Search results for: soxhlet extraction

Authors: Deepak Khare, Radha Krishan, Bhaskar Nikam

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The present study deals with the results of the Ortho-rectified Cartosat-1 PAN (2.5 m resolution) satellite data analysis for the extraction of canal networks under the Eastern Ganga Canal (EGC) command. Based on the information derived through the remote sensing data, in terms of the number of canals, their physical status and hydraulic connectivity from the source, irrigation potential (IP) created in the command was assessed by comparing with planned/design canal-wise irrigation potentials. All the geospatial information generated in the study is organized in a geodatabase. The EGC project irrigates the command through one main canal, five branch canals, 36 distributaries and 186 minors. The study was conducted with the main objectives of inventory and mapping of irrigation infrastructure using geographic information system (GIS), remote sensing and field data. Likewise, the assessment of irrigation potential created using the mapped infrastructure was performed as on March 2017. Results revealed that the canals were not only pending but were also having gap/s, and hydraulically disconnected in each branch canal and also in minors of EGC. A total of 16622.3 ha of commands were left untouched with canal water just due to the presence of gaps in the EGC project. The sum of all the gaps present in minor canals was 11.92 km, while in distributary, it was 2.63 km. This is a very good scenario that balances IP can be achieved by working on the gaps present in minor canals. Filling the gaps in minor canals can bring most of the area under irrigation, especially the tail reaches command.

Keywords: canal command, GIS, hydraulic connectivity, irrigation potential

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Authors: Ngoc Minh Quynh Pham, Quan V. Vuong, Michael C. Bowyer, Christopher J. Scarlett

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Tuckeroo (Cupaniopsis anacardioides) is an Australian native plant and is grown in the coastal regions in New South Wales, Queensland and Northern Australia. Its fruits have been eaten by birds; however there is no information on phytochemical and antioxidant capacity of these fruits. This study aimed to determine the phenolic compounds (TPC), flavonoids (TFC), proanthocyanidins (TPro) and antioxidant capacity in the whole or different parts of tuckeroo fruit including skin, flesh and seed. Whole and partly tuckeroo fruits were collected and immediately freeze dried to constant weight and then ground to small particle sizes (<1mm mesh). Samples were extracted in 50% methanol using an ultrasonic bath set at temperature 40 °C for 30 minutes. TPC, TFC, TPro and antioxidant capacity were measured by spectrophotometric analysis. The results showed that the whole fruits contained 106.23 mg GAE/g of TPC, 67.67 mg CAE/g of TFC and 56.74 mg CAE/g of TPro. These fruits also possessed high antioxidant capacity (DPPH: 263.78 mg TroE/g, ABTS: 346.98 mg TroE/g, CUPRAC: 370.12 mg TroE/g and FRAP: 176.30 mg TroE/g), revealing that these fruits are rich source of antioxidants. The results also showed that distribution of the antioxidants was varied in different parts of the fruits. Skin had the highest levels of TPC, TFC, and TPro as well as antioxidant properties, followed by the seed and flesh had the lowest levels of phenolic compounds and antioxidant capacity. Of note, levels of phenolic compounds and antioxidant capacity of the skin were significantly higher than those of the whole fruits. Therefore, the skin of tuckeroo fruits is recommended as a starting material for extraction and purification of phenolic compounds as potential antioxidants for further utilisation in the food and pharmaceutical industries.

Keywords: antioxidant capacity, Cupaniopsis anacardioides, phenolic compounds, tuckeroo fruit

