Search results for: detecting unknown viruses

Authors: Tianqi Yu, Yingnan Ding, Yina Zhang, Yulan Liu, Yahui Li, Jing Lei, Jiyong Zhou, Suquan Song, Boli Hu

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Circular RNAs (circRNAs) play critical roles in various diseases. However, whether and how circular RNA regulates influenza A virus (IAV) infection is unknown. Here, we studied the role of circular RNA GATA Zinc Finger Domain Containing 2A (circ-GATAD2A) in the replication of IAV H1N1 in A549 cells. Circ-GATAD2A was formed upon H1N1 infection. Knockdown of circ-GATAD2A in A549 cells enhanced autophagy and inhibited H1N1 replication. By contrast, overexpression of circ-GATAD2A impaired autophagy and promoted H1N1 replication. Similarly, knockout of vacuolar protein sorting 34 (VPS34) blocked autophagy and increased H1N1 replication. However, the expression of circ-GATAD2A could not further enhance H1N1 replication in VPS34 knockout cells. Collectively, these data indicated that circ-GATAD2A promotes the replication of H1N1 by inhibiting autophagy.

Keywords: autophagy, circ-GATAD2A, H1N1, replication

Procedia PDF Downloads 142

Authors: Abdulla Almulla, Wafaa Mahdi

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Building materials can make a significant contribution to the level of natural radioactivity in closed dwelling areas. Therefore, developing an expert system for monitoring the activity concentrations (ACs) of naturally occurring radioactive materials (NORMs) existing in building materials is useful for limiting the population’s exposure to gamma radiation emitted from those materials. The present work not only is aimed at examining the indoor radon concentration emitted by the building materials that are originated from various countries but are commercially available in Kuwait, but also is aimed at developing an expert system for monitoring the radiation emitted from these materials and classifying it as normal (acceptable) or dangerous (unacceptable). This system makes it possible to always monitor any radiological risks to human health. When detecting high doses of radiation, the system gives warning messages.

Keywords: building materials, NORMs, HNBRA, radionuclides, activity concentrations, expert systems

Procedia PDF Downloads 146

Authors: Hyun-Woo Cho

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The detection and identification of multivariate manufacturing processes are quite important in order to maintain good product quality. Unusual behaviors or events encountered during its operation can have a serious impact on the process and product quality. Thus they should be detected and identified as soon as possible. This paper focused on the efficient representation of process measurement data in detecting and identifying abnormalities. This qualitative method is effective in representing fault patterns of process data. In addition, it is quite sensitive to measurement noise so that reliable outcomes can be obtained. To evaluate its performance a simulation process was utilized, and the effect of adopting linear and nonlinear methods in the detection and identification was tested with different simulation data. It has shown that the use of a nonlinear technique produced more satisfactory and more robust results for the simulation data sets. This monitoring framework can help operating personnel to detect the occurrence of process abnormalities and identify their assignable causes in an on-line or real-time basis.

Keywords: detection, monitoring, identification, measurement data, multivariate techniques

Procedia PDF Downloads 224

Authors: Mohammadreza Aghasadeghi, Mojtaba Hamidi-Fard, Seyed Amir Sadeghi, Ashkan Noorbakhsh

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Introduction: HIV is known as one of the most important pathogens and mortality in all human societies, but unfortunately, no definitive cure has been found for it. Due to its weakened immune system, this virus causes a variety of primary and secondary opportunistic infections. Cytomegalovirus (CMV) is one of the most relevant opportunistic viruses seen in HIV-positive people that cause various infections in HIV-positive people. This virus causes various infections in HIV-positive people, such as retinal infection (CMVR), gastrointestinal infections, diarrhea, severe weight loss, and cerebrospinal fluid problems. These various infections make it important to evaluate the prevalence of CMV in HIV-positive people to diagnose it quickly and in a timely manner. This infection in HIV-positive people reduces life expectancy and causes serious harm to patients. However, a simple test in HIV-positive people can prevent the virus from progressing. Material and Methods: In this study, we collected 200 blood samples (including 147 men and 53 women) from HIV-positive individuals and examined the frequency of CMV-DNA in these cases by real-time PCR method. In the next step, the data was analyzed by SPSS software, and then we obtained the relationship between age, sex, and the frequency of CMV in HIV-positive individuals. Results: The total frequency of CMV DNA was about 59%, which is a relatively high prevalence due to the age range of the subjects. The frequency in men was 61.2% and 52.8% in women. This frequency was also higher in males than females. We also observed more frequency in two age groups of 16 to 30 years and 31 to 45 years. Discussion: Due to the high prevalence of CMV in HIV-positive individuals and causing serious problems in this group of people, this study was shown that both the patients and the community should pay more attention to this issue. Ministry of Health, as a stakeholder organization, can make CMV DNA testing mandatory as soon as a person is HIV positive.

