Search results for: cefoxitin disc diffusion MRSA detection

Authors: Soroush Momeni

Abstract:

Excellent damping capacity and superelasticity of the bulk NiTi shape memory alloy (SMA) makes it a suitable material of choice for tools in machining process as well as tribological systems. Although thin film of NiTi SMA has a same damping capacity as NiTi bulk alloys, it has a poor mechanical properties and undesirable tribological performance. This study aims at eliminating these application limitations for NiTi SMA thin films. In order to achieve this goal, NiTi thin films were magnetron sputtered as an interlayer between reactively sputtered hard TiCN coatings and hard work tool steel substrates. The microstructure, composition, crystallographic phases, mechanical and tribological properties of the deposited thin films were analyzed by using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), nanoindentation, ball–on-disc, scratch test, and three dimensional (3D) optical microscopy. It was found that under a specific coating architecture, the superelasticity of NiTi inter-layer can be combined with high hardness and wear resistance of TiCN protective layers. The obtained results revealed that the thickness of NiTi interlayers is an important factor controlling mechanical and tribological performance of bi-layer composite coating systems.

Keywords: PVD coatings, sliding wear, hardness, tool steel

Procedia PDF Downloads 285

Authors: Emma K. Sales

Abstract:

Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments; 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit. Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR analysis, genotype, genetic diversity, cultivars

Procedia PDF Downloads 454

Authors: S. Mohamed, D. Gonzalez, C. Sayada, P. Halfon

Abstract:

Drug resistance mutations are routinely detected using standard Sanger sequencing, which does not detect minor variants with a frequency below 20%. The impact of detecting minor variants generated by ultra-deep sequencing (UDS) on HIV drug-resistance (DR) interpretations has not yet been studied. Fifty HIV-1 patients who experienced virological failure were included in this retrospective study. The HIV-1 UDS protocol allowed the detection and quantification of HIV-1 protease and reverse transcriptase variants related to genotypes A, B, C, E, F, and G. DeepChek®-HIV simplified DR interpretation software was used to compare Sanger sequencing and UDS. The total time required for the UDS protocol was found to be approximately three times longer than Sanger sequencing with equivalent reagent costs. UDS detected all of the mutations found by population sequencing and identified additional resistance variants in all patients. An analysis of DR revealed a total of 643 and 224 clinically relevant mutations by UDS and Sanger sequencing, respectively. Three resistance mutations with > 20% prevalence were detected solely by UDS: A98S (23%), E138A (21%) and V179I (25%). A significant difference in the DR interpretations for 19 antiretroviral drugs was observed between the UDS and Sanger sequencing methods. Y181C and T215Y were the most frequent mutations associated with interpretation differences. A combination of UDS and DeepChek® software for the interpretation of DR results would help clinicians provide suitable treatments. A cut-off of 1% allowed a better characterisation of the viral population by identifying additional resistance mutations and improving the DR interpretation.

Keywords: HIV-1, ultra-deep sequencing, Sanger sequencing, drug resistance

Procedia PDF Downloads 335

Authors: Meriem Hamla, Mohamed Benaicha, Sabrine Derbal

Abstract:

In the present work, several materials such as M/glass (M = Pt, Mo) were investigated to test their suitability for studying the early nucleation stages and growth of copper-tin clusters. It was found that most of these materials stand as good substrates to be used in the study of the nucleation and growth of electrodeposited Cu-Sn alloys from aqueous solution containing CuCl2, SnCl2 as electroactive species and Na3C6H5O7 as complexing agent. Among these substrates, Pt shows instantaneous models followed by 3D diffusion-limited growth. On the other hand, the electrodeposited copper-tin thin films onto Mo substrate followed progressive nucleation. The deposition mechanism of the Cu-Sn films has been studied using stationary electrochemical techniques (cyclic voltammetery (CV) and chronoamperometry (CA). The structural, morphological and compositional of characterization have been studied using X-ray diffraction (XRD), scanning electron microscopy (SEM) and EDAX techniques respectively.

