Araujo Soares, Sauro Emerick Salomoni, Joao Paulo Lima da Silva, Igor Luiz Moura, Adson Ferreira da Rocha

Abstract:

This paper presents a tool developed in the Matlab platform. It was developed to simplify the analysis of surface electromyography signals (S-EMG) in a way accessible to users that are not familiarized with signal processing procedures. The tool receives data by commands in window fields and generates results as graphics and excel tables. The underlying math of each S-EMG estimator is presented. Setup window and result graphics are presented. The tool was presented to four non-engineer users and all of them managed to appropriately use it after a 5 minutes instruction period.

Keywords: S-EMG estimators, electromyography, surface electromyography, ARV, RMS, MDF, MNF, CV

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1099 Surface Topography Measurement by Confocal Spectral Interferometry

Authors: A. Manallah, C. Meier

Abstract:

Confocal spectral interferometry (CSI) is an innovative optical method for determining microtopography of surfaces and thickness of transparent layers, based on the combination of two optical principles: confocal imaging, and spectral interferometry. Confocal optical system images at each instant a single point of the sample. The whole surface is reconstructed by plan scanning. The interference signal generated by mixing two white-light beams is analyzed using a spectrometer. In this work, five ‘rugotests’ of known standard roughnesses are investigated. The topography is then measured and illustrated, and the equivalent roughness is determined and compared with the standard values.

Keywords: confocal spectral interferometry, nondestructive testing, optical metrology, surface topography, roughness

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1098 Determination of Concentrated State Using Multiple EEG Channels

Authors: Tae Jin Choi, Jong Ok Kim, Sang Min Jin, Gilwon Yoon

Abstract:

Analysis of EEG brainwave provides information on mental or emotional states. One of the particular states that can have various applications in human machine interface (HMI) is concentration. 8-channel EEG signals were measured and analyzed. The concentration index was compared during resting and concentrating periods. Among eight channels, locations the frontal lobe (Fp1 and Fp2) showed a clear increase of the concentration index during concentration regardless of subjects. The rest six channels produced conflicting observations depending on subjects. At this time, it is not clear whether individual difference or how to concentrate made these results for the rest six channels. Nevertheless, it is expected that Fp1 and Fp2 are promising locations for extracting control signal for HMI applications.

Keywords: concentration, EEG, human machine interface, biophysical

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1097 Broadcasting Stabilization for Dynamical Multi-Agent Systems

Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

Abstract:

This paper deals with a stabilization problem for multi-agent systems, when all agents in a multi-agent system receive the same broadcasting control signal and the controller can measure not each agent output but the sum of all agent outputs. It is analytically shown that when the sum of all agent outputs is bounded with a certain broadcasting controller for a given reference, each agent output is separately bounded:stabilization of the sum of agent outputs always results in the stability of every agent output. A numerical example is presented to illustrate our theoretic findings in this paper.

Keywords: broadcasting control, multi-agent system, transfer function, stabilization

Procedia PDF Downloads 385