Search results for: real sample analysis

Authors: Ferhat Mohamed, Boukhatem Mohamed Nadjib, Chemat Farid

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Simultaneous distillation–extraction (SDE) is routinely used by analysts for sample preparation prior to gas chromatography analysis. In this work, a new process design and operation for microwave assisted simultaneous distillation – solvent extraction (MW-SDE) of volatile compounds was developed. Using the proposed method, isolation, extraction and concentration of volatile compounds can be carried out in a single step. To demonstrate its feasibility, MW-SDE was compared with the conventional technique, Simultaneous distillation–extraction (SDE), for gas chromatography-mass spectrometry (GC-MS) analysis of volatile compounds in a fresh orange juice and a dry spice “carvi seeds”. SDE method required long time (3 h) to isolate the volatile compounds, and large amount of organic solvent (200 mL of hexane) for further extraction, while MW-SDE needed little time (only 30 min) to prepare sample, and less amount of organic solvent (10 mL of hexane). These results show that MW-SDE–GC-MS is a simple, rapid and solvent-less method for determination of volatile compounds from aromatic plants.

Keywords: essential oil, extraction, distillation, carvi seeds

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Authors: Sepulveda Juan

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This article explains the elements and considerations taken into account when implementing and applying patent evaluation and scientometric study in the identifications of technology trends, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.

Keywords: patents, scientometric, renewable energy, technology maps

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Authors: Mohammad Hashemi, John Herbert

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Quantifying and measuring Quality of Experience (QoE) are important and difficult concerns in Human Computer Interaction (HCI). Quality of Service (QoS) and the actual User Interface (UI) of the application are both important contributors to the QoE of a user. This paper describes a framework that measures accurately the way a user uses the UI in order to model users' behaviours and profiles. It monitors the use of the mouse and use of UI elements with accurate time measurement. It does this in real-time and does so unobtrusively and efficiently allowing the user to work as normal with the application. This real-time accurate measurement of the user's interaction provides valuable data and insight into the use of the UI, and is also the basis for analysis of the user's QoE.

Keywords: user modelling, user interface experience, quality of experience, user experience, human and computer interaction

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Authors: Diptoshi Roy, G. Sreevidya Varma, S. Asokan, Chandasree Das

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Germanium Telluride based quaternary thin film switching devices with composition Ge₁₅In₅Te₅₆Ag_24, have been deposited in sandwich geometry on glass substrate with aluminum as top and bottom electrodes. The bulk glassy form of the said composition is prepared by melt quenching technique. In this technique, appropriate quantity of elements with high purity are taken in a quartz ampoule and sealed under a vacuum of 10^-5 mbar. Then, it is allowed to rotate in a horizontal rotary furnace for 36 hours to ensure homogeneity of the melt. After that, the ampoule is quenched into a mixture of ice - water and NaOH to get the bulk ingot of the sample. The sample is then coated on a glass substrate using flash evaporation technique at a vacuum level of 10^-6 mbar. The XRD report reveals the amorphous nature of the thin film sample and Energy - Dispersive X-ray Analysis (EDAX) confirms that the film retains the same chemical composition as that of the base sample. Electrical switching behavior of the device is studied with the help of Keithley (2410^c) source-measure unit interfaced with Lab VIEW 7 (National Instruments). Switching studies, mainly SET (changing the state of the material from amorphous to crystalline) operation is conducted on the thin film form of the sample. This device is found to manifest memory switching as the device remains 'ON' even after the removal of the electric field. Also it is found that amorphous Ge₁₅In₅Te₅₆Ag₂₄ thin film unveils clean memory type of electrical switching behavior which can be justified by the absence of fluctuation in the I-V characteristics. The I-V characteristic also reveals that the switching is faster in this sample as no data points could be seen in the negative resistance region during the transition to on state and this leads to the conclusion of fast phase change during SET process. Scanning Electron Microscopy (SEM) studies are performed on the chosen sample to study the structural changes at the time of switching. SEM studies on the switched Ge₁₅In₅Te₅₆Ag₂₄ sample has shown some morphological changes at the place of switching wherein it can be explained that a conducting crystalline channel is formed in the device when the device switches from high resistance to low resistance state. From these studies it can be concluded that the material may find its application in fast switching Non-Volatile Phase Change Memory (PCM) Devices.