Keywords: CMV, HIV, AIDS, real-time PCR, SPSS

Procedia PDF Downloads 201

Authors: Elyas Shivanian

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In this paper, the spectral meshless radial point interpolation (SMRPI) technique is applied to the Cauchy problems of two-dimensional elliptic PDEs in doubly connected domains. It is obtained the unknown data on the inner boundary of the domain while overspecified boundary data are imposed on the outer boundary of the domain by using the SMRPI. Shape functions, which are constructed through point interpolation method using the radial basis functions, help us to treat problem locally with the aim of high order convergence rate. In this way, localization in SMRPI can reduce the ill-conditioning for Cauchy problem. Furthermore, we improve previous results and it is revealed the SMRPI is more accurate and stable by adding strong perturbations.

Keywords: cauchy problem, doubly connected domain, radial basis function, shape function

Procedia PDF Downloads 269

Authors: Alden Boby, Dane Brown, James Connan

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Character recognition is a well-researched topic across disciplines. Regardless, creating a solution that can cater to multiple situations is still challenging. Vehicle licence plates lack an international standard, meaning that different countries and regions have their own licence plate format. A problem that arises from this is that the typefaces and designs from different regions make it difficult to create a solution that can cater to a wide range of licence plates. The main issue concerning detection is the character recognition stage. This paper aims to create an object detection-based character recognition model trained on a custom dataset that consists of typefaces of licence plates from various regions. Given that characters have featured consistently maintained across an array of fonts, YOLO can be trained to recognise characters based on these features, which may provide better performance than OCR methods such as Tesseract OCR.

Keywords: computer vision, character recognition, licence plate recognition, object detection

Procedia PDF Downloads 108

Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

Procedia PDF Downloads 220

Authors: Jinming Ma, Tianbing Xia, Janusz Getta

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This paper presents the application of fuzzy set theory to implement of mobile advertisement anti-fraud systems. Mobile anti-fraud is a method aiming to identify mobile advertisement fraudsters. One of the main problems of mobile anti-fraud is the lack of evidence to prove a user to be a fraudster. In this paper, we implement an application by using fuzzy set theory to demonstrate how to detect cheaters. The advantage of our method is that the hardship in detecting fraudsters in small data samples has been avoided. We achieved this by giving each user a suspicious degree showing how likely the user is cheating and decide whether a group of users (like all users of a certain APP) together to be fraudsters according to the average suspicious degree. This makes the process more accurate as the data of a single user is too small to be predictable.

Keywords: mobile internet, advertisement, anti-fraud, fuzzy set theory

Procedia PDF Downloads 162

Authors: Helmi Vent

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This four-year artistic research project has set the goal of exploring the adaptable transitions within the realms between the two genres. This paper will single out one research question from the entire project for its focus, namely on how and under what circumstances such transitions between a reinterpretation and a new creation can take place during the performative process. The film documentation that accompany the project were produced at the Mozarteum University in Salzburg, Austria, as well as on diverse everyday stages at various locations. The model institution that hosted the project is the LIA – Lab Inter Arts, under the direction of Helmi Vent. LIA combines artistic research with performative applications. The project participants are students from various artistic fields of study. The film documentation forms a central platform for the entire project. They function as audiovisual records of performative performative origins and development processes, while serving as the basis for analysis and evaluation, including the self-evaluation of the recorded material and they also serve as illustrative and discussion material in relation to the topic of this paper. Regarding the “interspaces” and variable 'transitions': The performing arts in the western cultures generally orient themselves toward existing original compositions – most often in the interconnected fields of music, dance and theater – with the goal of reinterpreting and rehearsing a pre-existing score, choreographed work, libretto or script and presenting that respective piece to an audience. The essential tool in this reinterpretation process is generally the artistic ‘language’ performers learn over the course of their main studies. Thus, speaking is combined with singing, playing an instrument is combined with dancing, or with pictorial or sculpturally formed works, in addition to many other variations. If the Performing Arts would rid themselves of their designations from time to time and initially follow the emerging, diffusely gliding transitions into the unknown, the artistic language the performer has learned then becomes a creative resource. The illustrative film excerpts depicting the realms between Performing Arts and Performance Art present insights into the ways the project participants embrace unknown and explorative processes, thus allowing the genesis of new performative designs or concepts to be invented between the participants’ acquired cultural and artistic skills and their own creations – according to their own ideas and issues, sometimes with their direct involvement, fragmentary, provisional, left as a rough draft or fully composed. All in all, it is an evolutionary process and its key parameters cannot be distilled down to their essence. Rather, they stem from a subtle inner perception, from deep-seated emotions, imaginations, and non-discursive decisions, which ultimately result in an artistic statement rising to the visible and audible surface. Within these realms between performing arts and performance art and their extremely flexible transitions, exceptional opportunities can be found to grasp and realise art itself as a research process.

