Search results for: pathogen detection

Authors: S. M. Yasir Arafat

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Driving models are needed by many researchers to improve traffic safety and to advance autonomous vehicle design. To be most useful, a driving model must state specifically what information is needed and how it is processed. So we developed an “Obstacle Avoidance and Detection Autonomous Car” based on sensor application. The ever increasing technological demands of today call for very complex systems, which in turn require highly sophisticated controllers to ensure that high performance can be achieved and maintained under adverse conditions. Based on a developed model of brakes operation, the controller of braking system operation has been designed. It has a task to enable solution to the problem of the better controlling of braking system operation in a more accurate way then it was the case now a day.

Keywords: automobile, obstacle, safety, sensing

Procedia PDF Downloads 364

Authors: An-Shik Yang, Chin-Ting Kuo, Yung-Chun Yang, Wen-Hsin Hsieh, Chiang-Ho Cheng

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Optical biosensors have become a powerful detection and analysis tool for wide-ranging applications in biomedical research, pharmaceuticals and environmental monitoring. This study carried out the computational fluid dynamics (CFD)-based simulations to explore the dispersion phenomenon in the microchannel of a optical biosensor. The predicted time sequences of concentration contours were utilized to better understand the dispersion development occurred in different geometric shapes of microchannels. The simulation results showed the surface concentrations at the sensing probe (with the best performance of a grating coupler) in respect of time to appraise the dispersion effect and therefore identify the design configurations resulting in minimum dispersion.

Keywords: CFD simulations, dispersion, microfluidic, optical waveguide sensors

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Authors: Nabil Shawkat, Jamil Saquer

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Social media has accelerated our ability to engage with others and eliminated many communication barriers. On the other hand, the widespread use of social media resulted in an increase in online hate speech. This has drastic impacts on vulnerable individuals and societies. Therefore, it is critical to detect hate speech to prevent innocent users and vulnerable communities from becoming victims of hate speech. We investigate the performance of different deep learning and machine learning algorithms on three different datasets. Our results show that the BERT model gives the best performance among all the models by achieving an F1-score of 90.6% on one of the datasets and F1-scores of 89.7% and 88.2% on the other two datasets.

Keywords: hate speech, machine learning, deep learning, abusive words, social media, text classification

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Authors: Debbarma Asis, Guha Chandan

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Tumor Protein-53 (P53) is one of the tumor suppressor proteins. P53 regulates the cell cycle that conserves stability by preventing genome mutation. It is named so as it runs as 53-kilodalton (kDa) protein on Polyacrylamide gel electrophoresis although the actual mass is 43.7 kDa. Experimental evidence has indicated that P53 cancer mutants loses tumor suppression activity and subsequently gain oncogenic activities to promote tumourigenesis. Tumor-specific DNA has recently been detected in the plasma of breast cancer patients. Detection of tumor-specific genetic materials in cancer patients may provide a unique and valuable tumor marker for diagnosis and prognosis. Commercially available MDA-468 breast cancer cell line was used for the proposed study.

Keywords: tumor protein (P53), cancer mutants, MDA-468, tumor suppressor gene

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Authors: Claire Williams

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Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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Authors: Israel Ibarra Solis, Juan Carlos Rodriguez Sierra, Ma. del Carmen Salazar Hernandez, Isis Rodriguez Sanchez, David Perez Guerrero

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At the present paper we try to explain the analysis techniques use for the lubricating oil in a maintenance period of a city bus (Mercedes Benz Boxer 40), which is call ‘R-24 route’, line Coecillo Centro SA de CV in Leon Guanajuato, to estimate the optimal time for the oil change. Using devices such as the rotational viscometer and the atomic absorption spectrometer, they can detect the incipient form when the oil loses its lubricating properties and, therefore, cannot protect the mechanical components of diesel engines such these trucks. Timely detection of lost property in the oil, it allows us taking preventive plan maintenance for the fleet.