Keywords: Chalcogenides, Vapor deposition, Electrical switching, PCM.

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Authors: Fernández-Brito David, Lopez-Medina Javier Alonso, Murillo-Bracamontes Eduardo Antonio, Palomino-Ovando Martha Alicia, Gervacio-Arciniega José Juan

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Magnetic Force Microscopy (MFM) is an Atomic Force Microscopy (AFM) technique that characterizes, at a nanometric scale, the magnetic properties of ferromagnetic materials. Conventional MFM works by scanning in two different AFM modes. The first one is tapping mode, in which the cantilever has short-range force interactions with the sample, with the purpose to obtain the topography. Then, the lift AFM mode starts, raising the cantilever to maintain a fixed distance between the tip and the surface of the sample, only interacting with the magnetic field forces of the sample, which are long-ranged. In recent years, there have been attempts to improve the MFM technique. Bimodal MFM was first theoretically developed and later experimentally proven. In bimodal MFM, the AFM internal piezoelectric is used to cause the cantilever oscillations in two resonance modes simultaneously, the first mode detects the topography, while the second is more sensitive to the magnetic forces between the tip and the sample. However, it has been proven that the cantilever vibrations induced by the internal AFM piezoelectric ceramic are not optimal, affecting the bimodal MFM characterizations. Moreover, the Secondary Resonance Magnetic Force Microscopy (SR-MFM) was developed. In this technique, a coil located below the sample generates an external magnetic field. This alternating magnetic field excites the cantilever at a second frequency to apply the Bimodal MFM mode. Nonetheless, for ferromagnetic materials with a low coercive field, the external field used in SR-MFM technique can modify the magnetic domains of the sample. In this work, a Hybrid Bimodal MFM (HB-MFM) technique is proposed. In HB-MFM, the bimodal MFM is used, but the first resonance frequency of the cantilever is induced by the magnetic field of the ferromagnetic sample due to its vibrations caused by a piezoelectric element placed under the sample. The advantages of this new technique are demonstrated through the preliminary results obtained by HB-MFM on a hard disk sample. Additionally, traditional two pass MFM and HB-MFM measurements were compared.

Keywords: magnetic force microscopy, atomic force microscopy, magnetism, bimodal MFM

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Authors: N. Scheidegger, A. Mueller

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Job preferences are a well-developed research field. Many studies analyze the preferences using simple ratings with a sample of university graduates. The current study analyzes the preferences with a mixed method approach of a qualitative preliminary study and adaptive conjoint-analysis. Preconditions of accepting job offers are clarified for professionals in the industrial sector. It could be shown that, e.g. wages above the average are critical and that career opportunities must be seen broader than merely a focus on formal personnel development programs. The results suggest that, to be effective with their recruitment efforts, employers must take into account key desirable job attributes of their target group.

Keywords: conjoint analysis, employer attractiveness, job preferences, personnel marketing

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Authors: Rabia Qusien

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New media has emerged as a significant force in the society which connects people across the globe. Where new media brought many advantages for its users, there is a darker aspect of new technology in the form of cyberbullying. Researcher has employed survey method to reach to its targeted audience. Sample of 604 respondents was selected from one of metropolitan city of Pakistan Lahore to collect the data. Equal sample from both genders was selected to apply gender analysis. Results of this study indicate that cyber bullying is having significant psychological and educational effects. Females face more cyber bullying incidents as compared to males so they face more severe effects of cyber bullying. A comprehensive analysis of managing strategies depicts that mostly youth tries to handle this issue personally but at times they seek the support of their family and friends when they face severe issues. Due to privacy concerns females get more upset and they are more likely to seek social support from friends and family.

