Search results for: soxhlet extraction method

Authors: Imen Debbabi, Hédi BelHadjSalah

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The Improved Element Free Galerkin (IEFG) method is presented to treat the steady states and the transient heat transfer problems. As a result of a combination between the Improved Moving Least Square (IMLS) approximation and the Element Free Galerkin (EFG) method, the IEFG's shape functions don't have the Kronecker delta property and the penalty method is used to impose the Dirichlet boundary conditions. In this paper, two heat transfer problems, transient and steady states, are studied to improve the efficiency of this meshfree method for 2D heat transfer problems. The performance of the IEFG method is shown using the comparison between numerical and analytic results.

Keywords: meshfree methods, the Improved Moving Least Square approximation (IMLS), the Improved Element Free Galerkin method (IEFG), heat transfer problems

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Authors: Strahinja Kovačević, Jelena Vladić, Senka Vidović, Zoran Zeković, Lidija Jevrić, Sanja Podunavac Kuzmanović

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Supercritical extracts of highly valuated medicinal plant Satureja montana were prepared by application of supercritical carbon dioxide extraction in the carbon dioxide pressure range from 125 to 350 bar and temperature range from 40 to 60°C. Using GC/MS method of analysis chemical profiles (aromatic constituents) of S. montana extracts were obtained. Self-training artificial neural networks were applied to predict the retention time of the analyzed terpenes in GC/MS system. The best ANN model obtained was multilayer perceptron (MLP 11-11-1). Hidden activation was tanh and output activation was identity with Broyden–Fletcher–Goldfarb–Shanno training algorithm. Correlation measures of the obtained network were the following: R(training) = 0.9975, R(test) = 0.9971 and R(validation) = 0.9999. The comparison of the experimental and predicted retention times of the analyzed compounds showed very high correlation (R = 0.9913) and significant predictive power of the established neural network.

Keywords: ANN regression, GC/MS, Satureja montana, terpenes

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Authors: Fatmawati Adam, Saidatul Syaima Mat Tari, Saiful Nizam Tajuddin, Nurul Salwa Azliyana Hamzah

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Essential oil of agarwood or known as Gaharu in Malay is highly prized for its value as luxury fragrances and incense. However, the complexities of the chemical composition of agarwood itself is the main challenge for establishment of an effective recovery method, which is able to ensure uniform qualities and standard for each batch of essential oil production. Agarwood markers are actually a blend of volatile and non-volatile compounds. While volatile molecules could be easily retrieved by the present distillation technique, the high solubility properties are the limiting factor for the latter. With regard to this, an elementary chemistry resolution study had been performed on commercial agarwood essential oil-water mixture, by the application of preparative HPLC and FTIR. Interpretation of the results leads to the theoretical postulation that, agarwood water mixture comprise of agarospirol, jinkohol, jinkoh eremol and khusenol. This study provides a pinpoint on the chemical characteristics of water soluble (non-volatile) agarwood compounds, therefore, will be an insight for researchers to develop a more strategic technique for their extraction. Thereafter the optimum quality of this essential oil could be controlled in a more improved way.

Keywords: Agarwood, Aquillaria Malaccensis, agarospirol, jinkohol, jinkoh eremol, khusenol

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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This paper presents an iteration method for the numerical solutions of a one-dimensional problem of generalized thermoelasticity with one relaxation time under given initial and boundary conditions. The thermoelastic material with variable properties as a power functional graded has been considered. Adomian’s decomposition techniques have been applied to the governing equations. The numerical results have been calculated by using the iterations method with a certain algorithm. The numerical results have been represented in figures, and the figures affirm that Adomian’s decomposition method is a successful method for modeling thermoelastic problems. Moreover, the empirical parameter of the functional graded, and the lattice design parameter have significant effects on the temperature increment, the strain, the stress, the displacement.