Keywords: electrodeposition, CuSn, nucleation, mechanism

Procedia PDF Downloads 398

Authors: S. Khan, A. Khan, Abdul R. Soomrani, Raja F. Zafar, A. Waqas, G. Akbar

Abstract:

This paper proposes a low-complexity image interpolation method. Image interpolation is used to convert a low dimension video/image to high dimension video/image. The objective of a good interpolation method is to upscale an image in such a way that it provides better edge preservation at the cost of very low complexity so that real-time processing of video frames can be made possible. However, low complexity methods tend to provide real-time interpolation at the cost of blurring, jagging and other artifacts due to errors in slope calculation. Non-linear methods, on the other hand, provide better edge preservation, but at the cost of high complexity and hence they can be considered very far from having real-time interpolation. The proposed method is a linear method that uses gradient orientation for slope calculation, unlike conventional linear methods that uses the contrast of nearby pixels. Prewitt edge detection is applied to separate uniform regions and edges. Simple line averaging is applied to unknown uniform regions, whereas unknown edge pixels are interpolated after calculation of slopes using gradient orientations of neighboring known edge pixels. As a post-processing step, bilateral filter is applied to interpolated edge regions in order to enhance the interpolated edges.

Keywords: edge detection, gradient orientation, image upscaling, linear interpolation, slope tracing

Procedia PDF Downloads 260

Authors: Salma Krafessi

Abstract:

The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

Procedia PDF Downloads 69

Authors: Jaskirat Singh, Roshan Lal Virdi, Khushdeep Goyal

Abstract:

The purpose of this paper is to perform a microstructural analysis of Friction Stir Welded joints of aluminum alloys 6063 and 5083, also to check the properties of the weld zone by SEM analysis. FSW experiments were carried on CNC Vertical milling machine. The tools used for welding were the round cylindrical pin shape and square pin shape. It is found that Microstructure shows the uniformly distributed material with minimum heat affected zone and dense welded zone without any defect. Microstructures indicate that the weld material is defect free. The SEM shows the diffusion of material with base metal with proper bonding without any defect.

Keywords: friction stir welding, aluminum alloy, microstructure, SEM analysis

Procedia PDF Downloads 308

Authors: Berredjem Hajira, Benlaifa Meriem, Becheker Imene, Bardi Rafika, Djebar Med Reda

Abstract:

Recent acquired or reactivation T.gondii infection is a serious complication in HIV patients. Classical serological diagnosis relies on the detection of anti-Toxoplasma immunoglobulin ; however, serology may be unreliable in HIV immunodeficient patients who fail to produce significant titers of specific antibodies. PCR assays allow a rapid diagnosis of Toxoplasma infection. In this study, we compared the value of the PCR for diagnosing active toxoplasmosis in cerebrospinal fluid and blood samples from HIV patients. Anti-Toxoplasma antibodies IgG and IgM titers were determined by ELISA. In parallel, nested PCR targeting B1 gene and conventional PCR-ELISA targeting P30 gene were used to detect T. gondii DNA in 25 blood samples and 12 cerebrospinal fluid samples from patients in whom toxoplasmic encephalitis was confirmed by clinical investigations. A total of 15 negative controls were used. Serology did not contribute to confirm toxoplasmic infection, as IgG and IgM titers decreased early. Only 8 out 25 blood samples and 5 out 12 cerebrospinal fluid samples PCRs yielded a positive result. 5 patients with confirmed toxoplasmosis had positive PCR results in either blood or cerebrospinal fluid samples. However, conventional nested B1 PCR gave best results than the P30 gene one for the detection of T.gondii DNA in both samples. All samples from control patients were negative. This study demonstrates the unusefulness of the serological tests and the high sensitivity and specificity of PCR in the diagnosis of toxoplasmic encephalitis in HIV patients.

Keywords: cerebrospinal fluid, HIV, Toxoplasmosis, PCR

Procedia PDF Downloads 379

Authors: A.Chen Chao-Chang, Phong Pham-Quoc

Abstract:

Chemical-mechanical polishing (CMP) process has been widely applied on fabricating integrated circuits (IC) with a soft polishing pad combined with slurry composed of micron or nano-scaled abrasives for generating chemical reaction to remove substrate or film materials from wafer. During CMP process, pad uniformity usually works as a datum surface of wafer planarization and pad asperities can dominate the microscopic pad-slurry-wafer interaction. However, pad topography can be changed by related mechanism factors of CMP and it needs to be re-conditioned or dressed by a diamond dresser of well-distributed diamond grits on a disc surface. It is still very complicated to analyze and understand kinematic of diamond dressing process under the effects of input variables including oscillatory of diamond dresser and rotation speed ratio between the pad and the diamond dresser. This paper has developed a generic geometric model to clarify the kinematic modeling of diamond dressing processes such as dresser/pad motion, pad cutting locus, the relative velocity of the diamond abrasive grits on pad surface, and overlap of cutting for prediction of pad surface topography. Simulation results focus on comparing and analysis kinematics of the diamond dressing on certain CMP tools. Results have shown the significant parameters for diamond dressing process and also discussed. Future study can apply on diamond dresser design and experimental verification of pad dressing process.