Keywords: cyber bullying, cyber victims, educational impacts, psychological impacts

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Authors: Seden Demirtaş, Feyza Tantekin Erden

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The importance of research in early childhood education is growing all around the world. This study aims to investigate research trends in graduate theses written in Turkey in the area of early childhood education. Descriptive, contextual and methodological aspects of graduate theses were analyzed to investigate the trends. A sample of the study consisted of 1000 graduate theses (n= 1000) including both MS theses and Ph.D. dissertations. Theses and dissertations were obtained from the thesis database of Council of Higher Education (CoHE). An investigation form was developed by the researcher to analyze graduate theses. The investigation forms validated by expert opinion from early childhood education department. To enhance the reliability of the investigation form, inter-coder agreement was measured by Cohen’s Kappa value (.86). Data were gathered via using the investigation form, and content analysis method was used to analyze the data. Results of the analysis were presented by descriptive statistics and frequency tables. Analysis of the study is on-going and preliminary results of the study show that master theses related to early childhood education have started to be written in 1986, and the number of the theses has increased gradually. In most of the studies, sample group consisted of children especially in between 5-6 age group. Child development, activities (applied in daily curriculum of preschools) and teaching methods are the mostly examined concepts in graduate theses. Qualitative and quantitative research methods were referred equally by researchers in these theses.

Keywords: content analysis, early childhood education, graduate thesis, research trends

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Authors: S. Oudjemia, F. Alim, S. Seddiki

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This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

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Authors: Shan-e-Fatima, Mushtaq Khan, Syed Imran Hussian

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Plasma arc welding technology is used for welding SS-304L with A-36. Two different optimize butt welded joints were produced by using austenitic filler alloy E-309L and with direct fusion at 45 A, 2mm/sec by keeping plasma gas flow rate at 0.5LPM. Microstructure analysis of the weld bead was carried out. The results reveal complex heterogeneous microstructure in austenitic base filler alloy sample where as full martensite was found in directly fused sample.

Keywords: fusion zone microstructure, stainless steel, low carbon steel, plasma arc welding

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Authors: Chen Bo, Wen Zengping

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Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment.

Keywords: ground motion selection, scaling method, seismic fragility analysis, spectral shape

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Authors: Deepanjali Gurav, Kun Qian

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In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

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Authors: Maxime Farin, Emmanuel Moulin, Lynda Chehami, Farouk Benmeddour, Pierre Campistron

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Assessing corrosion is crucial in the petrochemical and marine industry. Usual ultrasonic methods based on guided waves to detect corrosion can inspect large areas but lack precision. We propose a complementary and sensitive ultrasonic method (~ 10 MHz) based on coda wave interferometry to detect and quantify corrosion at the surface of a steel sample. The method relies on a single piezoelectric transducer, exciting the sample and measuring the scattered coda signals at different instants in time. A laboratory experiment is conducted with a steel sample immersed in salted water for 60~h with parallel coda and temperature measurements to correct coda dependence to temperature variations. Micrometric changes to the sample surface caused by corrosion are detected in the late coda signals, allowing precise corrosion detection. Moreover, a good correlation is found between a parameter quantifying the temperature-corrected stretching of the coda over time with respect to a reference without corrosion and the corrosion surface over the sample recorded with a camera.

Keywords: coda wave interferometry, nondestructive evaluation, corrosion, ultrasonics

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Authors: S. I. Usenko, V. N. Golubeva, I. A. Konopkina, I. V. Astakhova, O. V. Vakhnina, A. A. Korableva, A. A. Kalinina, K. B. Zhogova