Keywords: Adomian, decomposition method, generalized thermoelasticity, algorithm

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Authors: Khairil I. Othman, Mahfuzah Mahayaddin, Zarina Bibi Ibrahim

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We develop and demonstrate a computationally efficient numerical technique to solve first order stiff differential equations. This technique is based on block method whereby three approximate points are calculated. The Cholistani of varied step sizes are presented in divided difference form. Stability regions of the formulae are briefly discussed in this paper. Numerical results show that this block method perform very well compared to existing methods.

Keywords: block method, divided difference, stiff, computational

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Authors: N. Benhabyles, K. Arab, O. Bouchenak, A. Baz

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The hypoglycemic and antihyperglycemic effects of flavonoids rich extract obtained from leaves of Olea europaea L. was analyzed in normal and alloxan induced diabetic rats. The extraction was performed by confrontation with organic solvents method, which yielded four extracts: Di ethyl Ether, Ethyl Acetate, Butanolic, and Aqueous extract. A single oral dose of 100 mg/kg of the different extract was evaluated for hypoglycemic activity in a glucose tolerance test in normal rats and 200 mg/kg, 400 mg/kg, 600 mg/kg of AE for anti-hyperglycemic activity in alloxan-induced (125 mg/kg) diabetic rats. Dosage of 100 mg/kg of the extract significantly decreased (p<0.05) blood glucose levels in the glucose tolerance test after 120 min. However, a better activity is obtained with the AE. For the anti-hyperglycemic study, the results showed a substantial decrease in blood glucose during the 2 h of treatment for all groups treated with different doses of flavonoids. From the results it can be concluded that flavonoids of O. europaea can be a potential candidate in treating the hyperglycemic conditions.

Keywords: alloxan, antihyperglycemic effect, diabetes mellitus, flavonoids, hypoglycemic effect, Olea europaea L.

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Authors: H. Majour, L. Djabri

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Many methods in the groundwater vulnerability have been developed in the world (methods like PRAST, DRIST, APRON/ARAA, PRASTCHIM, GOD). In this study, our choice dealt with two recent complementary methods using category mapping of index with weighting criteria (Point County Systems Model MSCP) namely the standard DRASTIC method and SI (Susceptibility Index). At present, these two methods are the most used for the mapping of the intrinsic vulnerability of groundwater. Two classes of groundwater vulnerability in the Biskra sandy aquifer were identified by the DRASTIC method (average and high) and the SI method (very high and high). Integrated analysis has revealed that the high class is predominant for the DRASTIC method whereas for that of SI the preponderance is for the very high class. Furthermore, we notice that the method SI estimates better the vulnerability for the pollution in nitrates, with a rate of 85 % between the concentrations in nitrates of groundwater and the various established classes of vulnerability, against 75 % for the DRASTIC method. By including the land use parameter, the SI method produced more realistic results.

Keywords: DRASTIC, SI, GIS, Biskra sandy aquifer, Algeria

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

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Authors: Ikram Mohamed Eltayeb, Ustina Saeed Barsoumbolice

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Cinnamomum zeylanicum belong to the family Lauraceae and Artemisia absinthium belong to the family Asteraceae. Both were traditionally used as antiemetic, anti-inflammatory and antidiabetic. In Sudan, the mixtures of the two plants were traditionally used for the treatment of diabetes. Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia. It is mainly classified into two major groups, type-1 and type-2. Type-2 is a combination of resistance to insulin action and an inadequate compensatory insulin secretory response. The treatment of type-2 diabetes mellitus (DM) with synthetic drugs have many side effects so many researches were conducted to overcome or reduce this side effects by using alternative medicine. The objective of this study is to investigate and compare the anti-diabetic activity of C. zeylanicum and A. absinthium and their combination with difference ratio. C. zeylanicum and A. absinthium were extracted by 96% ethanol using Soxhlet apparatus. Thirty-two rats were divided into eight groups; each group contains four rats. 1st group was administered with distilled water at dose of 10ml/kg, 2nd group had received glucose only at dose of 2g/kg intraperitoneal, the standard group (3rd group) had received Glibenclamide orally at dose of 0.45mg/kg, 4th group received 100 mg C. zeylanicum + 300 mg A. absinthium with a ratio of (25:75), 5th group received 300 mg C. zeylanicum + 100 mg A. absinthium with a ratio of (75:25), 6th group received 200 mg C. zeylanicum + 200 mg A. absinthiumwith a ratio of (50:50), 7th group received 400 mg of A. absinthium, 8th group received 400 mg of C. zeylanicum. Then the blood samples were taken Retro-orbitally at 0, 1, 2 and 4 hours and the glucose level was measured. Each plant alone and their combination with different ratios shows antidiabetic effect. The significant activity was shown by A. absinthium extract (400 mg/kg), combination of ratio of (75:25) A. absinthium: C. zeylanicum(400mg/kg) and then C. zeylanicum(400mg/kg) with p-value 0.001, 0.022, 0.030 respectively, the activity was found to be increased with time. The other combinations showed less activity with p-value > 0.05. The result concludes that the good antidiabetic activity was performed by A. absinthium alone and its activity decreased by increase combination ratio with C. zeylanicum. Which maybe explains by the antagonistic effect between the compounds of C. zeylanicum and A. absinthium.