Keywords: atomic absorption spectrometry, maintenance, predictive velocity rate, lubricating oils

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Authors: Ece Cigdem Mutlu, Burak Alakent

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Maintaining the quality of manufactured products at a desired level depends on the stability of process dispersion and location parameters and detection of perturbations in these parameters as promptly as possible. Shewhart control chart is the most widely used technique in statistical process monitoring to monitor the quality of products and control process mean and variability. In the application of Xbar control charts, sample standard deviation and sample mean are known to be the most efficient conventional estimators in determining process dispersion and location parameters, respectively, based on the assumption of independent and normally distributed datasets. On the other hand, there is no guarantee that the real-world data would be normally distributed. In the cases of estimated process parameters from Phase I data clouded with outliers, efficiency of traditional estimators is significantly reduced, and performance of Xbar charts are undesirably low, e.g. occasional outliers in the rational subgroups in Phase I data set may considerably affect the sample mean and standard deviation, resulting a serious delay in detection of inferior products in Phase II. For more efficient application of control charts, it is required to use robust estimators against contaminations, which may exist in Phase I. In the current study, we present a simple approach to construct robust Xbar control charts using average distance to the median, Qn-estimator of scale, M-estimator of scale with logistic psi-function in the estimation of process dispersion parameter, and Harrell-Davis qth quantile estimator, Hodge-Lehmann estimator and M-estimator of location with Huber psi-function and logistic psi-function in the estimation of process location parameter. Phase I efficiency of proposed estimators and Phase II performance of Xbar charts constructed from these estimators are compared with the conventional mean and standard deviation statistics both under normality and against diffuse-localized and symmetric-asymmetric contaminations using 50,000 Monte Carlo simulations on MATLAB. Consequently, it is found that robust estimators yield parameter estimates with higher efficiency against all types of contaminations, and Xbar charts constructed using robust estimators have higher power in detecting disturbances, compared to conventional methods. Additionally, utilizing individuals charts to screen outlier subgroups and employing different combination of dispersion and location estimators on subgroups and individual observations are found to improve the performance of Xbar charts.

Keywords: average run length, M-estimators, quality control, robust estimators

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Authors: Ravi Kumar, Dhrubajit Barman, Nomi Baruah

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Software Cloning has grown an active area in software engineering research community yielding numerous techniques, various tools and other methods for clone detection and removal. The copying, modifying a block of code is identified as cloning as it is the most basic means of software reuse. Agile Software Development is an approach which is currently being used in various software projects, so that it helps to respond the unpredictability of building software through incremental, iterative, work cadences. Software Cloning has been introduced to Agile Environment and many Agile Software Development approaches are using the concept of Software Cloning. This paper discusses the various Agile Software Development approaches. It also discusses the degree to which the Software Cloning concept is being introduced in the Agile Software Development approaches.

Keywords: agile environment, refactoring, reuse, software cloning

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Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

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Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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Authors: Nanditha Rajamani, Anirudhaa R. Rao, Divya Sriram

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One of the greatest difficulties in treating patients with pain is the highly subjective nature of pain sensation. The measurement of pain intensity is primarily dependent on the patient’s report, often with little physical evidence to provide objective corroboration. This is also complicated by the fact that there are only few and expensive existing technologies (Functional Magnetic Resonance Imaging-fMRI). The need is thus clear and urgent for a reliable, non-invasive, non-painful, objective, readily adoptable, and coefficient diagnostic platform that provides additional diagnostic information to supplement its current regime with more information to assist doctors in diagnosing these patients. Thus, our idea of developing a pain detector was conceived to take a step further the detection and diagnosis of chronic and acute pain.

Keywords: pain sensor, microwave radiometery, pain sensation, fMRI

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Authors: Steve H. Y. Lee, Jeremy P. E. Spencer

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The aim of the present study was to explore the feasibility of enriching polyphenols in cow milk via addition of flavanone-rich citrus pulp to existing animal feed. 8 Holstein lactating cows were enrolled onto the 4 week feeding study. 4 cows were fed the standard farm diet (control group), with another 4 (treatment group) which are fed a standard farm diet mixed with citrus pulp diet. Milk was collected twice a day, 3 times a week. The resulting milk yield and its macronutrient composition as well as lactose content were measured. The milk phenolic compounds were analysed using electrochemical detection (ECD).