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Authors: Areej Ali Baeshen

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Allelopathy is a complex phenomenon that depends on the concentration of allelochemicals. It has both inhibitory and stimulatory effects, which may be decided by concentration of allelochemicals present in extraction. In the present study, the allelopathic effects of Eruca sativa, Mentha peperina, and Coriandrum sativum water extract prepared by grinding fresh leaves of the medicinal plants in distilled water and three concentrations were taken from the crude extracts (100%, 50% and 25% in addition to 0% as control), and were tested for their effects on seed germination and some growth parameters of Zea mays. The experiment was conducted in sterilized Petri dishes under the natural laboratory conditions at temperature of 25°C, with a 24 h, 48 h, 72 h, 96 h and 120 h time interval for seed germination and 24 h, 48 h and 72 h for radicle length. The effects of different concentrations of aqueous extract were compared to distilled water (control, 0%). In maize, germination percentage was suppressed when plants was treated with 100% extracts, however, 50% and 25% of M. peprina increased germination percentage by 4 times more than the control. Moreover, 50% and 25% extracts of M. peperina and 50% of C. sativum increased maize radicle and plumule length by 3 to 4 times that of the control. Results of plumule fresh and dry weights revealed that concentrations of water extracts of 100% and 50% M. peperina, E. sativa 100% and E. sativa 50% reported almost similar plumule fresh weight as in control plants. The most interesting finding is the reduction in harmful salts and TDS which could be a good factor in saline soils of Saudi Arabia.

Keywords: Zea mays, Eruca sativa, Mentha peperina, Coriandrum sativum, medicinal plants, allelochemicals, aqueous extract

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Authors: Chun-Wei Yeh, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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Reducing greenhouse gases or converting them into fuels and chemicals with added value is vital for the environment. Given the enhanced techniques for hydrocarbon extraction in this context, the catalytic conversion of methane to methanol is particularly intriguing for future applications as vehicle fuels and/or bulk chemicals. Metal-organic frameworks (MOFs) have received much attention recently for the oxidation of methane to methanol. In addition, biomimetic material, particulate methane monooxygenase (pMMO), has been reported to convert methane using copper oxide clusters as active sites. Inspired by these, in this study, we considered the well-known MIL-53(Al) MOF as support for copper oxide clusters (Cu2Ox, Cu3Ox) to investigate their reactivity towards methane oxidation using Density Functional Theory (DFT) calculations. The copper oxide clusters (Cu2O2, Cu3O2) are modeled by oxidizing copper clusters (Cu2, Cu3) with two oxidizers, O2 and N2O. The initial C-H bond activation barriers on Cu2O2/MIL-53(Al) and Cu3O2/MIL-53(Al) catalysts are 0.70 eV and 0.64 eV, respectively, and are the rate-determining steps in the overall methane conversion to methanol reactions. The desorption energy of the methanol over the Cu2O/MIL-53(Al) and Cu3O/MIL-53(Al) is 0.71eV and 0.75 eV, respectively. Furthermore, to explore the prospect of catalyst reusability, we considered the different oxidants and proposed the different reaction pathways for completing the reaction cycle and regenerating the active copper oxide clusters. To know the reason for the difference between bi-copper and tri-cooper systems, we also did an electronic analysis. Finally, we calculate the Microkinetic Simulation. The result shows that the reaction can happen at room temperature.

Keywords: DFT study, copper oxide cluster, MOFs, methane conversion

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Authors: Zhifei Hu, Feng Xia

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In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.

Keywords: graph attention network, knowledge graph, recommendation, information propagation

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Authors: Tigist Girma Kidane, Yalew Dessalegn Asfaw

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Abstract: The current investigation aims to measure the longitudinal and transversal three-point bending tests of bamboo fibres polypropylene composites (BFPPCs) for the application of the automobile industry. Research has not been done on the properties of Ethiopian bamboo fibres for the utilization of composite development. The samples of bamboo plants have been harvested in 3–groups of age, 2–harvesting seasons, and 3–regions of bamboo species. Roll milling machine used for the extraction of bamboo fibres which has been developed by the authors. Chemical constituents measured using gravimetric methods. Unidirectional bamboo fibres prepreg has been produced using PP and hot press machine, then BFPPCs were produced using 6 layers of prepregs at automatic hot press machine. Age, harvesting month, and bamboo species have a statistically significant effect on the longitudinal and transverse flexural strength (FS), modulus of elasticity (MOE), and failure strain at α = 0.05 as evaluated by one-way ANOVA. 2–yrs old of BFPPCs have the highest FS and MOE, whereas November has the highest value of flexural properties. The highest to the lowest FS and MOE of BFPPCs has measured in Injibara, Mekaneselam, and Kombolcha, respectively. The transverse 3-point bending test has a lower FS and MOE compared to the longitudinal direction. The chemical constituents of Injibara, Mekaneselam, and Kombolcha have the highest to the lowest, respectively. 2-years old of bamboo fibres has the highest chemical constituent. The chemical constituents improved the flexural properties. Bamboo fibres in Ethiopia can be relevant for composite development, which has been applied in the area of requiring higher flexural properties.