Keywords: antidiabetic, Artemisia absinthium , cinnamomum zeylanicum, combination

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Authors: Archit Yajnik, Rustam Ali

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In this paper, numerical method based on discrete GHM multiwavelets is presented for solving the Fredholm integral equations of second kind. There is hardly any article available in the literature in which the integral equations are numerically solved using discrete GHM multiwavelet. A number of examples are demonstrated to justify the applicability of the method. In GHM multiwavelets, the values of scaling and wavelet functions are calculated only at t = 0, 0.5 and 1. The numerical solution obtained by the present approach is compared with the traditional Quadrature method. It is observed that the present approach is more accurate and computationally efficient as compared to quadrature method.

Keywords: GHM multiwavelet, fredholm integral equations, quadrature method, function approximation

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Authors: Prodromos E. Atlamazoglou

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The method of moments combined with the method of symmetrical components is used for the analysis of interstitial hyperthermia applicators. The basis and testing functions are both piecewise sinusoids, qualifying our technique as a Galerkin one. The dielectric coatings are modeled by equivalent volume polarization currents, which are simply related to the conduction current distribution, avoiding in that way the introduction of additional unknowns or numerical integrations. The results of our method for a four dipole circular array, are in agreement with those already published in literature for a same hyperthermia configuration. Apart from being accurate, our approach is more general, more computationally efficient and takes into account the coupling between the antennas.

Keywords: hyperthermia, integral equations, insulated antennas, method of symmetrical components

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Pratham Madnur, Prathamkumar Shetty, Sneha Varur, Gouri Parashetti

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In order to overcome conventional obstacles, this research paper investigates novel approaches for cricket pitch and ball detection that make use of cutting-edge technologies. The research integrates OpenCV for pitch inspection and modifies the YOLOv8 model for cricket ball detection in order to overcome the shortcomings of manual pitch assessment and traditional ball detection techniques. To ensure flexibility in a range of pitch environments, the pitch detection method leverages OpenCV’s color space transformation, contour extraction, and accurate color range defining features. Regarding ball detection, the YOLOv8 model emphasizes the preservation of minor object details to improve accuracy and is specifically trained to the unique properties of cricket balls. The methods are more reliable because of the careful preparation of the datasets, which include novel ball and pitch information. These cutting-edge methods not only improve cricket analytics but also set the stage for flexible methods in more general sports technology applications.