Keywords: milk, polyphenol, animal feeding, lactating cows

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Authors: J. H. Bang, H. J. Baek, K. I. Kim, B. J. Lee, H. J. Jung, H. J. Jang, S. K. Jung

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Asthma is a chronic inflammatory lung disease characterized by airway hyper responsiveness (AHR), airway obstruction and airway wall remodeling responsible for significant morbidity and mortality worldwide. Genetic and environment factors may result in asthma, but there are no the exact causes of asthma. Chungpye-tang (CPT) has been prescribed as a representative aerosol agent for patients with dyspnea, cough and phlegm in the respiratory clinic at Kyung Hee Korean Medicine Hospital. This Korean herbal medicines have the effect of dispelling external pathogen and dampness pattern. CPT is composed of 4 species of herbal medicines. The 4 species of herbal medicines are Ephedrae herba, Pogostemonis(Agatachis) herba, Caryophylli flos and Zingiberis rhizoma crudus. CPT suppresses neutrophil infiltration and the production of pro-inflammatory cytokines in lipopolysaccharide (LPS)-induced acute lung injury (ALI) mouse model. Moreover, the anti-inflammatory effects of CPT on a mouse model of Chronic Obstructive Pulmonary Disease (COPD) was proved. Activation of the NF-κB has been proven that it plays an important role in inflammation via inducing transcription of pro-inflammatory genes. Over-expression of NF-κB has been believed be related to many inflammatory diseases such as arthritis, gastritis, asthma and COPD. So we firstly hypothesize whether CPT has an anti-inflammatory effect on asthmatic human airway epithelial tissue via inhibiting NF-κB pathway. In this study, CPT was extracted with distilled water for 3 hours at 100°C. After process of filtration and evaporation, it was freeze dried. And asthmatic human lung tissues were provided by MatTek Corp. We investigated the precise mechanism of the anti-inflammatory effect of CPT by western blotting analysis. We observed whether the decoction extracts could reduce NF-κB activation, COX-2 protein expression and NF-κB-mediated pro-inflammatory cytokines such as TNF-α, eotaxin, IL-4, IL-9 and IL-13 in asthmatic human lung tissue. As results of this study, there was a trend toward decreased NF-κB expression in asthmatic human airway epithelial tissue. We found that the inhibition effects of CPT on COX-2 expression was not determined. IL-9 and IL-13 secretion was significantly reduced in the asthmatic human lung tissue treated with CPT. Overall, our results indicate that CPT has an anti-inflammatory effect through blocking the signaling pathway of NF-κB, thereby CPT may be a potential remedial agent for allergic asthma.

Keywords: Chungpye-tang, allergic asthma, asthmatic human airway epithelial tissue, nuclear factor kappa B (NF-κB) pathway, COX-2

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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Authors: Rajeev Jain, Nimisha Jadon, Kshiti Singh

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Titanium oxide nanoparticles and 1-butyl-2,3-dimethylimidazolium bis (trifluoromethane- sulfonyl) imide modified glassy carbon electrode (TiO2/IL/GCE) has been fabricated for electrochemical sensing of flunarizine dihydrochloride (FRH). The electrochemical properties and morphology of the prepared nanocomposite were studied by electrochemical impedance spectroscopy (EIS) and transmission electron microscopy (TEM). The response of the electrochemical sensor was found to be proportional to the concentrations of FRH in the range from 0.5 µg mL-1 to 16 µg mL-1. The detection limit obtained was 0.03 µg mL-1. The proposed method was also applied to the determination of FRH in pharmaceutical formulation and human serum with good recoveries.

Keywords: flunarizine dihydrochloride, ionic liquid, nanoparticles, voltammetry, human serum

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Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

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Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

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Authors: Mohammadamin Abbasnejad

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The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Chee Sun Won

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This paper presents the size reduction of images for machine-to-machine communications. Here, the salient image regions to be preserved include the image patches of the key-points such as corners and blobs. Based on a saliency image map from the key-points and their image patches, an axis-aligned grid-size optimization is proposed for the reduction of image size. To increase the size-reduction efficiency the aspect ratio constraint is relaxed in the constraint optimization framework. The proposed method yields higher matching accuracy after the size reduction than the conventional content-aware image size-reduction methods.