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Gold can be determined in natural objects and manufactured articles of different origin. The up-to-date status of research and problems of high gold level determination in alloys and manufactured articles are described in detail in the literature. No less important is the task of this metal determination in minerals, process products and waste pieces. The latters, as objects of gold content chemical analysis, are most hard-to-study for two reasons: Because of high requirements to accuracy of analysis results and because of difference in chemical and phase composition. As a rule, such objects are characterized by compound, variable and very often unknown matrix composition that leads to unpredictable and uncontrolled effect on accuracy and other analytical characteristics of analysis technique. In this paper, the methods for the determination of gold are described, using flame atomic-absorption spectrophotometry and gravimetric analysis technique. The techniques are aimed at gold determination in a solution for gold etching (KJ+J2), in the technological mixture formed after cleaning stainless steel members of vacuum-deposit installation with concentrated nitric and hydrochloric acids as well as in gold-containing powder resulted from liquid wastes reprocessing. Optimal conditions for sample preparation and analysis of liquid and solid waste specimens of compound and variable matrix composition were chosen. The boundaries of relative resultant error were determined for the methods within the range of gold mass concentration from 0.1 to 30g/dm3 in the specimens of liquid wastes and mass fractions from 3 to 80% in the specimens of solid wastes.

Keywords: microelectronics waste pieces, gold, sample preparation, atomic-absorption spectrophotometry, gravimetric analysis technique

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Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

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The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

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Authors: Abubakar Umar Birnin-yauri

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Plastic wastes arising from Polyethylene (PE)-based materials are increasingly becoming environmental problem, this is owed to the fact that these PE waste materials will only decompose over hundreds, or even thousands of years, during which they cause serious environmental problems. In this research, Polymer blends prepared from PE, Cashewnut flour (CNF) and Gum Arabic (GA) were studied in order to assay their biodegradation potentials via composting method. Different sample formulations were made i.e., X1= (70% PE, 25% CNF and 5% GA, X2= (70% PE, 20% CNF and 10% GA), X3= (70% PE, 15% CNF and 15% GA), X4 = (70% PE, 10% CNF and 20% GA) and X5 = (70% PE, 5% CNF and 25% GA) respectively. The results obtained showed that X1 recorded weight loss of 9.89% of its original weight after the first 20 days and 37.45% after 100 day, and X2 lost 12.67 % after the first 20 days and 42.56% after 100day, sample X5 experienced the greatest weight lost in the two methods adopted which are 52.9% and 57.89%. Instrumental analysis such as Fourier Transform Infrared Spectroscopy, Thermogravimetric analysis and Scanning electron microscopy were performed on the polymer blends before and after biodegradation. The study revealed that the biodegradation of the polymer blends is influenced by the contents of both the CNF and GA added into the blends.

Keywords: polyethylene, cashewnut, gum Arabic, biodegradation, blend, environment

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Authors: Andrey V. Timofeev

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An adaptive nonparametric method is proposed for stable real-time detection of seismoacoustic sources in multichannel C-OTDR systems with a significant number of channels. This method guarantees given upper boundaries for probabilities of Type I and Type II errors. Properties of the proposed method are rigorously proved. The results of practical applications of the proposed method in a real C-OTDR-system are presented in this report.

Keywords: guaranteed detection, multichannel monitoring systems, change point, interval estimation, adaptive detection

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Authors: Raghunath Arnab

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The two-phase sampling which is also known as double sampling was introduced in 1938. In two-phase sampling, samples are selected in phases. In the first phase, a relatively large sample of size is selected by some suitable sampling design and only information on the auxiliary variable is collected. During the second phase, a sample of size is selected either from, the sample selected in the first phase or from the entire population by using a suitable sampling design and information regarding the study and auxiliary variable is collected. Evidently, two phase sampling is useful if the auxiliary information is relatively easy and cheaper to collect than the study variable as well as if the strength of the relationship between the variables and is high. If the sample is selected in more than two phases, the resulting sampling design is called a multi-phase sampling. In this article we will consider how one can use data collected at the first phase sampling at the stages of estimation of the parameter, stratification, selection of sample and their combinations in the second phase in a unified setup applicable to any sampling design and wider classes of estimators. The problem of the estimation of variance will also be considered. The variance of estimator is essential for estimating precision of the survey estimates, calculation of confidence intervals, determination of the optimal sample sizes and for testing of hypotheses amongst others. Although, the variance is a non-negative quantity but its estimators may not be non-negative. If the estimator of variance is negative, then it cannot be used for estimation of confidence intervals, testing of hypothesis or measure of sampling error. The non-negativity properties of the variance estimators will also be studied in details.