Keywords: age, bamboo species, flexural properties, harvesting season, polypropylene

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Authors: Hongxin Zhao, Shibing Yang, Bingming Yi, Yi Ning

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Background: A few studies have found evidence that exposure to endogenous or postmenopausal exogenous estrogens may be associated with a lower prevalence of age-related macular degeneration (AMD), but dispute over this association is ongoing due to inconsistent results reported by different studies. Objectives: To conduct a systematic review and meta-analysis to investigate the association between hormone replacement therapy (HRT) use and AMD. Methods: Relevant studies that assessed the association between HRT and AMD were searched through four databases (PubMed, Web of Science, Cochrane Library, EMBASE) and reference lists of retrieved studies. Study selection, data extraction and quality assessment were conducted by three independent reviewers. The fixed-effect meta-analyses were performed to estimate the association between HRT ever-use and AMD by pooling risk ratio (RR) or odds ratio (OR) across studies. Results: The review identified 2 prospective and 7 cross-sectional studies with 93992 female participants that reported an estimate of the association between HRT ever-use and presence of early AMD or late AMD. Meta-analyses showed that there were no statistically significant associations between HRT ever-use and early AMD (pooled RR for cohort studies was 1.04, 95% CI 0.86 - 1.24; pooled OR for cross-sectional studies was 0.91, 95% CI 0.82 - 1.01). The pooled results from cross-sectional studies also showed no statistically significant association between HRT ever-use and late AMD (OR 1.01; 95% CI 0.89 - 1.15). Conclusions: The pooled effects from observational studies published to date indicate that HRT use is associated with neither early nor late AMD. Exposure to HRT may not protect women from developing AMD.

Keywords: hormone replacement therapy, age-related macular degeneration, meta-analysis, systematic review

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Authors: W. Loongyai, N. Saengsawang, W. Danvilai, C. Kridtayopas, P. Sopannarath, C. Bunchasak

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Betong chicken is a slow growing and a lean strain of chicken, while the rapid growth of broiler is accompanied by increased fat. We investigated the growth performance, fat accumulations, lipid serum biochemical levels and lipoprotein lipase (LPL) gene expression of female Betong (KU line) at the age of 4 and 6 weeks. A total of 80 female Betong chickens (KU line) and 80 female broiler chickens were reared under open system (each group had 4 replicates of 20 chicks per pen). The results showed that feed intake and average daily gain (ADG) of broiler chicken were significantly higher than Betong (KU line) (P < 0.01), while feed conversion ratio (FCR) of Betong (KU line) at week 6 were significantly lower than broiler chicken (P < 0.01) at 6 weeks. At 4 and 6 weeks, two birds per replicate were randomly selected and slaughtered. Carcass weight did not significantly differ between treatments; the percentage of abdominal fat and subcutaneous fat yield was higher in the broiler (P < 0.01) at 4 and 6 week. Total cholesterol and LDL level of broiler were higher than Betong (KU line) at 4 and 6 weeks (P < 0.05). Abdominal fat samples were collected for total RNA extraction. The cDNA was amplified using primers specific for LPL gene expression and analysed using real-time PCR. The results showed that the expression of LPL gene was not different when compared between Betong (KU line) and broiler chickens at the age of 4 and 6 weeks (P > 0.05). Our results indicated that broiler chickens had high growth rate and fat accumulation when compared with Betong (KU line) chickens, whereas LPL gene expression did not differ between breeds.

