Search results for: signal amplification

Authors: Eusebio A. Jiménez-Arévalo, Deifilia Ahuatzi-Chacón, Juvencio Galíndez-Mayer, Cleotilde Juárez-Ramírez, Nora Ruiz-Ordaz

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Bendiocarb is a known toxic xenobiotic that presents acute and chronic risks for freshwater invertebrates and estuarine and marine biota; thus, the treatment of water contaminated with the insecticide is of concern. In this paper, a bacterial community with the capacity to grow in bendiocarb as its sole carbon and nitrogen source was isolated by enrichment techniques in batch culture, from samples of a composting plant located in the northeast of Mexico City. Eight cultivable bacteria were isolated from the microbial community, by PCR amplification of 16 rDNA; Pseudoxanthomonas spadix (NC_016147.2, 98%), Ochrobacterium anthropi (NC_009668.1, 97%), Staphylococcus capitis (NZ_CP007601.1, 99%), Bosea thiooxidans. (NZ_LMAR01000067.1, 99%), Pseudomonas denitrificans. (NC_020829.1, 99%), Agromyces sp. (NZ_LMKQ01000001.1, 98%), Bacillus thuringiensis. (NC_022873.1, 97%), Pseudomonas alkylphenolia (NZ_CP009048.1, 98%). NCBI accession numbers and percentage of similarity are indicated in parentheses. These bacteria were regarded as the isolated species for having the best similarity matches. The ability to degrade bendiocarb by the immobilized bacterial community in a packed bed biofilm reactor, using as support volcanic stone fragments (tezontle), was evaluated. The reactor system was operated in batch using mineral salts medium and 30 mg/L of bendiocarb as carbon and nitrogen source. With this system, an overall removal efficiency (η_bend) rounding 90%, was reached.

Keywords: bendiocarb, biodegradation, biofilm reactor, carbamate insecticide

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Authors: Zhihui Liu, Dongmei Hao, Qian Qiu, Yang An, Lin Yang, Song Zhang, Yimin Yang, Xuwen Li, Dingchang Zheng

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Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor.

Keywords: electrohysterogram, feature, preterm labor, term labor

Procedia PDF Downloads 558

Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, Cassandra R. Rickertsen, Kamala Clark-Swanson, Scott A. Whitmire, Kristin R. Swanson

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Glioblastoma Multiforme (GBM), the most common primary brain tumor, often presents with hyperintensity on T2-weighted or T2-weighted fluid attenuated inversion recovery (T2/FLAIR) magnetic resonance imaging (MRI). This hyperintensity corresponds with vasogenic edema, however there are likely many infiltrating tumor cells within the hyperintensity as well. While MRIs do not directly indicate tumor cells, MRIs do reflect the microenvironmental water abnormalities caused by the presence of tumor cells and edema. The inherent heterogeneity and resulting MRI features of GBMs complicate assessing disease response. To understand how hyperintensity on T2/FLAIR MRI may correlate with edema in the extracellular space (ECS), a multi-compartmental MRI signal equation which takes into account tissue compartments and their associated volumes with input coming from a mathematical model of glioma growth that incorporates edema formation was explored. The reasonableness of two possible extracellular space schema was evaluated by varying the T2 of the edema compartment and calculating the possible resulting T2s in tumor and peripheral edema. In the mathematical model, gliomas were comprised of vasculature and three tumor cellular phenotypes: normoxic, hypoxic, and necrotic. Edema was characterized as fluid leaking from abnormal tumor vessels. Spatial maps of tumor cell density and edema for virtual tumors were simulated with different rates of proliferation and invasion and various ECS expansion schemes. These spatial maps were then passed into a multi-compartmental MRI signal model for generating simulated T2/FLAIR MR images. Individual compartments’ T2 values in the signal equation were either from literature or estimated and the T2 for edema specifically was varied over a wide range (200 ms – 9200 ms). T2 maps were calculated from simulated images. T2 values based on simulated images were evaluated for regions of interest (ROIs) in normal appearing white matter, tumor, and peripheral edema. The ROI T2 values were compared to T2 values reported in literature. The expanding scheme of extracellular space is had T2 values similar to the literature calculated values. The static scheme of extracellular space had a much lower T2 values and no matter what T2 was associated with edema, the intensities did not come close to literature values. Expanding the extracellular space is necessary to achieve simulated edema intensities commiserate with acquired MRIs.

Keywords: extracellular space, glioblastoma multiforme, magnetic resonance imaging, mathematical modeling

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Authors: T. Vijayashree, A. Gopal

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The aim of the work is to classify and authenticate medicinal plant materials and herbs widely used for Indian herbal medicinal preparation. The quality and authenticity of these raw materials are to be ensured for the preparation of herbal medicines. These raw materials are to be carefully screened, analyzed and documented due to mistaken of look-alike materials which do not have medicinal characteristics.