Keywords: art as research method, Lab Inter Arts ( LIA ), performing arts, performance art

Procedia PDF Downloads 249

Authors: Rana Rimawi, Ayman Baklizi

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Skewed distributions are important models that are frequently used in applications. Generalized distributions form a class of skewed distributions and gain widespread use in applications because of their flexibility in data analysis. More specifically, the Generalized Logistic Distribution with its different types has received considerable attention recently. In this study, based on progressively type-II censored data, we will consider point estimation in type II Generalized Logistic Distribution (Type II GLD). We will develop several estimators for its unknown parameters, including maximum likelihood estimators (MLE), Bayes estimators and linear estimators (BLUE). The estimators will be compared using simulation based on the criteria of bias and Mean square error (MSE). An illustrative example of a real data set will be given.

Keywords: point estimation, type II generalized logistic distribution, progressive censoring, maximum likelihood estimation

Procedia PDF Downloads 188

Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

Procedia PDF Downloads 185

Authors: Soumaya Sallem, Marc Olivas

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This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

Procedia PDF Downloads 180

Authors: Kai Chen, Shuguang Cui, Feng Yin

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Gaussian process (GP) with spectral mixture (SM) kernel demonstrates flexible non-parametric Bayesian learning ability in modeling unknown function. In this work a novel time-varying and non-stationary convolution spectral mixture (TN-CSM) kernel with a significant enhancing of interpretability by using process convolution is introduced. A way decomposing the SM component into an auto-convolution of base SM component and parameterizing it to be input dependent is outlined. Smoothly, performing a convolution between two base SM component yields a novel structure of non-stationary SM component with much better generalized expression and interpretation. The TN-CSM perfectly allows compatibility with the stationary SM kernel in terms of kernel form and spectral base ignored and confused by previous non-stationary kernels. On synthetic and real-world datatsets, experiments show the time-varying characteristics of hyper-parameters in TN-CSM and compare the learning performance of TN-CSM with popular and representative non-stationary GP.

Keywords: Gaussian process, spectral mixture, non-stationary, convolution

Procedia PDF Downloads 180

Authors: Chaima Babi, Said Gadri

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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

Procedia PDF Downloads 69

Authors: Teguh Sugiarto

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Background: The research aims to explore if there is fraud in a financial statement, use the Act stated that Benford's distribution all digits must compare the number will follow the trend of lower number. Research methods: This research uses all the analysis number being in Benford's law. After receiving the results of the analysis of all the digits, the author makes a distinction between implementation using the scale above and below 5%, the rate of occurrence of difference. With the number which have differences in the range of 5%, then can do the follow-up and the detection of the onset of fraud against the financial statements. The findings: From the research that has been done can be drawn the conclusion that the average of all numbers appear in the financial statements, and compare the rates of occurrence of numbers according to the characteristics of Benford's law. About the existence of errors and fraud in the financial statements of PT medco Energy Tbk did not occur. Conclusions: The study concludes that Benford's law can serve as indicator tool in detecting the possibility of in financial statements to case studies of PT Medco Energy Tbk for the fiscal year 2000-2010.