Keywords: kinematic modeling, diamond dresser, pad cutting locus, CMP

Procedia PDF Downloads 255

Authors: João Filipe Papel, Tatsuji Munaka

Abstract:

With society's aging and the number of elderly with dementia rising, researchers have been actively studying how to support the elderly in the early stages of dementia with the objective of allowing them to have a better life quality and as much as possible independence. To make this possible, most researchers in this field are using the Internet Of Things to monitor the elderly activities and assist them in performing them. The most common sensor used to monitor the elderly activities is the Camera sensor due to its easy installation and configuration. The other commonly used sensor is the sound sensor. However, we need to consider privacy when using these sensors. This research aims to develop a system capable of predicting the early stages of dementia based on monitoring and controlling the elderly activities of daily living. To make this system possible, some issues need to be addressed. First, the issue related to elderly privacy when trying to detect their Activities of Daily Living. Privacy when performing detection and monitoring Activities of Daily Living it's a serious concern. One of the purposes of this research is to achieve this detection and monitoring without putting the privacy of the elderly at risk. To make this possible, the study focuses on using an approach based on using Magnet Sensors to collect binary data. The second is to use the data collected by monitoring Activities of Daily Living to predict the early stages of Dementia. To make this possible, the research team suggests developing a proprietary ontology combined with both data-driven and knowledge-driven.

Keywords: dementia, activity recognition, magnet sensors, ontology, data driven and knowledge driven, IoT, activities of daily living

Procedia PDF Downloads 104

Authors: Guanyu Jiang, Donghai Xu, Huanteng Liu

Abstract:

After the Fukushima-Daiichi accident, the development of accident tolerant fuel cladding materials to improve reactor safety has become a hot topic in the field of nuclear industry. ZrO₂ has a satisfactory neutron economy and can guarantee the fission chain reaction process, which enables it to be a promising coating for zirconium alloy cladding. Maintaining a good corrosion resistance in primary coolant loop during normal operations of Pressurized Water Reactors is a prerequisite for ZrO₂ as a protective coating on zirconium alloy cladding. Research on the corrosion performance of ZrO₂ coating in nuclear water chemistry is relatively scarce, and existing reports failed to provide an in-depth explanation for the failure causes of ZrO₂ coating. Herein, a detailed corrosion process of ZrO₂ coating in lithiated water at 360 °C and 18.5 MPa was proposed based on experimental research and molecular dynamics simulation. Lithiated water with different LiOH solutions in the present work was deaerated and had a dissolved oxygen concentration of < 10 ppb. The concentration of Li (as LiOH) was determined to be 2.3 ppm, 70 ppm, and 500 ppm, respectively. Corrosion tests were conducted in a static autoclave. Modeling and corresponding calculations were operated on Materials Studio software. The calculation of adsorption energy and dynamics parameters were undertaken by the Energy task and Dynamics task of the Forcite module, respectively. The protective effect and failure mechanism of ZrO₂ coating on Zry-4 under varied LiOH concentrations was further revealed by comparison with the coating corrosion performance in pure water (namely 0 ppm Li). ZrO₂ coating provided a favorable corrosion protection with the occurrence of localized corrosion at low LiOH concentrations. Factors influencing corrosion resistance mainly include pitting corrosion extension, enhanced Li+ permeation, short-circuit diffusion of O²⁻ and ZrO₂ phase transformation. In highly-concentrated LiOH solutions, intergranular corrosion, internal oxidation, and perforation resulted in coating failure. Zr ions were released to coating surface to form flocculent ZrO₂ and ZrO₂ clusters due to the strong diffusion and dissolution tendency of α-Zr in the Zry-4 substrate. Considering that primary water of Pressurized Water Reactors usually includes 2.3 ppm Li, the stability of ZrO₂ make itself a candidate fuel cladding coating material. Under unfavorable conditions with high Li concentrations, more boric acid should be added to alleviate caustic corrosion of ZrO₂ coating once it is used. This work can provide some references to understand the service behavior of nuclear coatings under variable water chemistry conditions and promote the in-pile application of ZrO₂ coating.