Keywords: authenticity, standardization, principal component analysis, imaging processing, signal processing

Procedia PDF Downloads 238

Authors: Vitaliy Petrov, Natalia Shusharina, Vitaliy Kasymov, Maksim Patrushev, Evgeny Bogdanov

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The leading worldwide death reasons are ischemic heart disease and other cardiovascular illnesses. Generally, the common symptom is high blood pressure. Long-time blood pressure control is very important for the prophylaxis, correct diagnosis and timely therapy. Non-invasive methods which are based on Korotkoff sounds are impossible to apply often and for a long time. Implantable devices can combine longtime monitoring with high accuracy of measurements. The main purpose of this work is to create a real-time monitoring system for decreasing the death rate from cardiovascular diseases. These days implantable electronic devices began to play an important role in medicine. Usually implantable devices consist of a transmitter, powering which could be wireless with a special made battery and measurement circuit. Common problems in making implantable devices are short lifetime of the battery, big size and biocompatibility. In these work, blood pressure measure will be the focus because it’s one of the main symptoms of cardiovascular diseases. Our device will consist of three parts: the implantable pressure sensor, external transmitter and automated workstation in a hospital. The Implantable part of pressure sensors could be based on piezoresistive or capacitive technologies. Both sensors have some advantages and some limitations. The Developed circuit is based on a small capacitive sensor which is made of the technology of microelectromechanical systems (MEMS). The Capacitive sensor can provide high sensitivity, low power consumption and minimum hysteresis compared to the piezoresistive sensor. For this device, it was selected the oscillator-based circuit where frequency depends from the capacitance of sensor hence from capacitance one can calculate pressure. The external device (transmitter) used for wireless charging and signal transmission. Some implant devices for these applications are passive, the external device sends radio wave signal on internal LC circuit device. The external device gets reflected the signal from the implant and from a change of frequency is possible to calculate changing of capacitance and then blood pressure. However, this method has some disadvantages, such as the patient position dependence and static using. Developed implantable device doesn’t have these disadvantages and sends blood pressure data to the external part in real-time. The external device continuously sends information about blood pressure to hospital cloud service for analysis by a physician. Doctor’s automated workstation at the hospital also acts as a dashboard, which displays actual medical data of patients (which require attention) and stores it in cloud service. Usually, critical heart conditions occur few hours before heart attack but the device is able to send an alarm signal to the hospital for an early action of medical service. The system was tested with wireless charging and data transmission. These results can be used for ASIC design for MEMS pressure sensor.

Keywords: MEMS sensor, RF power, wireless data, oscillator-based circuit

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Authors: Katalin Gombos, Bence Gálik, Krisztina Ildikó Kalács, Krisztina Gödöny, Ákos Várnagy, József Bódis, Attila Gyenesei, Gábor L. Kovács

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Although non-invasive pre-implantation genetic testing for aneuploidy (NIPGT-A) is potentially appropriate to assess chromosomal ploidy of the embryo, practical application of it in a routine IVF center has not been started in the absence of a recommendation. We developed a comprehensive workflow for a clinically applicable strategy for NIPGT-A based on next-generation sequencing (NGS) technology. We performed MALBAC whole genome amplification and NGS on spent blastocyst culture media of Day 3 embryos fertilized with intra-cytoplasmic sperm injection (ICSI). Spent embryonic culture media of morphologically good quality score embryos were enrolled in further analysis with the blank culture media as background control. Chromosomal abnormalities were identified by an optimized bioinformatics pipeline applying a copy number variation (CNV) detecting algorithm. We demonstrate a comprehensive workflow covering both wet- and dry-lab procedures supporting a clinically applicable strategy for NIPGT-A. It can be carried out within 48 h which is critical for the same-cycle blastocyst transfer, but also suitable for “freeze all” and “elective frozen embryo” strategies. The described integrated approach of non-invasive evaluation of embryonic DNA content of the culture media can potentially supplement existing pre-implantation genetic screening methods.

Keywords: next generation sequencing, in vitro fertilization, embryo assessment, non-invasive pre-implantation genetic testing

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Authors: M. A. Gad, A. Z. Al-Herrawy

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Microsporidia comprises various pathogenic species can infect humans by means of water. Moreover, chlorine disinfection of drinking-water has limitations against this protozoan pathogen. A total of 48 water samples were collected from two drinking water treatment plants having two different filtration systems (slow sand filter and rapid sand filter) during one year period. Samples were collected from inlet and outlet of each plant. Samples were separately filtrated through nitrocellulose membrane (142 mm, 0.45 µm), then eluted and centrifuged. The obtained pellet from each sample was subjected to DNA extraction, then, amplification using genus-specific primer for microsporidia. Each microsporidia-PCR positive sample was performed by two species specific primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis. The results of the present study showed that the percentage of removal for microsporidia through different treatment processes reached its highest rate in the station using slow sand filters (100%), while the removal by rapid sand filter system was 81.8%. Statistically, the two different drinking water treatment plants (slow and rapid) had significant effect for removal of microsporidia. Molecular identification of microsporidia-PCR positive samples using two different primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis showed the presence of the two pervious species in the inlet water of the two stations, while Encephalitozoon intestinalis was detected in the outlet water only. In conclusion, the appearance of virulent microsporidia in treated drinking water may cause potential health threat.