Keywords: OpenCV, YOLOv8, cricket, custom dataset, computer vision, sports

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Authors: Michael Huber, Maximilian J. Poller, Jens Tochtermann, Wolfgang Korth, Andreas Jess, Jakob Albert

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Aside from the desulfurisation, the denitrogenation of fuels is of great importance to minimize the environmental impact of transport emissions. The oxidative reaction pathway of organic nitrogen in the catalytic oxidative denitrogenation could be successfully elucidated. This is the first time such a pathway could be traced in detail in non-microbial systems. It was found that the organic nitrogen is first oxidized to nitrate, which is subsequently reduced to molecular nitrogen via nitrous oxide. Hereby, the organic substrate serves as a reducing agent. The discovery of this pathway is an important milestone for the further development of fuel denitrogenation technologies. The United Nations aims to counteract global warming with Net Zero Emissions (NZE) commitments; however, it is not yet foreseeable when crude oil-based fuels will become obsolete. In 2021, more than 50 million barrels per day (mb/d) were consumed for the transport sector alone. Above all, heteroatoms such as sulfur or nitrogen produce SO₂ and NOx during combustion in the engines, which is not only harmful to the climate but also to health. Therefore, in refineries, these heteroatoms are removed by hy-drotreating to produce clean fuels. However, this catalytic reaction is inhibited by the basic, nitrogenous reactants (e.g., quinoline) as well as by NH3. The ion pair of the nitrogen atom forms strong pi-bonds to the active sites of the hydrotreating catalyst, which dimin-ishes its activity. To maximize the desulfurization and denitrogenation effectiveness in comparison to just extraction and adsorption, selective oxidation is typically combined with either extraction or selective adsorption. The selective oxidation produces more polar compounds that can be removed from the non-polar oil in a separate step. The extraction step can also be carried out in parallel to the oxidation reaction, as a result of in situ separation of the oxidation products (ECODS; extractive catalytic oxidative desulfurization). In this process, H8PV5Mo7O40 (HPA-5) is employed as a homogeneous polyoxometalate (POM) catalyst in an aqueous phase, whereas the sulfur containing fuel components are oxidized after diffusion from the organic fuel phase into the aqueous catalyst phase, to form highly polar products such as H₂SO₄ and carboxylic acids, which are thereby extracted from the organic fuel phase and accumulate in the aqueous phase. In contrast to the inhibiting properties of the basic nitrogen compounds in hydrotreating, the oxidative desulfurization improves with simultaneous denitrification in this system (ECODN; extractive catalytic oxidative denitrogenation). The reaction pathway of ECODS has already been well studied. In contrast, the oxidation of nitrogen compounds in ECODN is not yet well understood and requires more detailed investigations.

Keywords: oxidative reaction pathway, denitrogenation of fuels, molecular catalysis, polyoxometalate

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Authors: B. Sellami, Y. Laskri, M. Belloufi

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Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, a new family of conjugate gradient method is proposed for unconstrained optimization. This method includes the already existing two practical nonlinear conjugate gradient methods, which produces a descent search direction at every iteration and converges globally provided that the line search satisfies the Wolfe conditions. The numerical experiments are done to test the efficiency of the new method, which implies the new method is promising. In addition the methods related to this family are uniformly discussed.

Keywords: conjugate gradient method, global convergence, line search, unconstrained optimization

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: M. Torres, A. Moulay, M. Zhuldybina, M. Rozel, N. D. Trinh, C. Bois

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Printed electronics are a fast-growing market as their applications cover a large range of industrial needs, their production cost is low, and the additive printing techniques consume less materials than subtractive manufacturing methods used in traditional electronics. With the growing demand for printed electronics, there are concerns about their harmful and irreversible contribution to the environment. Indeed, it is estimated that 80% of the environmental load of a product is determined by the choices made at the conception stage. Therefore, examination through a life cycle approach at the developing stage of a novel product is the best way to identify potential environmental issues and make proactive decisions. Life cycle analysis (LCA) is a comprehensive scientific method to assess the environmental impacts of a product in its different stages of life: extraction of raw materials, manufacture and distribution, use, and end-of-life. Impacts and major hotspots are identified and evaluated through a broad range of environmental impact categories of the ReCiPe (H) middle point method. At the conception stage, the LCA is a tool that provides an environmental point of view on the choice of materials and processes and weights-in on the balance between performance materials and eco-friendly materials. Using the life cycle approach, the current work aims to provide a cradle-to-grave life cycle assessment of a roll-to-roll hybrid printed smart label designed for the food cold chain. Furthermore, this presentation will present the environmental impact of metallic conductive inks, a comparison with promising conductive polymers, evaluation of energy vs. performance of industrial printing processes, a full assessment of the impact from the smart label applied on a cellulosic-based substrate during the recycling process and the possible recovery of precious metals and rare earth elements.