Keywords: ZrO₂ coating, Zry-4, corrosion behavior, failure mechanism, LiOH concentration

Procedia PDF Downloads 85

Authors: Mustafa Col, Funda Gul Koc, Merve Yangaz, Eylem Subasi, Can Akbasoglu

Abstract:

G38NiCrMo8-4-4 steel is widely used in mining industries, machine parts, gears due to its high strength and toughness properties. In this study, microstructure, wear and mechanical properties of G38NiCrMo8-4-4 steel modified with boron used in the mining industry were investigated. For this purpose, cast materials were alloyed by melting in an induction furnace to include boron with the rates of 0 ppm, 15 ppm, and 50 ppm (wt.) and were formed in the dimensions of 150x200x150 mm by casting into the sand mould. Homogenization heat treatment was applied to the specimens at 1150˚C for 7 hours. Then all specimens were austenitized at 930˚C for 1 hour, quenched in the polymer solution and tempered at 650˚C for 1 hour. Microstructures of the specimens were investigated by using light microscope and SEM to determine the effect of boron and heat treatment conditions. Changes in microstructure properties and material hardness were obtained due to increasing boron content and heat treatment conditions after microstructure investigations and hardness tests. Wear tests were carried out using a pin-on-disc tribometer under dry sliding conditions. Charpy V notch impact test was performed to determine the toughness properties of the specimens. Fracture and worn surfaces were investigated with scanning electron microscope (SEM). The results show that boron element has a positive effect on the hardness and wear properties of G38NiCrMo8-4-4 steel.

Keywords: G38NiCrMo8-4-4 steel, boron, heat treatment, microstructure, wear, mechanical properties

Procedia PDF Downloads 195

Authors: Hamidreza Akbari

Abstract:

In this paper, for detection of inclined eccentricity in an induction motor, time–frequency analysis of the stator startup current is carried out. For this purpose, the discrete wavelet transform is used. Data are obtained from simulations, using winding function approach. The results show the validity of the approach for detecting the fault and discriminating with respect to other faults.

Keywords: induction machine, fault, DWT, electric

Procedia PDF Downloads 350

Authors: Mandeep Kataria, Ritu Narula, Navneet Kaur

Abstract:

Asparagine is vital amino acid which is required for the development of brain and it regulates the equilibrium of central nervous system. Asparagine is the chief amino acid that forms acrylamide in baked food by reacting with reducing sugars at high temperature ( Millard Reaction i.e. amino acids and sugars give new flavors at high temperature). It can also be a parameter of freshness in fruit juices because on storage of juices at 37°C caused an 87% loss in the total free amino acids and major decrease was recorded in asparagine contents. With this significance of monitoring asparagine, in the present work a biosensor for determining asparagine in fruit juices is developed. For the construction of biosensor L-asparaginase enzyme (0.5 IU) was co-immobilized with phenol red on TEOS chitosan sol-gel plastic disc and fixed on the fiber optic tip. Tip was immersed in a cell having 5ml of substrate and absorption was noted at response time of 5 min with 10-1 - 10-10 M concentrations of asparagine at 538 nm. L-asparaginase was extracted and from Solanum nigrum Asparagine biosensor was applied fruit juices on the monitoring asparagine contents. L-asparagine concentration found to be present in fruit juices like Guava Juice, Apple Juice, Mango Juice, Litchi juice, Strawberry juice, Pineapple juice Lemon juice, and Orange juice. Hence the developed biosensor has commercial aspects in quality insurance of fruit juices.

Keywords: fiber optic biosensor, chitosan, teos, l-asparaginase

Procedia PDF Downloads 289

Authors: M. Maier, I. Dedigama, J. Majasan, Y. Wu, Q. Meyer, L. Castanheira, G. Hinds, P. R. Shearing, D. J. L. Brett

Abstract:

Increasing the efficiency of electrolyser technology is commonly seen as one of the main challenges on the way to the Hydrogen Economy. There is a significant lack of understanding of the different states of operation of polymer electrolyte membrane water electrolysers (PEMWE) and how these influence the overall efficiency. This in particular means the two-phase flow through the membrane, gas diffusion layers (GDL) and flow channels. In order to increase the efficiency of PEMWE and facilitate their spread as commercial hydrogen production technology, new analytic approaches have to be found. Acoustic emission (AE) offers the possibility to analyse the processes within a PEMWE in a non-destructive, fast and cheap in-situ way. This work describes the generation and analysis of AE data coming from a PEM water electrolyser, for, to the best of our knowledge, the first time in literature. Different experiments are carried out. Each experiment is designed so that only specific physical processes occur and AE solely related to one process can be measured. Therefore, a range of experimental conditions is used to induce different flow regimes within flow channels and GDL. The resulting AE data is first separated into different events, which are defined by exceeding the noise threshold. Each acoustic event consists of a number of consequent peaks and ends when the wave diminishes under the noise threshold. For all these acoustic events the following key attributes are extracted: maximum peak amplitude, duration, number of peaks, peaks before the maximum, average intensity of a peak and time till the maximum is reached. Each event is then expressed as a vector containing the normalized values for all criteria. Principal Component Analysis is performed on the resulting data, which orders the criteria by the eigenvalues of their covariance matrix. This can be used as an easy way of determining which criteria convey the most information on the acoustic data. In the following, the data is ordered in the two- or three-dimensional space formed by the most relevant criteria axes. By finding spaces in the two- or three-dimensional space only occupied by acoustic events originating from one of the three experiments it is possible to relate physical processes to certain acoustic patterns. Due to the complex nature of the AE data modern machine learning techniques are needed to recognize these patterns in-situ. Using the AE data produced before allows to train a self-learning algorithm and develop an analytical tool to diagnose different operational states in a PEMWE. Combining this technique with the measurement of polarization curves and electrochemical impedance spectroscopy allows for in-situ optimization and recognition of suboptimal states of operation.

Keywords: acoustic emission, gas diffusion layers, in-situ diagnosis, PEM water electrolyser

Procedia PDF Downloads 156

Authors: Jigg Pelayo, Ricardo Villar

Abstract:

Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

Procedia PDF Downloads 245

Authors: Myungsu Lim, William Xiu Shun Wong, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Namgyu Kim

Abstract:

The amount of real-time data generated through various mass media has been increasing rapidly. In this study, we had performed topic analysis by using the unstructured text data that is distributed through news article. As one of the most prevalent applications of topic analysis, the issue tracking technique investigates the changes of the social issues that identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has limitation that it cannot discover dynamic mutation process of complex social issues. The purpose of this study is to overcome the limitations of the existing issue tracking method. We first derived core issues of each period, and then discover the dynamic mutation process of various issues. In this study, we further analyze the mutation process from the perspective of the issues categories, in order to figure out the pattern of issue flow, including the frequency and reliability of the pattern. In other words, this study allows us to understand the components of the complex issues by tracking the dynamic history of issues. This methodology can facilitate a clearer understanding of complex social phenomena by providing mutation history and related category information of the phenomena.

Keywords: Data Mining, Issue Tracking, Text Mining, topic Analysis, topic Detection, Trend Detection

Procedia PDF Downloads 408

Authors: Leila Fozouni, Anahita Mazandarani

Abstract:

Background: Maternal infections are the most common cause of infections in infants, and the level of infection and its severity highly depends on the degree of colonization of the bacteria in the mother; so, the occurrence of aggressive diseases is not unpredictable in mothers with very high colonization. Group B Streptococcus is part of the normal flora of the gastrointestinal and genital tracts in women and is the leading cause of septicemia and meningitis in newborns. Today Zinc oxide nanoparticle is regarded as one of the most commonly used and safest nanoparticles for defeating Gram-positive and Gram-negative bacteria. This study aims to determine the antibacterial effects of Zinc oxide on the growth of drug-resistant group B Streptococcus strains isolated from pregnant women. Materials and Methods: This cross-sectional study was conducted on 150 pregnant women of 28–37 weeks admitted to seven hospitals and maternity wards in Golestan province, northeast of Iran. For bacterial identification, rectovaginal swabs were firstly inoculated to the Todd-Hewitt Broth and cultured in blood agar (containing 5% sheep blood). Then microbiologic and PCR methods were performed to detect group B Streptococci. Disk diffusion and broth microdilution tests were used to determine the bacterial susceptibility to antibiotics according to CLSI M100(2021) criteria. The antibacterial properties of Zinc oxide nanoparticles were evaluated using the agar well-diffusion method. Results: The prevalence of group B Streptococcus was 18% in pregnant women. Out of twenty-seven positive cultures, 62.96% were higher than thirty years old. Ninety percent and 45% of isolates were resistant to clindamycin and erythromycin, respectively, and susceptibility to cefazolin was 71%. In addition, susceptibility to ampicillin and penicillin were 74% and 55%, respectively. The results showed that 82% of erythromycin-resistant, 92% clindamycin-resistant, and 78% of cefazolin-resistant isolates were eliminated by zinc oxide nanoparticles at a concentration of 100 mg/L of the nanoparticle. Furthermore, ZnONPs could inhibit all drug-resistant isolates at a concentration of 200 mg/mL (MIC90 ≥ 200). Conclusion: Since the drug resistance of group B streptococci against various antibiotics is increasing, determining and investigating the drug-resistance pattern of this bacterium to different antibiotics in order to prevent arbitrary consumption of antibiotics by pregnant women and ultimately prevent Infant mortality seems necessary. Generally, ZnONPs showed a high antimicrobial effect, and it was revealed that the bactericide effect increases upon the increase in the concentration of the nanoparticle.