Keywords: removal, efficacy, microsporidia, drinking water treatment plants, PCR

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Authors: Ruolan Zhang, Ryo Imai, Naoko Senda, Tomoyuki Sakai

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Enzymes have attracted increasing attentions in industrial manufacturing for their applicability in catalyzing complex chemical reactions under mild conditions. Directed evolution has become a powerful approach to optimize enzymes and exploit their full potentials under the circumstance of insufficient structure-function knowledge. With the incorporation of cell-free synthetic biotechnology, rapid enzyme synthesis can be realized because no cloning procedure such as transfection is needed. Its open environment also enables direct enzyme measurement. These properties of cell-free biotechnology lead to excellent throughput of enzymes generation. However, the capabilities of current screening methods have limitations. Fluorescence-based assay needs applicable fluorescent label, and the reliability of acquired enzymatic activity is influenced by fluorescent label’s binding affinity and photostability. To acquire the natural activity of an enzyme, another method is to combine pre-screening step and high-performance liquid chromatography (HPLC) measurement. But its throughput is limited by necessary time investment. Hundreds of variants are selected from libraries, and their enzymatic activities are then identified one by one by HPLC. The turn-around-time is 30 minutes for one sample by HPLC, which limits the acquirable enzyme improvement within reasonable time. To achieve the real high-throughput enzyme screening, i.e., obtain reliable enzyme improvement within reasonable time, a widely applicable high-throughput measurement of enzymatic reactions is highly demanded. Here, a high-throughput screening method using broadband coherent anti-Stokes Raman spectroscopy (CARS) was proposed. CARS is one of coherent Raman spectroscopy, which can identify label-free chemical components specifically from their inherent molecular vibration. These characteristic vibrational signals are generated from different vibrational modes of chemical bonds. With the broadband CARS, chemicals in one sample can be identified from their signals in one broadband CARS spectrum. Moreover, it can magnify the signal levels to several orders of magnitude greater than spontaneous Raman systems, and therefore has the potential to evaluate chemical's concentration rapidly. As a demonstration of screening with CARS, alcohol dehydrogenase, which converts ethanol and nicotinamide adenine dinucleotide oxidized form (NAD+) to acetaldehyde and nicotinamide adenine dinucleotide reduced form (NADH), was used. The signal of NADH at 1660 cm⁻¹, which is generated from nicotinamide in NADH, was utilized to measure the concentration of it. The evaluation time for CARS signal of NADH was determined to be as short as 0.33 seconds while having a system sensitivity of 2.5 mM. The time course of alcohol dehydrogenase reaction was successfully measured from increasing signal intensity of NADH. This measurement result of CARS was consistent with the result of a conventional method, UV-Vis. CARS is expected to have application in high-throughput enzyme screening and realize more reliable enzyme improvement within reasonable time.

Keywords: Coherent Anti-Stokes Raman Spectroscopy, CARS, directed evolution, enzyme screening, Raman spectroscopy

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Authors: Sylvain Amailland, Jean-Hugh Thomas, Charles Pézerat, Romuald Boucheron, Jean-Claude Pascal

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The noise requirements for naval and research vessels have seen an increasing demand for quieter ships in order to fulfil current regulations and to reduce the effects on marine life. Hence, new methods dedicated to the characterization of propeller noise, which is the main source of noise in the far-field, are needed. The study of cavitating propellers in closed-section is interesting for analyzing hydrodynamic performance but could involve significant difficulties for hydroacoustic study, especially due to reverberation and boundary layer noise in the tunnel. The aim of this paper is to present a numerical methodology for the identification of hydroacoustic sources on marine propellers using hydrophone arrays in a large hydrodynamic tunnel. The main difficulties are linked to the reverberation of the tunnel and the boundary layer noise that strongly reduce the signal-to-noise ratio. In this paper it is proposed to estimate the reflection coefficients using an inverse method and some reference transfer functions measured in the tunnel. This approach allows to reduce the uncertainties of the propagation model used in the inverse problem. In order to reduce the boundary layer noise, a cleaning algorithm taking advantage of the low rank and sparse structure of the cross-spectrum matrices of the acoustic and the boundary layer noise is presented. This approach allows to recover the acoustic signal even well under the boundary layer noise. The improvement brought by this method is visible on acoustic maps resulting from beamforming and DAMAS algorithms.

Keywords: acoustic imaging, boundary layer noise denoising, inverse problems, model adaptation

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Authors: Faheema Khan

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In order to investigate the influence of genetic background on salt tolerance in Soybean (Glycine max) ten soybean genotypes released/notified in India were selected. (Pusa-20, Pusa-40, Pusa-37, Pusa-16, Pusa-24, Pusa-22, BRAGG, PK-416, PK-1042, and DS-9712). The 10-day-old seedlings were subjected to 0, 25, 50, 75, 100, 125, and 150 mM NaCl for 15 days. Plant growth, leaf osmotic adjustment, and RAPD analysis were studied. In comparison to control plants, the plant growth in all genotypes was decreased by salt stress, respectively. Salt stress decreased leaf osmotic potential in all genotypes however the maximum reduction was observed in genotype Pusa-24 followed by PK-416 and Pusa-20. The difference in osmotic adjustment between all the genotypes was correlated with the concentrations of ion examined such as Na+ and the leaf proline concentration. These results suggest that the genotypic variation for salt tolerance can be partially accounted for by plant physiological measures. The genetic polymorphisms between soybean genotypes differing in response to salt stress were characterized using 25 RAPD primers. These primers generated a total of 1640 amplification products, among which 1615 were found to be polymorphic. A very high degree of polymorphism (98.30%) was observed. UPGMA cluster analysis of genetic similarity indices grouped all the genotypes into two major clusters. Intra-clustering within the two clusters precisely grouped the 10 genotypes in sub-cluster as expected from their physiological findings. Our results show that RAPD technique is a sensitive, precise and efficient tool for genomic analysis in soybean genotypes.