Keywords: Benford law, first digits, all digits number Benford law, financial statement

Procedia PDF Downloads 231

Authors: Jen-Fa Huang, Yu-Wei Chiu, Jhe-Ren Cheng

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Visible light communication (VLC) technique has become useful method via LED light blinking. Several issues on indoor mobile robot positioning with LED blinking are examined in the paper. In the transmitter, we control the transceivers blinking message. Orthogonal Walsh codes are adopted for such purpose on auto-correlation function (ACF) to detect signal sequences. In the robot receiver, we set the frame of time by 1 ns passing signal from the transceiver to the mobile robot. After going through many periods of time detecting the peak value of ACF in the mobile robot. Moreover, the transceiver transmits signal again immediately. By capturing three times of peak value, we can know the time difference of arrival (TDOA) between two peak value intervals and finally analyze the accuracy of the robot position.

Keywords: Visible Light Communication, Auto-Correlation Function (ACF), peak value of ACF, Time difference of Arrival (TDOA)

Procedia PDF Downloads 304

Authors: Charles Koduru, Parth Patel, M. Hassan Tanveer

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In this paper, the communication between a team of robots is used to sanitize an environment with germs is proposed. We introduce capabilities from a team of robots (most likely heterogeneous), a wheeled robot named ROSbot 2.0 that consists of a mounted LiDAR and Kinect sensor, and a modified prototype design of a unicycle-drive Roomba robot called the UV robot. The UV robot consists of ultrasonic sensors to avoid obstacles and is equipped with an ultraviolet light system to disinfect and kill germs, such as bacteria and viruses. In addition, the UV robot is equipped with disinfectant spray to target hidden objects that ultraviolet light is unable to reach. Using the sensors from the ROSbot 2.0, the robot will create a 3-D model of the environment which will be used to factor how the ultraviolet robot will disinfect the environment. Together this proposed system is known as the RME assistive robot device or RME system, which communicates between a navigation robot and a germ disinfecting robot operated by a user. The RME system includes a human-machine interface that allows the user to control certain features of each robot in the RME assistive robot device. This method allows the cleaning process to be done at a more rapid and efficient pace as the UV robot disinfects areas just by moving around in the environment while using the ultraviolet light system to kills germs. The RME system can be used in many applications including, public offices, stores, airports, hospitals, and schools. The RME system will be beneficial even after the COVID-19 pandemic. The Kennesaw State University will continue the research in the field of robotics, engineering, and technology and play its role to serve humanity.

Keywords: multi robot system, assistive robots, COVID-19 pandemic, ultraviolent technology

Procedia PDF Downloads 167

Authors: Duc Dong Do, Ngoc Ha Tran, Thanh Hai Dang, Cao Cuong Dang, Xuan Huan Hoang

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Global aligning two protein-protein interaction networks is an essentially important task in bioinformatics/computational biology field of study. It is a challenging and widely studied research topic in recent years. Accurately aligned networks allow us to identify functional modules of proteins and/ororthologous proteins from which unknown functions of a protein can be inferred. We here introduce a novel efficient heuristic global network alignment algorithm called FASTAn, including two phases: the first to construct an initial alignment and the second to improve such alignment by exerting a local optimization repeated procedure. The experimental results demonstrated that FASTAn outperformed the state-of-the-art global network alignment algorithm namely SPINAL in terms of both commonly used objective scores and the run-time.

Keywords: FASTAn, Heuristic algorithm, biological network alignment, protein-protein interaction networks

Procedia PDF Downloads 590

Authors: Malay Bhattacharyya, Saparya Suresh

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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

Procedia PDF Downloads 113

Authors: Moushira Zaki, Wafaa Ezzat, Yasser Elhosary, Omnia Saleh

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Nonalcoholic fatty liver disease (NAFLD) has increased in conjunction with obesity. The accuracy of risk factors for detecting NAFLD in obese adolescents has not undergone a formal evaluation. The aim of this study was to evaluate predictors of NAFLD among Egyptian female obese adolescents. The study included 162 obese female adolescents. All were subjected to anthropometry, biochemical analysis and abdominal ultrasongraphic assessment. Metabolic syndrome (MS) was diagnosed according to the IDF criteria. Significant association between presence of MS and NAFLD was observed. Obese adolescents with NAFLD had significantly higher levels of ALT, triglycerides, fasting glucose, insulin, blood pressure and HOMA-IR, whereas decreased HDL-C levels as compared with obese cases without NAFLD. Receiver–operating characteristic (ROC) curve analysis shows that ALT is a sensitive predictor for NAFLD, confirming that ALT can be used as a marker of NAFLD.