Keywords: lipoprotein lipase gene, Betong (KU line), broiler, abdominal fat, gene expression

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Authors: Fatemeh Saadat Ghareh Bagh, Srimanta Ray, Jerald Lalman

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Lignin, the largest inventory of organic carbon with a high caloric energy value is a major component in woody and non-woody biomass. In pulping mills, a large amount of the lignin is burned for energy. At the same time, the phenolic structure of lignin enables it to be converted to value-added compounds.This study has focused on extracting lignin from black liquor using deep eutectic solvents (DESs). Therefore, three choline chloride (ChCl)-DESs paired with lactic acid (LA) (1:11), oxalic acid.2H₂O (OX) (1:4), and malic acid (MA) (1:3) were synthesized at 90oC and atmospheric pressure. The kinetics of lignin recovery from black liquor using DES was investigated at three moderate temperatures (338, 353, and 368 K) at time intervals from 30 to 210 min. The extracted lignin (acid soluble lignin plus Klason lignin) was characterized by Fourier transform infrared spectroscopy (FTIR). The FTIR studies included comparing the extracted lignin with a model Kraft lignin. The extracted lignin was characterized spectrophotometrically to determine the acid soluble lignin (ASL) [TAPPI UM 250] fraction and Klason lignin was determined gravimetrically using TAPPI T 222 om02. The lignin extraction reaction using DESs was modeled by first-order reaction kinetics and the activation energy of the process was determined. The ChCl:LA-DES recovered lignin was 79.7±2.1% at 368K and a DES:BL ratio of 4:1 (v/v). The quantity of lignin extracted for the control solvent, [emim][OAc], was 77.5+2.2%. The activation energy measured for the LA-DES system was 22.7 KJ mol⁻¹, while the activation energy for the OX-DES and MA-DES systems were 7.16 KJ·mol⁻¹ and 8.66 KJ·mol⁻¹ when the total lignin recovery was 75.4 ±0.9% and 62.4 ±1.4, % respectively.

Keywords: black liquor, deep eutectic solvents, kinetics, lignin

Procedia PDF Downloads 148

Authors: J. C. Akan, F. I. Abdulrahman, Z. M. Chellube

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The aim of this study was to determine the levels of some organochlorine (o, p-DDE, p,p’-DDD, o,p’-DDD, p,p’-DDT, p,p’-DDT, α-BHC, γ-BHC, lindane, Endosulfan sulphate, dieldrin and aldrin and organophosphorus (Dichlorvos, Diazinon, Chlorpyrifos, fenitrothion and Fenitrothion) pesticide residues in the gills, liver, stomach, kidney and flesh of four fish species (Tilapia zilli, Clarias anguillaris Hetrotis niloticus and Oreochronmis niloticus) between the periods of September 2010 to October, 2011. Samples were collected from Kwantan turare in Lake Chad, Baga, Borno State, Nigeria. Extraction of the fish samples and de-fattening of the fish sample extracts were performed using standard procedures. Analysis of the fish samples for pesticide residues were carried out using Shimadzu GC/MS (GC – 17A), equipped with fluorescence detector. Large differences in the levels of pesticide residues were observed between tissues within each fish. The concentrations of all the organophosphorus pesticides were higher in the organs of Oreochronmis niloticus, while Hetrotis niloticus shows the lowest. For organochlorine pesticides, the organs of Tilapia zilli showed the highest concentrations, while Hetrotis niloticus shows the lowest. The highest pesticide concentrations were observed in gills and liver tissues of all the species of fish study, while the lowest concentrations were observed in flesh. Based on the above results, it can therefore be concluded that the concentrations of pesticide in the four fish species study did exceed the permissible limits set by FAO and FEPA.

Keywords: organochlorine, organophosphorus, pesticides, accumulation, fish, lake chad

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Authors: Ogbonnaya O. Iroanya, Samson T. Fakorede, Osamudiamen J. Edosa, Hadiat A. Azeez