Keywords: glycine max, NaCl, RAPD, proteomics

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Authors: Surbhi Aggarwal, Jaishree Paul

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Background: Role of GABA has been implicated in autoimmune diseases like multiple sclerosis, type1 diabetes and rheumatoid arthritis where they modulate the immune response but role in gut inflammation has not been defined. Ulcerative colitis (UC) and diarrhoeal predominant irritable bowel syndrome (IBS-D) both involve inflammation of gastrointestinal tract. UC is a chronic, relapsing and idiopathic inflammation of gut. IBS is a common functional gastrointestinal disorder characterised by abdominal pain, discomfort and alternating bowel habits. Mild inflammation is known to occur in IBS-D. Aim: Aim of this study was to investigate the role of GABA in UC as well as in IBS-D. Materials and methods: Blood and biopsy samples from UC, IBS-D and controls were collected. ELISA was used for measuring level of GABA in serum of UC, IBS-D and controls. RT-PCR analysis was done to determine GABAergic signal system in colon biopsy of UC, IBS-D and controls. RT-PCR was done to check the expression of proinflammatory cytokines. CurveExpert 1.4, Graphpad prism-6 software were used for data analysis. Statistical analysis was done by unpaired, two-way student`s t-test. All sets of data were represented as mean± SEM. A probability level of p < 0.05 was considered statistically significant. Results and conclusion: Significantly decreased level of GABA and altered GABAergic signal system was detected in UC and IBS-D as compared to controls. Significantly increased expression of proinflammatory cytokines was also determined in UC and IBS-D as compared to controls. Hence we conclude that insufficient level of GABA in UC and IBS-D leads to overproduction of proinflammatory cytokines which further contributes to inflammation. GABA may be used as a promising therapeutic target for treatment of gut inflammation or other inflammatory diseases.

Keywords: diarrheal predominant irritable bowel syndrome, γ-aminobutyric acid (GABA), inflammation, ulcerative colitis

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Authors: K. S. Sreejith, C. Shaji

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Though both Arabian Sea and its counterpart Bay of Bengal is forced primarily by the semi-annually reversing monsoons, the spatio-temporal variations of surface waters is very strong in the Arabian Sea as compared to the Bay of Bengal. This study focuses on the inter-annual variability of Sea Surface Temperature (SST) in the Arabian Sea by analysing ERSST dataset which covers 152 years of SST (January 1854 to December 2002) based on the ICOADS in situ observations. To capture the dominant SST oscillations and to understand the inter-annual SST variations at various local regions of the Arabian Sea, wavelet analysis was performed on this long time-series SST dataset. This tool is advantageous over other signal analysing tools like Fourier analysis, based on the fact that it unfolds a time-series data (signal) both in frequency and time domain. This technique makes it easier to determine dominant modes of variability and explain how those modes vary in time. The analysis revealed that pentadal SST oscillations predominate at most of the analysed local regions in the Arabian Sea. From the time information of wavelet analysis, it was interpreted that these cold and warm events of large amplitude occurred during the periods 1870-1890, 1890-1910, 1930-1950, 1980-1990 and 1990-2005. SST oscillations with peaks having period of ~ 2-4 years was found to be significant in the central and eastern regions of Arabian Sea. This indicates that the inter-annual SST variation in the Indian Ocean is affected by the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events.

Keywords: Arabian Sea, ICOADS, inter-annual variation, pentadal oscillation, SST, wavelet analysis

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Authors: Julia Hoefer Martí

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While research has consistently found a significant motherhood wage penalty for heterosexual women, where homosexual women are concerned, evidence has appeared to suggest no effect, or possibly even a wage bonus. This paper presents a model of the household with a public good that requires both a monetary expense and a labour investment, and where the household budget is shared between partners. Lower-wage partners will do relatively more of the household labour while higher-wage partners will specialise in market labour, and the arrival of a child exacerbates this split, resulting in the lower-wage partner taking on even more of the household labour in relative terms. Employers take this gender-sexuality dyad as a signal for employees’ commitment to the labour market after having a child, and use the information when setting wages after employees become parents. Given that women empirically earn lower wages than men, in a heterosexual couple the female partner will often do more of the household labour. However, as not every female partner has a lower wage, this results in an over-adjustment of wages that manifests as an unexplained motherhood wage penalty. On the other hand, in homosexual couples wage distributions are ex ante identical, and gender is no longer a useful signal to employers as to whether the partner is likely to specialise in household labour or market labour. This model is then tested using longitudinal data from the EU Standards of Income and Living Conditions (EU-SILC) to investigate the hypothesis that women experience different wage effects of motherhood depending on their sexual orientation. While heterosexual women receive a significant motherhood wage penalty of 8-10%, homosexual mothers do not receive any significant wage bonus or penalty of motherhood, consistent with the hypothesis presented above.