Keywords: Eco-design, label, life cycle assessment, printed electronics

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Authors: Muhammad Farooq Baig

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Objective: The purpose of this study was to compare results obtained using a single fecal specimen for O&P examination, direct immunofluorescence assay (DFA), and two conventional staining methods. Design: Hundred and fifty children fecal specimens were collected and examined by each method. The O&P and the DFA were used as the reference method. Setting: The study was performed at the laboratory in the Basic Medical Science Institute JPMC Karachi. Patients or Other Participants: The fecal specimens were collected from children with a suspected Giardia lamblia infection. Main Outcome Measures: The amount of agreement and disagreement between methods.1) Presence of giardiasis in our population. 2) The sensitivity and specificity of each method. Results: There was 45(30%) positive 105 (70%) negative on DFA, 41 (27.4%) positive 109 (72.6%) negative on iodine and 34 (22.6%) positive 116(77.4%) on saline method. The sensitivity and specificity of DFA in comparision to iodine were 92.2%, 92.7% respectively. The sensitivity and specificity of DFA in comparisoin to saline method were 91.2%, 87.9% respectively. The sensitivity of iodine method and saline method in compariosn to DFA were 82.2%, 68.8% respectively. There is mark diffrence in sensitivity of DFA to conventional method. Conclusion: The study supported findings of other investigators who concluded that DFA method have the greater sensitivity. The immunologic methods were more efficient and quicker than the conventional O&P method.

Keywords: direct immunofluorescence assay (DFA), ova and parasite (O&P), Giardia lamblia, children, medical science

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Authors: Shahindokht Bassiri-Jahromi, Mohammad Reza Pourshafie, Farzad Katiraee, Mannan Hajimahmoodi, Ehsan Mostafavi, Malihe Talebi

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Objective: Resistance of Candida species to antifungal agents has potentially serious implications for management of infections. Candida species are now fourth common organisms isolated from hospitalized patients. It is important to increase effective therapy. In the past decade, numerous reports of treatment failures were reported. Prevention and control of these infections will require new antimicrobial agents. Plant-derived antifungal have always been a source of novel therapeutics. The aim of this study was to investigate the antifungal effect of methanolic extract of pomegranate peel and pulp against Candida species. Material and Methods: Eight cultivars of Punica granatum L. were collected from Saveh Agricultural Investigation Center in Iran. Both pomegranate pulp and peel were dried and powdered separately. The dried powders were extracted by using a soxhlet extractor. The antifungal effect of methanolic extract of pomegranate peel and pulp were determined in vitro by minimum inhibitory concentration (MIC) against five standard species of (ATCC 10231), C. parapsilosis (ATCC 22019), C. tropicalis (ATCC 750), C. glabrata (PTCC 5297), and C. kroseii (PTCC 5295). Results: Maximum inhibitions of antifungal effect were attributed to peel extract pomegranate cultivar and Candida species. The most potential antifungal inhibition among 8 different cultivars observed by sour malas, sour white peel, and sour summer extracts respectively, against five Candida strains. The antifungal activity of pulp extracts against Candida species was approximately negative. Conclusion: The use of Punica granatum peel extract has been shown to possess antifungal activities. The phytochemistry and pharmacological actions of Punica granatum peel components suggest a wide range of clinical applications for the treatment and prevention of candidiasis.