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The human mitochondrial DNA (mtDNA) is about 17 kbp circular DNA fragments found within the mitochondria together with smaller fragments of 1200 bp known as the control region. Knowledge of variation within populations has been employed in forensic and molecular anthropology studies. The study was aimed at investigating the polymorphic nature of the two hypervariable segments (HVS) of the mtDNA, i.e., HVS1 and HVS2, and to determine the haplogroup distribution among individuals resident in Lagos, Southwestern Nigeria. Peripheral blood samples were obtained from sixty individuals who are not related maternally, followed by DNA extraction and amplification of the extracted DNA using primers specific for the regions under investigation. DNA amplicons were sequenced, and sequenced data were aligned and compared to the revised Cambridge Reference Sequence (rCRS) GenBank Accession number: NC_012920.1) using BioEdit software. Results obtained showed 61 and 52 polymorphic nucleotide positions for HVS1 and HVS2, respectively. While a total of three indels mutation were recorded for HVS1, there were seven for HVS2. Also, transition mutations predominate nucleotide change observed in the study. Genetic diversity (GD) values for HVS1 and HVS2 were estimated to be 84.21 and 90.4%, respectively, while random match probability was 0.17% for HVS1 and 0.89% for HVS2. The study also revealed mixed haplogroups specific to the African (L1-L3) and the Eurasians (U and H) lineages. New polymorphic sites obtained from the study are promising for human identification purposes.

Keywords: hypervariable region, indels, mitochondrial DNA, polymorphism, random match probability

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Junjie Wu, Hongjuan Hou, Eric Hu, Yongping Yang

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Solar aided power generation (SAPG) technology has been proven as an efficient way to make use of solar energy for power generation purpose. In an SAPG plant, a solar field consisting of parabolic solar collectors is normally used to supply the solar heat in order to displace the high pressure/temperature extraction steam. To understand the performance of such a SAPG plant, a new simulation model was developed by the authors recently, in which the boiler was treated, as a series of heat exchangers unlike other previous models. Through the simulations using the new model, it was found the outlet properties of reheated steam, e.g. temperature, would decrease due to the introduction of the solar heat. The changes make the (lower stage) turbines work under off-design condition. As a result, the whole plant’s performance may not be optimal. In this paper, the second solar filed was proposed to increase the inlet temperature of steam to be reheated, in order to bring the outlet temperature of reheated steam back to the designed condition. A 600MW SAPG plant was simulated as a case study using the new model to understand the impact of the second solar field on the plant performance. It was found in the study, the 2nd solar field would improve the plant’s performance in terms of cycle efficiency and solar-to-electricity efficiency by 1.91% and 6.01%. The solar-generated electricity produced by per aperture area under the design condition was 187.96W/m2, which was 26.14% higher than the previous design.

Keywords: solar-aided power generation system, off-design performance, coal-saving performance, boiler modelling, integration schemes

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Authors: N. H. Harun, A. S. Abdul Nasir, M. Y. Mashor, R. Hassan

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Leukaemia is a blood cancer disease that contributes to the increment of mortality rate in Malaysia each year. There are two main categories for leukaemia, which are acute and chronic leukaemia. The production and development of acute leukaemia cells occurs rapidly and uncontrollable. Therefore, if the identification of acute leukaemia cells could be done fast and effectively, proper treatment and medicine could be delivered. Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image. In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively. Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. Based on the good sensitivity value that has been obtained, the results indicate that moving k-means clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. Hence, indicating that the resultant images could be helpful to haematologists for further analysis of acute leukaemia.

Keywords: acute leukaemia images, clustering algorithms, image segmentation, moving k-means

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

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Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

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Authors: Zohreh Fallah, Edward P. L. Roberts

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One of the big challenges for produced water treatment is removing oil from water in the form of emulsified droplets which are not easily separated. An attractive approach is adsorption, as it is a simple and effective process. However, adsorbents must be regenerated in order to make the process cost effective. Several sorbents have been tested for treating oily wastewater. However, some issues such as high energy consumption for activated carbon thermal regeneration have been reported. Due to their significant electrical conductivity, Graphite Intercalation Compounds (GIC) were found to be suitable to be regenerated electrochemically. They are non-porous materials with low surface area and fast adsorptive capacity which are useful for removal of low concentration of organics. An innovative adsorption/regeneration process has been developed at the University of Manchester in which adsorption of organics are done by using a patented GIC adsorbent coupled with subsequent electrochemical regeneration. The oxidation of adsorbed organics enables 100% regeneration so that the adsorbent can be reused over multiple adsorption cycles. GIC adsorbents are capable of removing a wide range of organics and pollutants; however, no comparable report is available for removal of emulsified oil in produced water using abovementioned process. In this study the performance of this technology for the removal of emulsified oil in wastewater was evaluated. Batch experiments were carried out to determine the adsorption kinetics and equilibrium isotherm for both real produced water and model emulsions. The amount of oil in wastewater was measured by using the toluene extraction/fluorescence analysis before and after adsorption and electrochemical regeneration cycles. It was found that oil in water emulsion could be successfully treated by the treatment process and More than 70% of oil was removed.