Keywords: discrimination, gender, motherhood, sexual orientation, labor economics

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Authors: Mojgan Rabiey, Shyamali Roy, Billy Quilty, Ryan Creeth, George Sundin, Robert W. Jackson

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Bacterial canker is a major disease of Prunus species such as cherry (Prunus avium). It is caused by Pseudomonas syringae species including P. syringae pv. syringae (Pss) and P. syringae pv. morsprunorum race 1 (Psm1) and race 2 (Psm2). Concerns over the environmental impact of, and developing resistance to, copper controls call for alternative approaches to disease management. One method of control could be achieved using naturally occurring bacteriophage (phage) infective to the bacterial pathogens. Phages were isolated from soil, leaf, and bark of cherry trees in five locations in the South East of England. The phages were assessed for their host range against strains of Pss, Psm1, and Psm2. The phages exhibited a differential ability to infect and lyse different Pss and Psm isolates as well as some other P. syringae pathovars. However, the phages were unable to infect beneficial bacteria such as Pseudomonas fluorescens. A subset of 18 of these phages were further characterised genetically (Random Amplification of Polymorphic DNA-PCR fingerprinting and sequencing) and using electron microscopy. The phages are tentatively identified as belonging to the order Caudovirales and the families Myoviridae, Podoviridae, and Siphoviridae, with genetic material being dsDNA. Future research will fully sequence the phage genomes. The efficacy of the phage, both individually and in cocktails, to reduce disease progression in vivo will be investigated to understand the potential for practical use of these phages as biocontrol agents.

Keywords: bacteriophage, pseudomonas, bacterial cancker, biological control

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

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Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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Authors: S. Bahrami, A. Rezaie, Z. Boroumand, S. Ghavami

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Neospora caninum is protozoan parasite which can cause a serious disease in dogs and cattle. It has been shown that birds may be a permissive intermediate host for N. caninum since parasite DNA has been detected in tissues from birds. It is showed that embryonated chicken egg can be used as an animal model for experimental infection. The aim of present study was to compare experimental infection of Neospora in chicken and pigeons embryonated eggs. An infection with N. caninum Nc1 isolate was conducted in chicken and pigeons embryonated eggs to evaluate LD50. After calculation of LD50, 2LD50 of tachyzoites were injected to eggs. Macroscopic changes of each embryo were noticed and to investigate the parasite distribution in tissues immunohistochemistry (IHC) and molecular methods were used. In the present study, histopathological changes were considered and sections to those used for histopathological examination including heart, liver, brain and chorioallantoic (CA) membrane were subjected to IHC, too. For PCR procedure, primer pair Np21/Np6 was used for amplification of the Nc5 gene. Pigeon's embryo showed more macroscopic changes than chicken embryo. A hemorrhage of the CA was the main grass lesion. All the infected tissues had histopathological changes. Microscopic examination of tissues revealed acute neosporosis due to hemorrhage, necrosis and infiltration of mononuclear inflammatory cells. Based on IHC and molecular results, the parasite aggregation in the heart was more predominant than in the other tissues. These results reinforce that there is genetic susceptibility to N. caninum in pigeons embryonated eggs like chickens embryonated eggs and provide new insights to research an inexpensive and available animal model for N. caninum.

Keywords: immunohistochemistry, Neospora caninum, PCR, pigeon embryonated egg

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Authors: Eunsong Lee, Gae Baik Kim, Young Pil Kim

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Bisphenol A (BPA) is one of the endocrine disruptors (EDCs), which have been suspected to be associated with reproductive dysfunction and physiological abnormality in human. Since the BPA has been widely used to make plastics and epoxy resins, the leach of BPA from the lining of plastic products has been of major concern, due to its environmental or human exposure issues. The simple detection of BPA based on the self-assembly of aptamer-mediated gold nanoparticles (AuNPs) has been reported elsewhere, yet the detection sensitivity still remains challenging. Here we demonstrate an improved AuNP-based sensor of BPA by using fluorescence-combined AuNP colorimetry in order to overcome the drawback of traditional AuNP sensors. While the anti-BPA aptamer (full length or truncated ssDNA) triggered the self-assembly of unmodified AuNP (citrate-stabilized AuNP) in the presence of BPA at high salt concentrations, no fluorescence signal was observed by the subsequent addition of SYBR Green, due to a small amount of free anti-BPA aptamer. In contrast, the absence of BPA did not cause the self-assembly of AuNPs (no color change by salt-bridged surface stabilization) and high fluorescence signal by SYBP Green, which was due to a large amount of free anti-BPA aptamer. As a result, the quantitative analysis of BPA was achieved using the combination of absorption of AuNP with fluorescence intensity of SYBR green as a function of BPA concentration, which represented more improved detection sensitivity (as low as 1 ppb) than did in the AuNP colorimetric analysis. This method also enabled to detect high BPA in water-soluble extracts from thermal papers with high specificity against BPS and BPF. We suggest that this approach will be alternative for traditional AuNP colorimetric assays in the field of aptamer-based molecular diagnosis.