Keywords: group B beta-hemolytic streptococcus, pregnant women, zinc oxide nanoparticles, drug resistance

Procedia PDF Downloads 99

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

Abstract:

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

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

Procedia PDF Downloads 319

Authors: N. Varsamis, M. Gerasimou, P. Christodoulou, S. Mantzoukis, G. Kolliopoulou, N. Zotos

Abstract:

Purpose: Body fluids (pleural, peritoneal, synovial, pericardial, cerebrospinal) are an important element in the detection of microorganisms. For this reason, it is important to examine them in the Intensive Care Unit (ICU) patients. Material and Method: Body fluids are transported through sterile containers and enriched as soon as possible with Tryptic Soy Broth (TSB). After one day of incubation, the broth is poured into selective media: Blood, Mac Conkey No. 2, Chocolate, Mueller Hinton, Chapman and Saboureaud agar. The above selective media are incubated directly for 2 days. After this period, if any number of microbial colonies are detected, gram staining is performed. After that, the isolated organisms are identified by biochemical techniques in the automated Microscan system (Siemens) and followed by a sensitivity test on the same system using the minimum inhibitory concentration MIC technique. The sensitivity test is verified by Kirby Bauer-based plate test. Results: In 2017 the Laboratory of Microbiology received 60 samples of body fluids from the ICU. More specifically the Microbiology Department received 6 peritoneal fluid specimens, 18 pleural fluid specimens and 36 cerebrospinal fluid specimens. 36 positive cultures were tested. S. epidermidis was identified in 18 specimens, S. haemolyticus in 6, and E. faecium in 12. Conclusions: The results show low detection of microorganisms in body fluid cultures.

Keywords: body fluids, culture, intensive care unit, microorganisms

Procedia PDF Downloads 202

Authors: Todd Zhou, Mikhail Yurochkin

Abstract:

Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

Procedia PDF Downloads 124

Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

Abstract:

This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

Procedia PDF Downloads 134

Authors: M. Etezadi, A. Fahimifar

Abstract:

In many geotechnical designs in rocks and rock masses, tensile strength of rock and rock mass is needed. The difficulties associated with performing a direct uniaxial tensile test on a rock specimen have led to a number of indirect methods for assessing the tensile strength that in the meantime the Brazilian test is more popular. Brazilian test is widely applied in rock engineering because specimens are easy to prepare, the test is easy to conduct and uniaxial compression test machines are quite common. This study compares experimental results of direct and Brazilian tensile tests carried out on two rock types and three concrete types using 39 cylindrical and 28 disc specimens. The tests are performed using Servo-Control device. The relationship between direct and indirect tensile strength of specimens is extracted using linear regression. In the following, tensile strength of direct and indirect test is evaluated using finite element analysis. The results are analyzed and effective factors on results are studied. According to the experimental results Brazilian test is shown higher tensile strength than direct test. Because of decreasing the contact surface of grains and increasing the uniformity in concrete specimens with fine aggregate (largest grain size= 6mm), higher tensile strength in direct test is shown. The experimental and numerical results of tensile strength are compared and empirical relationship witch is obtained from experimental tests is validated.