Keywords: obesity, NAFLD, predictors, adolescents, Egyptians, risk factors, prevalence

Procedia PDF Downloads 372

Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

Procedia PDF Downloads 325

Authors: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

Procedia PDF Downloads 271

Authors: Samaneh Farokhirad, Fatemeh Ahmadpoor

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Biological membranes are constantly in contact with various filamentous soft nanostructures that either reside on their surface or are being transported between the cell and its environment. In particular, viral infections are determined by the interaction of viruses (such as filovirus) with cell membranes, membrane protein organization (such as cytoskeletal proteins and actin filament bundles) has been proposed to influence the mechanical properties of lipid membranes, and the adhesion of filamentous nanoparticles influence their delivery yield into target cells or tissues. The goal of this research is to integrate the rapidly increasing but still fragmented experimental observations on the adhesion and self-assembly of nanofilaments (including filoviruses, actin filaments, as well as natural and synthetic nanofilaments) on cell membranes into a general, rigorous, and unified knowledge framework. The global outbreak of the coronavirus disease in 2020, which has persisted for over three years, highlights the crucial role that nanofilamentbased delivery systems play in human health. This work will unravel the role of a unique property of all cell membranes, namely flexoelectricity, and the significance of nanofilaments’ flexibility in the adhesion and self-assembly of nanofilaments on cell membranes. This will be achieved utilizing a set of continuum mechanics, statistical mechanics, and molecular dynamics and Monte Carlo simulations. The findings will help address the societal needs to understand biophysical principles that govern the attachment of filoviruses and flexible nanofilaments onto the living cells and provide guidance on the development of nanofilament-based vaccines for a range of diseases, including infectious diseases and cancer.

Keywords: virus nanofilaments, cell mechanics, computational biophysics, statistical mechanics

Procedia PDF Downloads 80

Authors: Howaida I. Abd-Alla, Nagwa M. M. Shalaby

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The fruit rind of Fortunella margarita (Nagami Kumkuat) was investigated for its chemical constituents. Thirteen metabolites were obtained and classified into, a sterol; β-sitosterol (1) and twelve phenolic compounds, three coumarins; xanthotoxin (2), isopimpinellin (3), umbelliferone (4), nine flavonoids of O-glycosides of flavone; apigenin-7-O-β-D-glucopyranoside (5), apigenin-7-O-rhamnoglucoside (rhoifolin) (6), C-glycosides; vitexin (7), vicenin II (8), and the methoxylated; 6-methoxyapigenin-7-methyl ether (9) and tangeretin (10) as well as flavanones class; naringenin (11), liquiritigenin (12), hesperdin (hesperetin-7-rhamnoglucoside) (13). All compounds were identified for the first time in F. margarita except compound (8). The major glycosides 5, 6, and 13 and total crude extract showed potential antiviral activity against live Newcastle disease virus vaccine strains (Komarov and LaSota) and live infectious bursitis viruses vaccine strain D78 replication in VERO cell cultures and on specific pathogen-free embryonated chicken eggs. Antiviral inhibitory concentration fifty (IC50), cytotoxic concentration fifty (CC50), and therapeutic index (TI) were calculated. In addition, the extract and compounds 7 and 13 showed marked antimicrobial activity against different strains of fungi, Gram-positive and negative bacteria, including some foodborne pathogens of animal origin, caused human disease. These results suggested that the extract of F. margarita may be considered potentially useful as a source of natural antiviral and antimicrobial agents. It can be used as an ingredient for functional food and/or pharmaceuticals.

Keywords: antimicrobial, antiviral, Fortunella margarita, Nagami Kumkuat, phenolic secondary metabolites

Procedia PDF Downloads 190

Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

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The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

Procedia PDF Downloads 53

Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

Procedia PDF Downloads 453

Authors: Michaela Porubanova

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In this exploratory study to examine the effects of emotional significance on change detection using the flicker paradigm, three different categories of scenes were randomly presented (neutral, positive and negative) in three different blocks. We hypothesized that because of the different effects on attention, performance in change detection tasks differs for scenes with different effective values. We found the greatest accuracy of change detection was for changes occurring in positive and negative scenes (compared with neutral scenes). Secondly and most importantly, changes in negative scenes (and also positive scenes, though not with statistical significance) were detected faster than changes in neutral scenes. Interestingly, women were less accurate than men in detecting changes in emotionally significant scenes (both negative and positive), i.e., women detected fewer changes in emotional scenes in the time limit of 40s. But on the other hand, women were quicker to detect changes in positive and negative images than men. The study makes important contributions to the area of the role of emotions on information processing. The role of emotion in attention will be discussed.