Keywords: bisphenol A, colorimetric, fluoroscence, gold-aptamer nanobiosensor

Procedia PDF Downloads 182

Authors: Ogbonnaya O. Iroanya, Samson T. Fakorede, Osamudiamen J. Edosa, Hadiat A. Azeez

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The human mitochondrial DNA (mtDNA) is about 17 kbp circular DNA fragments found within the mitochondria together with smaller fragments of 1200 bp known as the control region. Knowledge of variation within populations has been employed in forensic and molecular anthropology studies. The study was aimed at investigating the polymorphic nature of the two hypervariable segments (HVS) of the mtDNA, i.e., HVS1 and HVS2, and to determine the haplogroup distribution among individuals resident in Lagos, Southwestern Nigeria. Peripheral blood samples were obtained from sixty individuals who are not related maternally, followed by DNA extraction and amplification of the extracted DNA using primers specific for the regions under investigation. DNA amplicons were sequenced, and sequenced data were aligned and compared to the revised Cambridge Reference Sequence (rCRS) GenBank Accession number: NC_012920.1) using BioEdit software. Results obtained showed 61 and 52 polymorphic nucleotide positions for HVS1 and HVS2, respectively. While a total of three indels mutation were recorded for HVS1, there were seven for HVS2. Also, transition mutations predominate nucleotide change observed in the study. Genetic diversity (GD) values for HVS1 and HVS2 were estimated to be 84.21 and 90.4%, respectively, while random match probability was 0.17% for HVS1 and 0.89% for HVS2. The study also revealed mixed haplogroups specific to the African (L1-L3) and the Eurasians (U and H) lineages. New polymorphic sites obtained from the study are promising for human identification purposes.

Keywords: hypervariable region, indels, mitochondrial DNA, polymorphism, random match probability

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Authors: Xing Wang, Lin Feng, Xuan Zou, Hongchen liu

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Immediate Implantation after tooth extraction is considered to be the ideal way to retain the alveolar bone, but some scholars believe the aesthetic effect in the Early Implantation case are more reliable. In this study, 89 patients were added to this retrospective study up to 5 years. Assessment indicators was including the survival of the implant (peri-implant infection, implant loosening, shedding, crowns and occlusal), aesthetics (color and fullness gums, papilla height, probing depth, X-ray alveolar crest height, the patient's own aesthetic satisfaction, doctors aesthetics score), repair defects around the implant (peri-implant bone changes in height and thickness, whether the use of autologous bone graft, whether to use absorption/repair manual nonabsorbable material), treatment time, cost and the use of antibiotics.The results demonstrated that there is no significant difference in long-term success rate of immediate implantation, early implantation and delayed implantation (p> 0.05). But the results indicated immediate implantation group could get get better aesthetic results after two years (p< 0.05), but may increase the risk of complications and failures (p< 0.05). High-risk indicators include gingival recession, labial bone wall damage, thin gingival biotypes, planting position and occlusal restoration bad and so on. No matter which type of implanting methods was selected, the extraction methods and bone defect amplification techniques are observed as a significant factors on aesthetic effect (p< 0.05).

Keywords: immediate implantation, long-term effects, aesthetics area, dental implants

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Authors: John E. Muñoz, Jose F. Lopez, David S. Lopez

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Attention Deficit Hyperactivity Disorder (ADHD) is a disorder that affects 1 out of 5 Colombian children, converting into a real public health problem in the country. Conventional treatments such as medication and neuropsychological therapy have been proved to be insufficient in order to decrease high incidence levels of ADHD in the principal Colombian cities. This work demonstrates a design and development of a videogame that uses a brain computer interface not only to serve as an input device but also as a tool to monitor neurophysiologic signal. The video game named “The Harvest Challenge” puts a cultural scene of a Colombian coffee grower in its context, where a player can use his/her avatar in three mini games created in order to reinforce four fundamental aspects: i) waiting ability, ii) planning ability, iii) ability to follow instructions and iv) ability to achieve objectives. The details of this collaborative designing process of the multimedia tool according to the exact clinic necessities and the description of interaction proposals are presented through the mental stages of attention and relaxation. The final videogame is presented as a tool for sustained attention training in children with ADHD using as an action mechanism the neuromodulation of Beta and Theta waves through an electrode located in the central part of the front lobe of the brain. The processing of an electroencephalographic signal is produced automatically inside the videogame allowing to generate a report of the theta/beta ratio evolution - a biological marker, which has been demonstrated to be a sufficient measure to discriminate of children with deficit and without.