Keywords: image compression, image matching, key-point detection and description, machine-to-machine communication

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Authors: Nadine khadraoui, Rym Essid, Olfa Tabbene, Imen Chniba, Safa Boujemaa, Selim Jallouli, Nadia Fares, Behija Mlik, Boutheina Ben Abdelmoumen Mardassi

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Background and aim: Mycoplasma hominis is an opportunistic pathogen that can cause various gynecological infections such cervicitis, infertility, and, less frequently, extra-genital infections. Previous studies on the antimicrobial susceptibility of Mycoplasma hominis Tunisian strains have highlighted a significant resistance, even multi-resistance, to the most used antibiotic in the therapy of consequential infections. To address this concern, the present study aimed for the alternative of phytotherapy. Peganum harmala seed extract was tested as an antibacterial agent against multidrug-resistant M.hominis clinical strains. Material and Methods: Peganum harmala plant was collected from Ain Sebaa, Tabarka, North West region of Tunisia in April 2018, air-dried, grounded and extracted by different solvents.The crude methanolic extract was further partitioned with n-HEX, DCM, EtOAC and n-BuOl. Antibacterial activity was evaluated against M. hominis ATCC 23114 and 20 M. hominis clinical strains.The antimycoplasmal activity was tested by the microdilution method, and MIC values were determined. Phytochemical analysis and hemolytic activity on human erythrocytes were also performed. The active fraction was then subjected to purification, and the chemical identification of the active compound was investigated. Results: Among the tested fractions, the n-BuOH extract was the most active fraction since it exhibited an inhibitory effect against M. hominis ATCC 23114 and 80% of the tested clinical strains with MIC between 125 and 1000 µg/ml. The phytochemical analysis of the n-BuOH revealed its metabolic abundance in polyphenols, flavonoids and condensed tannin with levels of 257.37 mg AGE/g, 172.27 mg EC/g and 58.27 mg EC/g, respectively. In addition, P. harmala n-BuOH extract exhibited potent bactericidal activity against all M. hominis isolates with CMB values ranging between 125 and 4000 µg/ml. Further, the active fraction exhibited weak cytotoxicity effect at active concentrations when tested on human erythrocytes. The active compound was identified by gas chromatography–mass spectrometry as an indole alkaloid harmaline. Conclusion: In summary, Peganum harmala extract demonstrated an interesting anti-mycoplasmal activity against M. hominis Tunisian strains. Therefore, it could be considered as a potential candidate for the treatment of consequential infections. However, further studies are necessary to evaluate its mechanism of action in mycoplasmas.

Keywords: mycoplasma hominis, peganum harmala, antibioresistance, phytotherapy, phytochemical analysis

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Authors: Serpil Kilic, Ihsan Burak Cam, Murat Kilic, Timur Tongur

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Interest in the lead (Pb) has considerably increased due to knowledge about the potential toxic effects of this element, recently. Exposure to heavy metals above the acceptable limit affects human health. Indeed, Pb is accumulated through food chains up to toxic concentrations; therefore, it can pose an adverse potential threat to human health. A sensitive and reliable method for determination of Pb element in red pepper were improved in the present study. Samples (33 red pepper products having different brands) were purchased from different markets in Turkey. The selected method validation criteria (linearity, Limit of Detection, Limit of Quantification, recovery, and trueness) demonstrated. Recovery values close to 100% showed adequate precision and accuracy for analysis. According to the results of red pepper analysis, all of the tested lead element in the samples was determined at various concentrations. A Perkin- Elmer ELAN DRC-e model ICP-MS system was used for detection of Pb. Organic red pepper was used to obtain a matrix for all method validation studies. The certified reference material, Fapas chili powder, was digested and analyzed, together with the different sample batches. Three replicates from each sample were digested and analyzed. The results of the exposure levels of the elements were discussed considering the scientific opinions of the European Food Safety Authority (EFSA), which is the European Union’s (EU) risk assessment source associated with food safety. The Target Hazard Quotient (THQ) was described by the United States Environmental Protection Agency (USEPA) for the calculation of potential health risks associated with long-term exposure to chemical pollutants. THQ value contains intake of elements, exposure frequency and duration, body weight and the oral reference dose (RfD). If the THQ value is lower than one, it means that the exposed population is assumed to be safe and 1 < THQ < 5 means that the exposed population is in a level of concern interval. In this study, the THQ of Pb was obtained as < 1. The results of THQ calculations showed that the values were below one for all the tested, meaning the samples did not pose a health risk to the local population. This work was supported by The Scientific Research Projects Coordination Unit of Akdeniz University. Project Number: FBA-2017-2494.