Keywords: antifungal activity, Candida species, Punica granatum L., pharmacognosy

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Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words (BOVW), classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar (PolSAR)

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Authors: C. C. Lv, Y. L. Sun, D. W. Zuo

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Cemented carbide balls are usually implemented in industry under the environment of high speed, high temperature, corrosiveness and strong collisions. However, its application is limited due to high fabrication cost, processing efficiency and quality. A novel eccentric lapping method with two rotatable lapping plates was proposed in this paper. A mathematical model was constructed to analyze the influence of each design parameter on this lapping method. To validate this new lapping method, an orthogonal experiment was conducted with cemented carbide balls (YG6). The simulation model was verified and the optimal lapping parameters were derived. The results show that the surface roundness of the balls reaches to 0.65um from 2um in 1 hour using this lapping method. So, using this novel lapping method, it can effectively improve the machining precision and efficiency of cemented carbide balls.

Keywords: cemented carbide balls, eccentric lapping, high precision, lapping tracks, V-groove

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Authors: Young Hee Geum

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In this paper, we present the iterative method and determine the control parameters to converge cubically for solving nonlinear equations. In addition, we derive the asymptotic error constant.

Keywords: asymptotic error constant, iterative method, multiple root, root-finding, order of convergent

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Authors: P. Susheela, Mary Rosaline, R. Radha

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This research was designed to determine the bioactive compounds present in the nest samples of the mud dauber wasp, Sceliophron caementarium. Insects and insect-based products have been used for the treatment of various ailments from a very long time. It has been found that all over the world including the western societies and the indigenous populations, the usage of insect-based medicine plays an important role in various healing practices and magic rituals. Studies on the therapeutic usage of insects are negligible when compared to plants, the. In the present scenario, it is important to explore bioactive compounds from natural sources rather than depending on synthetic drugs that have adverse effects on human body. Keeping this in view, an attempt was made to analyze and identify bioactive components from the nest sample of the mud dauber wasp, Sceliophron caementarium. The nests of the mud dauber wasp, Sceliophron caementarium were collected from Coimbatore, Tamil Nadu, India. The nest sample was extracted with ethanol for 6-8 hours using Soxhlet apparatus. The final residue was obtained by filtering the extract through Whatman filter paper No.41. The GCMS analysis of the nest sample was performed using Perkin Elmer Elite - 5 capillary column. The resultant compounds were compared with the database of National Institute Standard and Technology (NIST), WILEY8, FAME. The GC-MS analysis of the concentrated ethanol extract revealed the presence of eight constituents like Methylene chloride, Eicosanoic acid, 1, 1’:3’, 1’’-Terphenyl, 5'-Phenyl, Di-N-Decylsulfone, 1, 2-Bis (Trimethylsilyl) Benzene, Androstane-11, 17-Dione, 3-[(Trimethylsilyl) Oxy]-, 17-[O-(Phenylmethyl) O. Most of the identified compounds were reported as having biological activities viz. anti-inflammatory, antibacterial and antifungal properties that can be of pharmaceutical importance and further study of these isolated compounds may prove their medicinal importance in future.

Keywords: Sceliophron caementarium, Gas chromatography-mass spectrometry, ethanol extract, bioactive compounds

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Authors: Hee-Jae Suh, Kyung-Su Kim, Min-Ji Kim, Yeon-Seong Jeong, Ok-Hwan Lee, Jae-Wook Shin, Hyang-Sook Chun, Chan Lee

Abstract:

Canthaxanthin is keto-carotenoid produced from beta-carotene and it has been approved to be used in many countries as a food coloring agent. Canthaxanthin has been analyzed using High Performance Liquid Chromatography (HPLC) system with various ways of pretreatment methods. Four official methods for verification of canthaxanthin at FSA (UK), AOAC (US), EFSA (EU) and MHLW (Japan) were compared to improve its analytical and the pretreatment method. The Linearity, the limit of detection (LOD), the limit of quantification (LOQ), the accuracy, the precision and the recovery ratio were determined from each method with modification in pretreatment method. All HPLC methods exhibited correlation coefficients of calibration curves for canthaxanthin as 0.9999. The analysis methods from FSA, AOAC, and MLHW showed the LOD of 0.395 ppm, 0.105 ppm, and 0.084 ppm, and the LOQ of 1.196 ppm, 0.318 ppm, 0.254 ppm, respectively. Among tested methods, HPLC method of MHLW with modification in pretreatments was finally selected for the analysis of canthaxanthin in lab, because it exhibited the resolution factor of 4.0 and the selectivity of 1.30. This analysis method showed a correlation coefficients value of 0.9999 and the lowest LOD and LOQ. Furthermore, the precision ratio was lower than 1 and the accuracy was almost 100%. The method presented the recovery ratio of 90-110% with modification in pretreatment method. The cross-validation of coefficient variation was 5 or less among tested three institutions in Korea.