Keywords: auxiliary information, two-phase sampling, varying probability sampling, unbiased estimators

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Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Amber C. W. Vandepoele, Michael A. Marciano

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Biological analyses frequently focus on single organisms, however many times, the biological sample consists of more than the target organism; for example, human microbiome research targets bacterial DNA, yet most samples consist largely of human DNA. Therefore, there would be an advantage to removing these contaminating organisms. Conversely, some analyses focus on a single organism but would greatly benefit from the additional information regarding the other organismal components of the sample. Forensic analysis is one such example, wherein most forensic casework, human DNA is targeted; however, it typically exists in complex non-pristine sample substrates such as soil or unclean surfaces. These complex samples are commonly comprised of not just human tissue but also microbial and plant life, where these organisms may help gain more forensically relevant information about a specific location or interaction. This project aims to optimize a ‘phylogenetic’ differential extraction method that will separate mammalian, bacterial and plant cells in a mixed sample. This is accomplished through the use of size exclusion separation, whereby the different cell types are separated through multiple filtrations using 5 μm filters. The components are then lysed via differential enzymatic sensitivities among the cells and extracted with minimal contribution from the preceding component. This extraction method will then allow complex DNA samples to be more easily interpreted through non-targeting sequencing since the data will not be skewed toward the smaller and usually more numerous bacterial DNAs. This research project has demonstrated that this ‘phylogenetic’ differential extraction method successfully separated the epithelial and bacterial cells from each other with minimal cell loss. We will take this one step further, showing that when adding the plant cells into the mixture, they will be separated and extracted from the sample. Research is ongoing, and results are pending.

Keywords: DNA isolation, geolocation, non-human, phylogenetic separation

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Authors: N. R. N. Mendis, S. N. Silva

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Introduction: Patient satisfaction of services provided by primary care health services depends on many factors. One key factor in this depends on is the nursing services received in primary care. Since majority of the primary care in Sri Lanka is provided by the private sector, it is important to assess patient satisfaction on this. Objective: To assess the satisfaction among the public on nurses working in dispensaries in Sri Lanka. Methods: A descriptive study was done on 200 individual selected using convenient sampling among dispensaries in Gampaha district, Sri Lanka. Results: 59.3% of the sample had long term illnesses or disabilities and all of them preferred speaking to a nurse. 70.9% of the sample used to make appointments with nurses while 57.8% out of them were comfortable in discussing their health concerns. 98.9 % agreed that they get individual attention by the nurses. Majority of the sample that is 34.2% spends around 20 minutes with the nurse without even making any pay. Significantly, the whole sample believes that the nurses are professional and admits that the care given is of high quality. All 100% of the sample said that the nurses could understand their concerns while 93.5% admitted that it was very useful in their recovery. Conclusions: Majority of the public were very much satisfied with the nurses and their practice at the dispensaries.

Keywords: health education, nurses practices, patient satisfaction, primary care

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Authors: Silka Abyadati, Dadi Rusdiana, Enjang Akhmad Juanda

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This study aims to investigate the students’ mastery concepts enhancement between students who are studying by using Integrated Real-Life Video and Animation (IRVA) and students who are studying without using IRVA. The development of IRVA is conducted by five stages: Analyze, Design, Development, Implementation and Evaluation (ADDIE) based on constructivist for Rotational Dynamics material in Physics learning. A constructivist model-based learning used is Interpretation Construction (ICON), which has the following phases: 1) Observation, 2) Construction interpretation, 3) Contextualization prior knowledge, 4) Conflict cognitive, 5) Learning cognitive, 6) Collaboration, 7) Multiple interpretation, 8) Multiple manifestation. The IRVA is developed for the stages of observation, cognitive conflict and cognitive learning. The sample of this study consisted of 32 students experimental group and a control group of 32 students in class XI of the school year 2015/2016 in one of Senior High Schools Bandung. The study was conducted by giving the pretest and posttest in the form of 20 items of multiple choice questions to determine the enhancement of mastery concept of Rotational Dynamics. Hypothesis testing is done by using T-test on the value of N-gain average of mastery concepts. The results showed that there is a significant difference in an enhancement of students’ mastery concepts between students who are studying by using IRVA and students who are studying without IRVA. Students in the experimental group increased by 0.468 while students in the control group increased by 0.207.