Keywords: lead analyses, red pepper, risk assessment, daily exposure

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Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

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This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

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Authors: Golnaz Shahtahmassebi, Jose Maria Sarabia

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In this talk, we introduce a new class of conjugate prior distributions obtained from conditional specification methodology. We illustrate the application of such distribution in Bayesian change point detection in Poisson processes. We obtain the posterior distribution of model parameters using a general bivariate distribution with gamma conditionals. Simulation from the posterior is readily implemented using a Gibbs sampling algorithm. The Gibbs sampling is implemented even when using conditional densities that are incompatible or only compatible with an improper joint density. The application of such methods will be demonstrated using examples of simulated and real data.

Keywords: change point, bayesian inference, Gibbs sampler, conditional specification, gamma conditional distributions

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Authors: Kinjal Parmar, Matteo Lelli

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The usage of IoT technology as a rockfall alert system is relatively new. This paper explains the potential of such an alert system called HelloMac from Maccaferri which provides transportation infrastructure asset owners the way to effectively utilize their resources in the detection of boulder impacts on rockfall barriers. This would ensure a faster assessment of the impacted barrier and subsequently facilitates the implementation of remedial works in an effective and timely manner. In addition, the HelloMac can also be integrated with another warning system to alert vehicle users of the unseen dangers ahead. HelloMac is developed to work also in remote areas, where cell coverage is not available. User gets notified when a rockfall even occurs via mobile app, SMS and email. Using such alarming systems effectively, we can reduce the risk of rockfall hazard.

Keywords: rockfall, barrier, HelloMac, rockfall alert system

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Authors: O. Tovide, N. Jahed, N. Mohammed, C. E. Sunday, H. R. Makelane, R. F. Ajayi, K. M. Molapo, A. Tsegaye, M. Masikini, S. Mailu, A. Baleg, T. Waryo, P. G. Baker, E. I. Iwuoha

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A graphenated–polyaniline (GR-PANI) nanocomposite sensor was constructed and used for the determination of anthracene. The direct electro-oxidation behavior of anthracene on the GR-PANI modified glassy carbon electrode (GCE) was used as the sensing principle. The results indicate thatthe response profile of the oxidation of anthracene on GR-PANI-modified GCE provides for the construction of sensor systems based onamperometric and potentiometric signal transductions. A dynamic linear range of 0.12- 100 µM anthracene and a detection limit of 0.044 µM anthracene were established for the sensor system.

Keywords: electrochemical sensors, environmental pollutants, graphenated-polymers, polyaromatic hydrocarbon

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Authors: M. Beheshti, S. Saegrov, T. M. Muthanna