Keywords: attention, emotion, flicker task, IAPS

Procedia PDF Downloads 341

Authors: Mafalda Moreira, Diana Alba, Inês Paiva Ferreira, Rita Calejo, Ana Rita Soares, Leonilde Machado

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Intellectual disability (ID) is characterized by deficits in intellectualfunctioningassociatedwithalterations in the adaptive behaviour, whose onset is inthedevelopmentalperiod. Itaffects 3% of the population, ofwhich 10% have a geneticaetiology. One of those causes isAlwadeiSyndrome, with 3 cases describedworldwide. It results from a homozygous nonsense mutation in theRUSC2 gene andisassociatedwithintellectualdisabilityanddysmorphic facialfeatures. Theauthorsreportthe case of a 5-year-old-boy, born to a healthymotherafter a full-termuneventfulpregnancy, thatwasreferred to Neurodevelopmentalconsultationdue toglobal developmentaldelay. Familyhistoryrevealedlearningdifficulties in the paternal brotherhood. Milddismorphicfeatureswereevidentsuch as darkinfraorbitalregion, low-set ears, beakednose, retrognathism, high-archedpalateandjointhyperlaxity. WechslerIntelligenceScale for Children III fullscaleIQ quoted 61. Karyotypeandchromosomalmicroarrayanalysiswerenormal, as well as the fragile X molecular study. DNA sequencingwasthenperformedandallowedtheidentificationof amutation in the RUSC2 gene. Theetiologicaldiagnosisof ID remains unknown in up to 80% of cases, creatinguncertainty in children’sfamilies. Theadvances in DNA sequencingtechnologieshaveincreasedourknowledgeofthegeneticdiseasesinvolved, as theAlwadeisyndromewasonlydescribedsince 2016. Thegeneticdiagnosisof ID allowsfamilygeneticcounselingandenablesthedevelopmentof target therapeutic approaches.

Keywords: intellectual disability, genetic aetiology, alwadei syndrome, RUSC2

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Authors: Farhad Sedaghati, Shahram Pezeshk

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Regional variations in strong ground motions for the Iranian Plateau have been investigated by using a simple statistical method called Analysis of Variance (ANOVA). In this respect, a large database consisting of 1157 records occurring within the Iranian Plateau with moment magnitudes of greater than or equal to 5 and Joyner-Boore distances up to 200 km has been considered. Geometric averages of horizontal peak ground accelerations (PGA) as well as 5% damped linear elastic response spectral accelerations (SA) at periods of 0.2, 0.5, 1.0, and 2.0 sec are used as strong motion parameters. The initial database is divided into two different datasets, for Northern Iran (NI) and Central and Southern Iran (CSI). The comparison between strong ground motions of these two regions reveals that there is no evidence for significant differences; therefore, data from these two regions may be combined to estimate the unknown coefficients of attenuation relationships.

Keywords: ANOVA, attenuation relationships, Iranian Plateau, PGA, regional variation, SA, strong ground motion

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Authors: M. Rezki, A. Belaidi

Abstract:

This paper deals with a method of learning to solve a real problem in biomedical engineering from a technical study of muscle fatigue. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles (viewpoint: anatomical and physiological). EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain and muscle fatigue in general. In order to study the EMG signal for detecting fatigue in a muscle, we have taken a real problem which touches the tramway conductor the handle bar. For the study, we have used a typical autonomous platform in order to get signals at real time. In our case study, we were confronted with complex problem to do our experiments in a tram. This type of problem is recurring among students. To teach our students the method to solve this kind of problem, we built a similar system. Through this study, we realized a lot of objectives such as making the equipment for simulation, the study of detection of muscle fatigue and especially how to manage a study of biomedical looking.

Keywords: EMG, health platform, conductor’s tram, muscle fatigue

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