Keywords: ADDIE, constructivist learning, Integrated Real-Life Video and Animation, mastery concepts, rotational dynamics

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Authors: Emily Kambalame

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Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions outperformed other retention allocations by identifying the optimal solution with the fewest function evaluation

Keywords: design optimization, multi-objective evolutionary, penalty-free, water distribution systems

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

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Authors: Homayon Ahmad Panahi, Seyed Mehdi Seyed Nejad, Elham Moniri

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A novel bio-adsorbent is fabricated by attaching a cibacron blue to yeast cells. The modified bio-sorbent has been characterized by some techniques like Fourier transform infrared spectroscopy (FT-IR) and elemental analysis (CHN) and applied for the preconcentration and determination of samarium from aqueous water samples. The best pH value for adsorption of the brilliant crecyle blue by yeast cells- cibacron blue was 7. The sorption capacity of modified biosorbent was 18.5 mg. g⁻¹. A recovery of 95.3% was obtained for Sm(III) when eluted with 0.5 M nitric acid. The method was applied for Sm(III) preconcentration and determination in river water sample.

Keywords: samarium, solid phase extraction, yeast cells, water sample, removal

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: P. van Tonder, U. Bagdadi, B. M. D. Lario, Z. Masina, T. R. Motshwari

Abstract:

This paper analyses how concrete reinforcing steel bars corrode and how it can be minimised through the use of various protection methods against corrosion, such as metal-based paint, alloying, cathodic protection and electroplating. Samples of carbon steel bars were protected, using these four methods. Tests performed on the samples included durability, electrical resistivity and bond strength. Durability results indicated relatively low corrosion rates for alloying, cathodic protection, electroplating and metal-based paint. The resistivity results indicate all samples experienced a downward trend, despite erratic fluctuations in the data, indicating an inverse relationship between electrical resistivity and corrosion rate. The results indicated lowered bond strengths when the reinforced concrete was cured in seawater compared to being cured in normal water. It also showed that higher design compressive strengths lead to higher bond strengths which can be used to compensate for the loss of bond strength due to corrosion in a real-world application. In terms of implications, all protection methods have the potential to be effective at resisting corrosion in real-world applications, especially the alloying, cathodic protection and electroplating methods. The metal-based paint underperformed by comparison, most likely due to the nature of paint in general which can fade and chip away, revealing the steel samples and exposing them to corrosion. For alloying, stainless steel is the suggested material of choice, where Y-bars are highly recommended as smooth bars have a much-lowered bond strength. Cathodic protection performed the best of all in protecting the sample from corrosion, however, its real-world application would require significant evaluation into the feasibility of such a method.

Keywords: protection methods, corrosion, concrete, reinforcing steel bars

Procedia PDF Downloads 147

Authors: Purnima Dhall, Rita Kumar

Abstract:

Introduction: River Yamuna, in the national capital territory (NCT), and also the primary source of drinking water for the city. Delhi discharges about 3,684 MLD of sewage through its 18 drains in to the Yamuna. Water quality monitoring is an important aspect of water management concerning to the pollution control. Public concern and legislation are now a day’s demanding better environmental control. Conventional method for estimating BOD5 has various drawbacks as they are expensive, time-consuming, and require the use of highly trained personnel. Stringent forthcoming regulations on the wastewater have necessitated the urge to develop analytical system, which contribute to greater process efficiency. Biosensors offer the possibility of real time analysis. Methodology: In the present study, a novel rapid method for the determination of biochemical oxygen demand (BOD) has been developed. Using the developed method, the BOD of a sample can be determined within 2 hours as compared to 3-5 days with the standard BOD3-5day assay. Moreover, the test is based on specified consortia instead of undefined seeding material therefore it minimizes the variability among the results. The device is coupled to software which automatically calculates the dilution required, so, the prior dilution of the sample is not required before BOD estimation. The developed BOD-Biosensor makes use of immobilized microorganisms to sense the biochemical oxygen demand of industrial wastewaters having low–moderate–high biodegradability. The method is quick, robust, online and less time consuming. Findings: The results of extensive testing of the developed biosensor on drains demonstrate that the BOD values obtained by the device correlated with conventional BOD values the observed R2 value was 0.995. The reproducibility of the measurements with the BOD biosensor was within a percentage deviation of ±10%. Advantages of developed BOD biosensor • Determines the water pollution quickly in 2 hours of time; • Determines the water pollution of all types of waste water; • Has prolonged shelf life of more than 400 days; • Enhanced repeatability and reproducibility values; • Elimination of COD estimation. Distinctiveness of Technology: • Bio-component: can determine BOD load of all types of waste water; • Immobilization: increased shelf life > 400 days, extended stability and viability; • Software: Reduces manual errors, reduction in estimation time. Conclusion: BiosensorBOD can be used to measure the BOD value of the real wastewater samples. The BOD biosensor showed good reproducibility in the results. This technology is useful in deciding treatment strategies well ahead and so facilitating discharge of properly treated water to common water bodies. The developed technology has been transferred to M/s Forbes Marshall Pvt Ltd, Pune.

Keywords: biosensor, biochemical oxygen demand, immobilized, monitoring, Yamuna

Procedia PDF Downloads 251

Authors: Apotiola Z. O., Anyakorah C. I., Kuforiji O. O.

Abstract:

Sensory and microbial properties of fresh and canned Calocybe indica (milky mushroom) were evaluated. The mushroom was grown under a controlled environment with hardwood (Cola nitida) and rice bran substrate (4:1) canned in a brine solution of salt and citric acid. Analysis was carried out using standard methods. The overall acceptability ranged between 5.62 and 6.50, with sample S30 adjudged the best. In all, significant differences p<0.01 exist in the panelist judgment. Thus, the incorporation of salt and citric acid at 3.5g and 1.5g, respectively, improved sensory attributes such as texture, aroma, color, and overall acceptability. There was no coliform and fungi growth on the samples throughout the storage period. The bacterial count, on the other hand, was observed only in the fifth and sixth week of the storage period which varied between 0.2 to 0.9 x 103 cfu/g. The highest value was observed in sample S20 of the sixth week of storage, while the lowest value was recorded in sample S30 of the sixth week of storage. Based on 16S rRNA gene sequencing, bacterial species were taxonomically confirmed as Bacillus thuringiensis. The percentile compositions and Sequence ID of the bacterial species in the mushroom was 90%.

Keywords: bacterial count, microbial property, sensory, sawdust, texture

Procedia PDF Downloads 25

Authors: Md. Shafiullah, Ali T. Al-Awami

Abstract:

This project proposes optimal scheduling of imported power of a load aggregator with the utilization of EVs to maximize its profit. As with the increase of renewable energy resources, electricity price in competitive market becomes more uncertain and, on the other hand, with the penetration of renewable distributed generators in the distribution network the predicted load of a load aggregator also becomes uncertain in real time. Though there is uncertainties in both load and price, the use of EVs storage capacity can make the operation of load aggregator flexible. LA submits its offer to day-ahead market based on predicted loads and optimized use of its EVs to maximize its profit, as well as in real time operation it uses its energy storage capacity in such a way that it can maximize its profit. In this project, load aggregators profit maximization algorithm is formulated and the optimization problem is solved with the help of CVX. As in real time operation the forecasted loads differ from actual load, the mismatches are settled in real time balancing market. Simulation results compare the profit of a load aggregator with a hypothetical group of 1000 EVs and without EVs.

Keywords: CVX, electricity market, load aggregator, load and price uncertainties, profit maximization, real time balancing operation

Procedia PDF Downloads 389