Keywords: tensile strength, brittle materials, direct and indirect tensile test, numerical modeling

Procedia PDF Downloads 548

Authors: S. Shankar Bharathi

Abstract:

Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

Procedia PDF Downloads 428

Authors: Tanju Teker, Yener Tekeli̇, Esra Karpuz

Abstract:

Salvia species are known as medicinal plant and often used in public. The antimicrobial effects and essential oil composition of Salvia verticillata L. subsp. amasiaca were determined. The antimicrobial activity is determined by using disk diffusion method against two Gram-positive bacteria, two Gram-negative bacteria and one kind of yeast and essential oil composition was determined by GC - MS. As a result of antimicrobial analysis while sample has shown very strong antimicrobial activity against Staphylococcus aureus, moderately effective against Pseudomonas aeruginosa and low effective against Enterococcus faecalis, it has not shown antimicrobial activity against Escherichia coli and C. albicans. Trans-caryophyllene (% 35.07), germacrene-d (% 10.98) and caryopyllene oxide (% 5.81) are the main components of essential oil composition.

Keywords: salvia, medicinal plant, antimicrobial activity, essential oil

Procedia PDF Downloads 458

Authors: Mohamed El Morsy, Gabriela Achtenová

Abstract:

Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs. This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of cepstrum analysis in detection and diagnosis of the gear condition.

Keywords: cepstrum analysis, fault diagnosis, gearbox, vibration signals

Procedia PDF Downloads 379

Authors: Praveena Nair Sivasankaran, Thomas Arthur Ward, Rubentheren Viyapuri

Abstract:

Paper describes a methodology to fabricate a simplified dragonfly wing structure using balsa wood and red prepreg fibre glass. These simplified wing structures were created for use in Biomimetic Micro Air Vehicles (BMAV). Dragonfly wings are highly corrugated and possess complex vein structures. In order to mimic the wings function and retain its properties, a simplified version of the wing was designed. The simplified dragonfly wing structure was created using a method called spatial network analysis which utilizes Canny edge detection method. The vein structure of the wings were carved out in balsa wood and red prepreg fibre glass. Balsa wood and red prepreg fibre glass was chosen due to its ultra- lightweight property and hence, highly suitable to be used in our application. The fabricated structure was then immersed in a nanocomposite solution containing chitosan as a film matrix, reinforced with chitin nanowhiskers and tannic acid as a crosslinking agent. These materials closely mimic the membrane of a dragonfly wing. Finally, the wings were subjected to a bending test and comparisons were made with previous research for verification. The results had a margin of difference of about 3% and thus the structure was validated.

Keywords: dragonfly wings, simplified, Canny edge detection, balsa wood, red prepreg, chitin, chitosan, tannic acid

Procedia PDF Downloads 331

Authors: Mehwish Asghar

Abstract:

Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

Procedia PDF Downloads 225

Authors: Srestha Chaturabul, Wanchalerm Srirachat, Thanaporn Wannachod, Prakorn Ramakul, Ura Pancharoen, Soorathep Kheawhom

Abstract:

The separation of mercury(II) from petroleum-produced water from the Gulf of Thailand was carried out using a hollow fiber supported liquid membrane system (HFSLM). Optimum parameters for feed pretreatment were 0.2 M HCl, 4% (v/v) Aliquat 336 for extractant and 0.1 M thiourea for stripping solution. The best percentage obtained for extraction was 99.73% and for recovery 90.11%, respectively. The overall separation efficiency noted was 94.92% taking account of both extraction and recovery prospects. The model for this separation developed along a combined flux principle i.e. convection–diffusion–kinetic. The results showed excellent agreement with theoretical data at an average standard deviation of 1.5% and 1.8%, respectively.

Keywords: separation, mercury(ii), petroleum produced water, hollow fiber, liquid membrane

Procedia PDF Downloads 298

Authors: Salah Hamri, Tewfik Bouchaour, Ulrich Maschke

Abstract:

The aim of this works is the study of swelling ratio of cross-linked polymer networks poly (2-hydroxyethyl methacrylate) (PHEMA). The system composed of erythrosine and Triethanolamine, in aqueous medium, is used as photo-initiator and 1,6-Hexanediol diacrylate as cross-linker. The analysis of UV-visible and infrared spectra, which were taken at different times during polymerization/cross linking, makes it possible to obtain useful information on the reaction mechanism. The swelling behavior was study by changing the nature of solvent, dye sensitizer (erythrosine, rose Bengal and eosin), and pH of the medium. The exploitation of experimental results using Fick diffusion model is also expected and shows a good correlation between theoretical and experimental results.

Keywords: cross-linker, photo-sensitizer, polymer network, swelling ratio

Procedia PDF Downloads 316