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Separated sewer systems are designed to transfer the wastewater from houses and industrial sections to wastewater treatment plants. Unwanted water in the sewer systems is a well-known problem, i.e. storm-water inflow is around 50% of the foul sewer, and groundwater infiltration to the sewer system can exceed 50% of total wastewater volume in deteriorated networks. Infiltration and inflow of non-sewer water (I/I) into sewer systems is unfavorable in separated sewer systems and can trigger overloading the system and reducing the efficiency of wastewater treatment plants. Moreover, I/I has negative economic, environmental, and social impacts on urban areas. Therefore, for having sustainable management of urban sewer systems, I/I of unwanted water into the urban sewer systems should be considered carefully and maintenance and rehabilitation plan should be implemented on these water infrastructural assets. This study presents a methodology to identify and quantify the level of I/I into the sewer system. Amount of I/I is evaluated by accurate flow measurement in separated sewer systems for specified isolated catchments in Trondheim city (Norway). Advanced information about the characteristics of I/I is gained by CCTV inspection of sewer pipelines with high I/I contribution. Achieving enhanced knowledge about the detection and localization of non-sewer water in foul sewer system during the wet and dry weather conditions will enable the possibility for finding the problem of sewer system and prioritizing them and taking decisions for rehabilitation and renewal planning in the long-term. Furthermore, preventive measures and optimization of sewer systems functionality and efficiency can be executed by maintenance of sewer system. In this way, the exploitation of sewer system can be improved by maintenance and rehabilitation of existing pipelines in a sustainable way by more practical cost-effective and environmental friendly way. This study is conducted on specified catchments with different properties in Trondheim city. Risvollan catchment is one of these catchments with a measuring station to investigate hydrological parameters through the year, which also has a good database. For assessing the infiltration in a separated sewer system, applying the flow rate measurement method can be utilized in obtaining a general view of the network condition from infiltration point of view. This study discusses commonly used and advanced methods of localizing and quantifying I/I in sewer systems. A combination of these methods give sewer operators the possibility to compare different techniques and obtain reliable and accurate I/I data which is vital for long-term rehabilitation plans.

Keywords: flow rate measurement, infiltration and inflow (I/I), non-sewer water, separated sewer systems, sustainable management

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Authors: Abdelkader Hadjoudja, Hajar Bouazza

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The PLD/CPLD devices are widely used for logic synthesis since several decades. Based on sum of product terms (PTs) architecture, the PLD/CPLD offer a high degree of flexibility to support various application requirements. They are suitable for large combinational logic, finite state machines as well as intensive I/O designs. CPLDs offer very predictable timing characteristics and are therefore ideal for critical control applications. This paper describes how the logic synthesis techniques, such as 1) XOR detection, 2) logic doubling, 3) complement of a Boolean function are combined, applied and used to optimize the CPLDs devices architecture that is based on PAL-like macrocells. Our goal is to use these techniques for minimizing the number of macrocells required to implement a circuit and minimize the delay of mapped circuit.

Keywords: CPLD, doubling, optimization, XOR

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Authors: Nelson R. Osungbemiro, O. A. Bello-Olusoji, M. Oladipupo

Abstract:

This study was carried out to determine the effects of probiotics Pseudomonas fluorescens on the growth performance, histology examination and immune modulation of African Catfish, (Clarias gariepinus) challenged with Clostridium botulinum. P. fluorescens, and C. botulinum isolates were removed from the gut, gill and skin organs of procured adult samples of Clarias gariepinus from commercial fish farms in Akure, Ondo State, Nigeria. The physical and biochemical tests were performed on the bacterial isolates using standard microbiological techniques for their identification. Antibacterial activity tests on P. fluorescens showed inhibition zone with mean value of 3.7 mm which indicates high level of antagonism. The experimental diets were prepared at different probiotics bacterial concentration comprises of five treatments of different bacterial suspension, including the control (T1), T2 (10³), T3 (10⁵), T4 (10⁷) and T5 (10⁹). Three replicates for each treatment type were prepared. Growth performance and nutrients utilization indices were calculated. The proximate analysis of fish carcass and experimental diet was carried out using standard methods. After feeding for 70 days, haematological values and histological test were done following standard methods; also a subgroup from each experimental treatment was challenged by inoculating Intraperitonieally (I/P) with different concentration of pathogenic C. botulinum. Statistically, there were significant differences (P < 0.05) in the growth performance and nutrient utilization of C. gariepinus. Best weight gain and feed conversion ratio were recorded in fish fed T4 (10⁷) and poorest value obtained in the control. Haematological analyses of C. gariepinus fed the experimental diets indicated that all the fish fed diets with P. fluorescens had marked significantly (p < 0.05) higher White Blood Cell than the control diet. The results of the challenge test showed that fish fed the control diet had the highest mortality rate. Histological examination of the gill, intestine, and liver of fish in this study showed several histopathological alterations in fish fed the control diets compared with those fed the P. fluorescens diets. The study indicated that the optimum level of P. fluorescens required for C. gariepinus growth and white blood cells formation is 10⁷ CFU g⁻¹, while carcass protein deposition required 10⁵ CFU g⁻¹ of P. fluorescens concentration. The study also confirmed P. fluorescens as efficient probiotics that is capable of improving the immune response of C. gariepinus against the attack of a virulent fish pathogen, C. botulinum.