Keywords: analytic method, canthaxanthin, food colorants, pretreatment method

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality.

Keywords: image dictionary creation, image super-resolution, LGE images, patch extraction

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

Abstract:

Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

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Authors: Misagh Ghobadi, Rich Crane, Karen Hudson-Edwards, Clemens Vinzenz Ullmann

Abstract:

Lithium is recognized as the critical energy metal of the 21st century, comparable in importance to coal in the 19th century and oil in the 20th century, often termed 'white gold'. Current global demand for lithium, estimated at 0.95-0.98 million metric tons (Mt) of lithium carbonate equivalent (LCE) annually in 2024, is projected to rise to 1.87 Mt by 2027 and 3.06 Mt by 2030. Despite anticipated short-term stability in supply and demand, meeting the forecasted 2030 demand will require the lithium industry to develop an additional capacity of 1.42 Mt of LCE annually, exceeding current planned and ongoing efforts. Brine resources constitute nearly 65% of global lithium reserves, underscoring the importance of exploring lithium recovery from underutilized sources, especially geothermal brines. However, conventional lithium extraction from brine deposits faces challenges due to its time-intensive process, low efficiency (30-50% lithium recovery), unsuitability for low lithium concentrations (<300 mg/l), and notable environmental impacts. Addressing these challenges, direct lithium extraction (DLE) methods have emerged as promising technologies capable of economically extracting lithium even from low-concentration brines (>50 mg/l) with high recovery rates (75-98%). However, most studies (70%) have predominantly focused on synthetic brines instead of native (natural/real), with limited application of these approaches in real-world case studies or industrial settings. This study aims to bridge this gap by investigating a geothermal brine sample collected from a real case study site in the UK. A Mn-based lithium-ion sieve (LIS) adsorbent was synthesized and employed to selectively extract lithium from the sample brine. Adsorbents with a Li:Mn molar ratio of 1:1 demonstrated superior lithium selectivity and adsorption capacity. Furthermore, the pristine Mn-based adsorbent was modified through transition metals doping, resulting in enhanced lithium selectivity and adsorption capacity. The modified adsorbent exhibited a higher separation factor for lithium over major co-existing cations such as Ca, Mg, Na, and K, with separation factors exceeding 200. The adsorption behaviour was well-described by the Langmuir model, indicating monolayer adsorption, and the kinetics followed a pseudo-second-order mechanism, suggesting chemisorption at the solid surface. Thermodynamically, negative ΔG° values and positive ΔH° and ΔS° values were observed, indicating the spontaneity and endothermic nature of the adsorption process.

Keywords: adsorption, critical minerals, DLE, geothermal brines, geochemistry, lithium, lithium-ion sieves

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Authors: Yukinori Fuse, Masato Kawaguchi

Abstract:

A quantitative risk assessment method was developed for fiber emissions from sprayed asbestos-containing materials (ACMs). In Japan, instead of being quantitative, these risk assessments have relied on the subjective judgment of skilled engineers, which may vary from one person to another. Therefore, this closed sampling method aims at avoiding any potential variability between assessments. This method was used to assess emissions from ACM sprayed in eleven buildings and the obtained results were compared with the subjective judgments of a skilled engineer. An approximate correlation tendency was found between both approaches. In spite of existing uncertainties, the closed sampling method is useful for public health protection. We firmly believe that this method may find application in the management and renovation decisions of buildings using friable and sprayed ACM.

Keywords: asbestos, renovation, risk assessment, maintenance

Procedia PDF Downloads 378