Keywords: BCI, neuromodulation, ADHD, videogame, neurofeedback, theta/beta ratio

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Authors: Subhajit Das, Nirjhar Dhang

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Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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Authors: Sevde Altuntas, Fatih Buyukserin

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Alzheimer’s disease is responsible for irreversible neural damage of brain parts. One of the disease markers is Amyloid-β 1-42 protein that accumulates in the brain in the form plaques. The basic problem for detection of the protein is the low amount of protein that cannot be detected properly in body liquids such as blood, saliva or urine. To solve this problem, tests like ELISA or PCR are proposed which are expensive, require specialized personnel and can contain complex protocols. Therefore, Surface-enhanced Raman Spectroscopy (SERS) a good candidate for detection of Amyloid-β 1-42 protein. Because the spectroscopic technique can potentially allow even single molecule detection from liquid and solid surfaces. Besides SERS signal can be improved by using nanopattern surface and also is specific to molecules. In this context, our study proposes to fabricate diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin - T to detect low concentrations of Amyloid-β 1-42 protein in water and artificial saliva medium by the enhancement of protein SERS signal. The nanopatterned PC surface that was used to enhance SERS signal was fabricated by using Anodic Alumina Membranes (AAM) as a template. It is possible to produce AAMs with different column structures and varying thicknesses depending on voltage and anodization time. After fabrication process, the pore diameter of AAMs can be arranged with dilute acid solution treatment. In this study, two different columns structures were prepared. After a surface modification to decrease their surface energy, AAMs were treated with PC solution. Following the solvent evaporation, nanopatterned PC films with tunable pillared structures were peeled off from the membrane surface. The PC film was then modified with Au and Thioflavin-T for the detection of Amyloid-β 1-42 protein. The protein detection studies were conducted first in water via this biosensor platform. Same measurements were conducted in artificial saliva to detect the presence of Amyloid Amyloid-β 1-42 protein. SEM, SERS and contact angle measurements were carried out for the characterization of different surfaces and further demonstration of the protein attachment. SERS enhancement factor calculations were also completed via experimental results. As a result, our research group fabricated diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin-T to detect low concentrations of Alzheimer’s Amiloid – β protein in water and artificial saliva medium. This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) Grant No: 214Z167.

Keywords: alzheimer, anodic aluminum oxide, nanotopography, surface enhanced Raman spectroscopy

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Authors: D. S. Malatesh, K. J. Ananda, C. Ansar Kamran, K. Ganesh Udupa

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Dirofilaria repens is a mosquito-borne filarioid nematode of dogs and other carnivores and accidentally affects humans. D. repens is reported in many countries, including India. Subcutaneous dirofilariosis caused by D. repens is a zoonotic disease, widely distributed throughout Europe, Asia, and Africa, with higher prevalence reported in dogs from Sri Lanka (30-60%), Iran (61%) and Italy (21-25%). Dirofilariasis in dogs was diagnosed by detection of microfilariae in blood. Identification of different Dirofilaria species was done by using molecular methods like polymerase chain reaction (PCR). Even though many researchers reported molecular evidence of D. repens across India, to our best knowledge there is no data available on molecular diagnosis of D. repens in dogs and its zoonotic implication in Karnataka state a southern state in India. The aim of the present study was to identify the Dirofilaria species occurring in dogs from Karnataka, India. Out of 310 samples screened for the presence of microfilariae using traditional diagnostic methods, 99 (31.93%) were positive for the presence of microfilariae. Based on the morphometry, the microfilariae were identified as D. repens. For confirmation of species, the samples were subjected to PCR using pan filarial primers (DIDR-F1, DIDR-R1) for amplification of internal transcribed spacer region 2 (ITS2) of the ribosomal DNA. The PCR product of 484 base pairs on agarose gel was indicative of D. repens. Hence, a single PCR reaction using pan filarial primers can be used to differentiate filarial species found in dogs. The present study confirms that dirofilarial species occurring in dogs from Karnataka is D. repens and further sequencing studies are needed for genotypic characterization of D. repens.

Keywords: Dirofilaria repens, molecular characterization, polymerase chain reaction, Karnataka, India

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Authors: Kumar Kanudkuri, A. Sandhya

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Typically, in a MRI clinical setting, there are several protocols run, each indicated for a specific anatomy and disease condition. However, these protocols or parameters within them can change over time due to changes to the recommendations by the physician groups or updates in the software or by the availability of new technologies. Most of the time, the changes are performed by the MRI technologist to account for either time, coverage, physiological, or Specific Absorbtion Rate (SAR ) reasons. However, giving properly guidelines to MRI technologist is important so that they do not change the parameters that negatively impact the image quality. Typically a standard American College of Radiology (ACR) MRI phantom is used for Quality Control (QC) in order to guarantee that the primary objectives of MRI are met. The visual evaluation of quality depends on the operator/reviewer and might change amongst operators as well as for the same operator at various times. Therefore, overcoming these constraints is essential for a more impartial evaluation of quality. This makes quantitative estimation of image quality (IQ) metrics for MRI quality control is very important. So in order to solve this problem, we proposed that there is a need for a robust, open-source, and automated MRI image control tool. The Designed and developed an automatic analysis tool for measuring MRI image quality (IQ) metrics like Signal to Noise Ratio (SNR), Signal to Noise Ratio Uniformity (SNRU), Visual Information Fidelity (VIF), Feature Similarity (FSIM), Gray level co-occurrence matrix (GLCM), slice thickness accuracy, slice position accuracy, High contrast spatial resolution) provided good accuracy assessment. A standardized quality report has generated that incorporates metrics that impact diagnostic quality.