Keywords: adsorption, electrochemical regeneration, emulsified oil, produced water

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Authors: Kenia Martínez, Geniel Talavera, Juan Alonso

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Moringa oleifera is a plant containing many nutrients that are mostly concentrated within the leaves. Commonly, the separation process of these nutrients involves solid-liquid extraction followed by evaporation and drying to obtain a concentrated extract, which is rich in proteins, vitamins, carbohydrates, and other essential nutrients that can be used in the food industry. In this work, three drying methods were used, which involved very different temperature and pressure conditions, to evaluate the effect of each method on the vitamin C content and the antioxidant efficiency of the extracts. Solid-liquid extractions of Moringa leaf (LE) were carried out by employing an ethanol solution (35% v/v) at 50 °C for 2 hours. The resulting extracts were then dried i) in a convective oven (CO) at 100 °C and at an atmospheric pressure of 750 mbar for 8 hours, ii) in a vacuum evaporator (VE) at 50 °C and at 300 mbar for 2 hours, and iii) in a freeze-drier (FD) at -40 °C and at 0.050 mbar for 36 hours. The antioxidant capacity (EC₅₀, mg solids/g DPPH) of the dry solids was calculated by the free radical inhibition method employing DPPH˙ at 517 nm, resulting in a value of 2902.5 ± 14.8 for LE, 3433.1 ± 85.2 for FD, 3980.1 ± 37.2 for VE, and 8123.5 ± 263.3 for CO. The calculated antioxidant efficiency (AE, g DPPH/(mg solids·min)) was 2.920 × 10^-5 for LE, 2.884 × 10^-5 for FD, 2.512 × 10^-5 for VE, and 1.009 × 10^-5 for CO. Further, the content of vitamin C (mg/L) determined by HPLC was 59.0 ± 0.3 for LE, 49.7 ± 0.6 for FD, 45.0 ± 0.4 for VE, and 23.6 ± 0.7 for CO. The results indicate that the convective drying preserves vitamin C and antioxidant efficiency to 40% and 34% of the initial value, respectively, while vacuum drying to 76% and 86%, and freeze-drying to 84% and 98%, respectively.

Keywords: antioxidant efficiency, convective drying, freeze-drying, Moringa oleifera, vacuum drying, vitamin C content

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: Muhammad S. Sajid, A. Iqbal, A. Kausar, M. Jawad-ul-Hassan, Z. Iqbal, Hafiz M. Rizwan, M. Saqib

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Among the ixodid ticks, species of genus Hyalomma are of prime importance as they can survive in harsh conditions better than those of other species. Similarly, among various tick-borne pathogens, Theileria (T.) annulata, the causative agent of tropical theileriosis in large ruminants, is responsible for reduced productivity and ultimately substantial economic losses due to morbidity and mortality. The present study was planned to screening of vector ticks through molecular techniques for determination of tick-borne theileriosis in district Toba Tek Singh (T. T. Singh), Punjab, Pakistan. For this purpose, among the collected ticks (n = 2252) from livestock and their microclimate, Hyalomma spp. were subjected to dissection for procurement of salivary glands (SGs) and formation of pool (averaged 8 acini in each pool). Each pool of acini was used for DNA extraction, quantification and primer-specific amplification of 18S rRNA of Theileria (T.) annulata. The amplicons were electrophoresed using 1.8% agarose gel following by imaging to identify the band specific for T. annulata. For confirmation, the positive amplicons were subjected to sequencing, BLAST analysis and homology search using NCBI software. The number of Theileria-infected acini was significantly higher (P < 0.05) in female ticks vs male ticks, infesting ticks vs questing ticks and riverine-collected vs non-riverine collected. The data provides first attempt to quantify the vectoral capacity of ixodid ticks in Pakistan for T. annulata which can be helpful in estimation of risk analysis of theileriosis to the domestic livestock population of the country.