Keywords: Clarias gariepinus, Clostridium botulinum, probiotics, Pseudomonas fluorescens

Procedia PDF Downloads 163

Authors: Mustafa Alshawaqfeh, Bilal Wajidy, Echin Serpedin, Jan Suchodolski

Abstract:

Inflammatory Bowel disease (IBD) is a disease of the colon with characteristic inflammation. Clinically IBD is detected using laboratory tests (blood and stool), radiology tests (imaging using CT, MRI), capsule endoscopy and endoscopy. There are two variants of IBD referred to as Ulcerative Colitis (UC) and Crohn’s disease. This study employs a hybrid feature selection method that combines a correlation-based variable ranking approach with exhaustive search wrapper methods in order to find potential biomarkers for UC. The proposed biomarkers presented accurate discriminatory power thereby identifying themselves to be possible ingredients to UC therapeutics.

Keywords: ulcerative colitis, biomarker detection, feature selection, inflammatory bowel disease (IBD)

Procedia PDF Downloads 403

Authors: Morteza Raki, Abolghasem Zabihollah, Omid Askari

Abstract:

Cantilever beam is a simplified sample of a lot of mechanical components used in a wide range of applications, including many industries such as gas turbine blade. Due to the nature of the operating conditions, beams are subject to variety of damages especially crack propagates. Crack propagation may lead to catastrophic failure during operation. Therefore, online detection of crack presence and its propagation is very important and may reduce possible significant cost of the whole system failure. This paper aims to investigate the effect of cracks presence and crack propagation on one end fixed beam`s vibration. A finite element model will be developed for the blade in which the modal response of the structure with and without crack will be studied. 

Keywords: blade, crack propagation, health monitoring, modal analysis

Procedia PDF Downloads 344

Authors: Rui Wang, Luodi Yu, Dan Huang, Hsuan-Chih Chen, Yang Zhang, Suiping Wang

Abstract:

Enhanced discrimination of pure tones but diminished discrimination of speech pitch (i.e., lexical tone) were found in children with autism who speak a tonal language (Mandarin), suggesting a speech-specific impairment of pitch perception in these children. However, in tonal languages, both lexical tone and vowel are phonemic cues and integrally dependent on each other. Therefore, it is unclear whether the presence of phonemic vowel dimension contributes to the observed lexical tone deficits in Mandarin-speaking children with autism. The current study employed a multi-feature oddball paradigm to examine how vowel and tone dimensions contribute to the neural responses for syllable change detection and involuntary attentional orienting in school-age Mandarin-speaking children with autism. In the oddball sequence, syllable /da1/ served as the standard stimulus. There were three deviant stimulus conditions, representing tone-only change (TO, /da4/), vowel-only change (VO, /du1/), and change of tone and vowel simultaneously (TV, /du4/). EEG data were collected from 25 children with autism and 20 age-matched normal controls during passive listening to the stimulation. For each deviant condition, difference waveform measuring mismatch negativity (MMN) was derived from subtracting the ERP waveform to the standard sound from that to the deviant sound for each participant. Additionally, the linear summation of TO and VO difference waveforms was compared to the TV difference waveform, to examine whether neural sensitivity for TV change detection reflects simple summation or nonlinear integration of the two individual dimensions. The MMN results showed that the autism group had smaller amplitude compared with the control group in the TO and VO conditions, suggesting impaired discriminative sensitivity for both dimensions. In the control group, amplitude of the TV difference waveform approximated the linear summation of the TO and VO waveforms only in the early time window but not in the late window, suggesting a time course from dimensional summation to nonlinear integration. In the autism group, however, the nonlinear TV integration was already present in the early window. These findings suggest that speech perception atypicality in children with autism rests not only in the processing of single phonemic dimensions, but also in the dimensional integration process.

Keywords: autism, event-related potentials , mismatch negativity, speech perception

Procedia PDF Downloads 219