Keywords: ACR MRI phantom, MRI image quality metrics, SNRU, VIF, FSIM, GLCM, slice thickness accuracy, slice position accuracy

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Adel M. Zakri, Mohammed A. Al-Saleh, Judith. K. Brown, Ali M. Idris

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Betasatellites are small circular single stranded DNA molecules found associated with begomoviruses on field symptomatic plants. Their genome size is about half that of the helper begomovirus, ranging between 1.3 and 1.4 kb. The helper begomoviruses are usually members of the family Geminiviridae. Okra leaves showing vein thickening were collected from okra plants growing in Jazan, Saudi Arabia. Total DNA was extracted from leaves and used as a template to amplify circular DNA using rolling circle amplification (RCA) technology. Products were digested with PstI to linearize the helper viral genome(s), and associated DNA satellite(s), yielding a 2.8kbp and 1.4kbp fragment, respectively. The linearized fragments were cloned into the pGEM-5Zf (+) vector and subjected to DNA sequencing. The 2.8 kb fragment was identified as Cotton leaf curl Gezira virus genome, at 2780bp, an isolate closely related to strains reported previously from Saudi Arabia. A clone obtained from the 1.4 kb fragments he 1.4kb was blasted to GeneBank database found to be a betasatellite. The genome of betasatellite was 1357-bp in size. It was found to be a recombinant containing one fragment (877-bp) that shared 91% nt identity with Cotton leaf curl Gezira betasatellite [KM279620], and a smaller fragment [133--bp) that shared 86% nt identity with Tomato leaf curl Sudan virus [JX483708]. This satellite is thus a recombinant between a malvaceous-infecting satellite and a solanaceous-infecting begomovirus.

Keywords: begomovirus, betasatellites, cotton leaf curl Gezira virus, okra plants

Procedia PDF Downloads 335

Authors: Ha T. T. Ly, Truc B. Truc, Hai N. Truong, Mai P. T. Nguyen, Ngoc D. Ngo, Khanh V. Tran, Hai T. Le

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Beta thalassemia is one of the most common inherited blood disorders, which is characterized by decreased or absent in beta globin expression. Patients with Beta thalassemia whose anemia is not so severe as to necessitate transfusions are said to have thalassemia intermedia. Objective: The goal of this study is prenatal diagnosis for pregnancy woman with Beta thalassemia intermedia and her husband with Beta thalassemia carrier at high risk of Beta thalassemia major in Northern of Vietnam. Material and method: The family has a 6 years-old compound heterozygous thalassemia major for CD71/72(+A) and Hbb:c. -78A>G/nt-28(A>G) male child. The father was heterozygous for CD71/72(+A) mutation which is Beta plus type and the mother was compound heterozygosity of two different variants, namely, Hbb: c. -78A>G/nt-28(A>G) and CD26(A-G) HbE. Prenatal Beta thalassemia mutation detection in fetal DNA was carried out using multiplex Amplification-refractory mutation system ARMS-PCR and confirmed by direct Sanger-sequencing Hbb gene. Prenatal diagnoses were perfomed by amniotic fluid sampling from pregnant woman in the 16-18th week of pregnancy after the genotypes of parents of the probands were identified. Result: When amniotic fluid sample was analyzed for Beta globin gene (Hbb), we found that the genotype is heterozygous for CD71/72(+A) and CD26(A-G) HbE. This genotype is different from the 1st child of this family. Conclusion: Prenatal diagnosis helps the parents to know the genotype and the thalassemia status of the fetus, so they can have early decision on their pregnancy. Genetic diagnosis provided a useful method in diagnosis for familial members in pedigree, genetic counseling and prenatal diagnosis.

Keywords: beta thalassemia intermedia, Hbb gene, pedigree, prenatal diagnosis

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Authors: Muhammad S. Sajid, A. Iqbal, A. Kausar, M. Jawad-ul-Hassan, Z. Iqbal, Hafiz M. Rizwan, M. Saqib

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Among the ixodid ticks, species of genus Hyalomma are of prime importance as they can survive in harsh conditions better than those of other species. Similarly, among various tick-borne pathogens, Theileria (T.) annulata, the causative agent of tropical theileriosis in large ruminants, is responsible for reduced productivity and ultimately substantial economic losses due to morbidity and mortality. The present study was planned to screening of vector ticks through molecular techniques for determination of tick-borne theileriosis in district Toba Tek Singh (T. T. Singh), Punjab, Pakistan. For this purpose, among the collected ticks (n = 2252) from livestock and their microclimate, Hyalomma spp. were subjected to dissection for procurement of salivary glands (SGs) and formation of pool (averaged 8 acini in each pool). Each pool of acini was used for DNA extraction, quantification and primer-specific amplification of 18S rRNA of Theileria (T.) annulata. The amplicons were electrophoresed using 1.8% agarose gel following by imaging to identify the band specific for T. annulata. For confirmation, the positive amplicons were subjected to sequencing, BLAST analysis and homology search using NCBI software. The number of Theileria-infected acini was significantly higher (P < 0.05) in female ticks vs male ticks, infesting ticks vs questing ticks and riverine-collected vs non-riverine collected. The data provides first attempt to quantify the vectoral capacity of ixodid ticks in Pakistan for T. annulata which can be helpful in estimation of risk analysis of theileriosis to the domestic livestock population of the country.

Keywords: Hyalomma anatolicum, ixodids, PCR, Theileria annulata

Procedia PDF Downloads 279