Keywords: Hyalomma anatolicum, ixodids, PCR, Theileria annulata

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Authors: Nour Daoud

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Patriarchy continues to thrive in Jordan where male-controlled values are still entrenched in a society that is suffering from upsetting percentages of Gender-based Violence (GBV). This paper is a systematic review of the literature with an attempt to evaluate and interpret all available research evidence relevant to determining the extent to which patriarchy contributes to the occurrence, re-occurrence, and continuation of GBV in Jordan. Twenty-one (21) full-text articles were selected for the in-depth review due to meeting the established criteria for inclusion. 81 percent of articles included primary data while 19 percent included secondary data. Analysis of data was based on a specific extraction form that was developed using the ‘Excel’ to respond to the main goal of the paper. Interpretation of data was in light of the theorization of different feminism schools on the relationship between patriarchy and gender-based violence. Findings show that 33 percent of the selected articles affirm that the patriarchal standpoint best explains the role of patriarchy in the incidence of gender-based violence in Jordan under its three main themes (Honor-based Violence, Intimate Partner Violence and Street Harassment). Apart from the limited number of articles that were found debating this argument and the low percentage of articles that acknowledged the role of patriarchy in the incidence of gender-based violence in Jordan, this paper breaks the ice to implement future empirical studies on this subject. Also, it is an invitation for all Jordanian women to unite their efforts in order to eradicate all forms of victimization against them.

Keywords: honor-based violence, intimate partner violence, middle-east, street harassment

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: Carolyn Whyte, Tina Halai, Sonita Koshal

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Aim: There are many methods available to assess the potential difficulty of third molar surgery. This study investigated various factors to assess whether they had a bearing on the difficulties encountered. Study design: A retrospective study was completed of 62 single mandibular third molar teeth removed under day case general anaesthesia between May 2016 and August 2016 by 3 consultant oral surgeons. Method: Data collection was by examining the OPG radiographs of each tooth and recording the necessary data. This was depth of impaction, angulation, bony impaction, point of application in relation to second molar, root morphology, Pell and Gregory classification and Winters Lines. This was completed by one assessor and verified by another. Information on medical history, anxiety, ethnicity and age were recorded. Case notes and surgical entries were examined for any difficulties encountered. Results: There were 5 cases which encountered surgical difficulties which included fracture of root apices (3) which were left in situ, prolonged bleeding (1) and post-operative numbness >6 months(1). Four of the 5 cases had Pell and Gregory classification as (B) where the occlusal plane of the impacted tooth is between the occlusal plane and the cervical line of the adjacent tooth. 80% of cases had the point of application as either coronal or apical one third (1/3) in relation to the second molar. However, there was variability in all other aspects of assessment in predicting difficulty of removal. Conclusions: Of the cases which encountered difficulties they all had at least one predictor of potential complexity but these varied case by case.

Keywords: impaction, mandibular third molar, radiographic assessment, surgical removal

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

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Authors: Agustinus Rudatyo Himamunanto, Anastasia Rita Widiarti

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Transliteration using Javanese manuscripts is one of methods to preserve and legate the wealth of literature in the past for the present generation in Indonesia. The transliteration manual process commonly requires philologists and takes a relatively long time. The automatic transliteration process is expected to shorten the time so as to help the works of philologists. The preprocessing and segmentation stage firstly done is used to manage the document images, thus obtaining image script units that will compile input document images free from noise and have the similarity in properties in the thickness, size, and slope. The next stage of characteristic extraction is used to find unique characteristics that will distinguish each Javanese script image. One of characteristics that is used in this research is the number of black pixels in each image units. Each image of Java scripts contained in the data training will undergo the same process similar to the input characters. The system testing was performed with the data of the book Hamong Tani. The book Hamong Tani was selected due to its content, age and number of pages. Those were considered sufficient as a model experimental input. Based on the results of random page automatic transliteration process testing, it was determined that the maximum percentage correctness obtained was 81.53%. The percentage of success was obtained in 32x32 pixel input image size with the 5x5 image window. With regard to the results, it can be concluded that the automatic transliteration model offered is relatively good.

Keywords: Javanese script, character recognition, statistical, automatic transliteration

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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Authors: R. F. Vieira, S. A. Figueiredo, O. M. Freitas, V. F. Domingues, C. Delerue-Matos

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The presence of sulphur compounds like hydrogen sulphide and mercaptans is one of the reasons for waste-water treatment and waste management being associated with odour emissions. In this context having a quantifying method for these compounds helps in the optimization of treatment with the goal of their elimination, namely biofiltration processes. The aim of this study was the development of a method for quantification of odorous gases in waste treatment plants air samples. A method based on head space solid phase microextraction (HS-SPME) coupled with gas chromatography - flame photometric detector (GC-FPD) was used to analyse H2S and Metil Mercaptan (MM). The extraction was carried out with a 75-μm Carboxen-polydimethylsiloxane fiber coating at 22 ºC for 20 min, and analysed by a GC 2010 Plus A from Shimadzu with a sulphur filter detector: splitless mode (0.3 min), the column temperature program was from 60 ºC, increased by 15 ºC/min to 100 ºC (2 min). The injector temperature was held at 250 ºC, and the detector at 260 ºC. For calibration curve a gas diluter equipment (digital Hovagas G2 - Multi Component Gas Mixer) was used to do the standards. This unit had two input connections, one for a stream of the dilute gas and another for a stream of nitrogen and an output connected to a glass bulb. A 40 ppm H2S and a 50 ppm MM cylinders were used. The equipment was programmed to the selected concentration, and it automatically carried out the dilution to the glass bulb. The mixture was left flowing through the glass bulb for 5 min and then the extremities were closed. This method allowed the calibration between 1-20 ppm for H2S and 0.02-0.1 ppm and 1-3.5 ppm for MM. Several quantifications of air samples from inlet and outlet of a biofilter operating in a waste management facility in the north of Portugal allowed the evaluation the biofilters performance.

Keywords: biofiltration, hydrogen sulphide, mercaptans, quantification

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Authors: Aliasghar Golmohammadian, Sona Rostampour Yasouri

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One of the most important intestinal pathogenic strains is E. coli O₁₅₇:H₇. This pathogenic bacterium is transmitted to humans through water and food. E. coli O₁₅₇:H₇ is the main cause of Hemorrhagic colitis (HC), Hemolytic Uremic Syndrome (HUS), Thrombotic Thrombocytopenic Purpura (TTP) and in some cases death. Since E. coli O₁₅₇:H₇ can be transmitted through the consumption of different foods, including vegetables, agricultural products, and fresh dairy products, this study aims to identify and isolate E. coli O₁₅₇:H₇ from wastewater by PCR technique. One hundred twenty samples of water and wastewater were collected by Falcom Sterile from Shahrood and Neka cities. The samples were checked for colony formation after appropriate centrifugation and cultivation in the specific medium of Sorbitol MacConkey Agar (SMAC) and other diagnostic media of E. coli O₁₅₇:H₇. Also, the plates were observed macroscopically and microscopically. Then, the necessary phenotypic tests were performed on the colonies, and finally, after DNA extraction, the PCR technique was performed with specific primers related to rfbE and stx2 genes. The number of 5 samples (6%) out of all the samples examined were determined positive by PCR technique with observing the bands related to the mentioned genes on the agarose gel electrophoresis. PCR is a fast and accurate method to identify the bacteria E. coli O₁₅₇:H₇. Considering that E. coli bacteria is a resistant bacteria and survives in water and food for weeks and months, the PCR technique can provide the possibility of quick detection of contaminated water. Moreover, it helps people in the community control and prevent the transfer of bacteria to healthy and underground water and agricultural and even dairy products.

Keywords: E. coli O₁₅₇:H₇, PCR, water, wastewater

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