Search results for: petroleum spirit extract

Authors: Ikele Chika Bright, Mgbenka Bernard Obialo, Ikele Chioma Faith

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Icthyophthiriasis is a prevalent protozoan (ectoparasite) mostly affecting cultured and aquarium fishes. The majority of the chemotherapeutants lack efficacy for completely eliminating Ich parasite without affecting the environment and they are not safe for human health. The present work is focused on the evaluating different immersion treatments of African catfish (Clarias gariepinus) infected with ichthyophthiriasis and treated with a non-chemical and environmental friendly parasiticides Moringa oleifera. A total number of 800 apparently healthy parasites free (examined) post juvenile catfish were obtained from a reputable farm, disinfected with potassium permanganate in a quarantine tank to remove any possible external parasites. The fish were further challenged with approximately 44,000 infective stages of theronts which were obtained through serial passages by cohabitation. Seven groups (A-G) of post Juvenile were used for the experiment which was carried out into three stages; Dips (60minutes), short term treatment (24-96h) and prolong bath treatment (0-15 days). The concentrations selected were dependent on the outcome of the LC50 of the plant material from which dose-dependent factors were used to select various concentrations of the treatment. In Dips treatment, group D-G were treated with 1,500mg/L, 2500mg/L., 3500mg/L and 4500mg/L, short-term treatment was treated with 150mg/L, 250mg/L, 350mg/L and 450mg/L and prolong bath was treated with 15mg/L, 25mg/L, 35mg/L and 45mg/L of the plant extract whereas group A, B and C were normal control, Ich- infested not treated and Ich- infested treated with standard drug (Acriflavin), respectively. The various types of treatment applied with corresponding concentrations showed almost complete elimination of the adult parasites (trophonts) both in the gills and the body smear, thereby making M. oleifera a potential parasiticides. There were serious pathological alterations in the skin and gills which are usually the main point for Ich parasites invasion but no significant morphological characteristics was noted among the treated groups subjected to different immersion treatment patterns. Epitheliocystis, aneurysm, oedema, hemorrhage, and localization of the adult parasite in the gills were the overall common observations made in the gills whereas degeneration of muscle fibre, dermatitis, hemorrhage, oedema, abscess formation and keratinisation were observed in the skin. However, there are no pathological changes in the control group. Moreover, biochemical parameters such as urea, creatinine, albumin., globulin, total protein, ALT, AST), blood chemistry (sodium, chloride, potassium, bicarbonate), antioxidants (CAT, SOD, GPx, LPO), enzymatic activities (myeloperoxidase, thioreadoxin reductase), Inflammatory response (C-reactive protein), Stress markers (lactate dehydrogenase), heamatological parameters (RBC, PCV, WBC, HB and differential count), lipid profile (total cholesterol, tryglycerides , high density lipoprotein and low density lipoprotein) all showed various significant (P<0.05) and no significant (P>0.05) responses among the Ich-infested fish treated under three immersion treatments. It is suggested that M. oleifera may serve as an alternatives to chemotherapeutants for control of Ichthyophthiriasis in African catfish Clarias gariepinus.

Keywords: Icthyophthirius multifilis, immersion treatment, pathophysiology, African catfish

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Authors: Zahra Sokar, Sara Oufquir, Brahim Eddafali, Abderrahman Chait

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Fenugreek is one of the oldest plants used in traditional herbal medicine. Several studies have demonstrated the anticancer effects of seeds by inhibiting the proliferation, angiogenesis, invasion and metastasis of various cancers. While there is plenty of research demonstrating the antineoplastic effects of dormant seeds, little is known about the potential of sprouts in fighting cancer. Therefore, we propose to study the chemoprotective effect of germinating fenugreek seeds on keratoacanthoma skin cancer induced by cutaneous exposure to DMA/Croton oil in mice. The results obtained show that oral administration of 250 and 500 mg/kg aqueous sprout seed extract reduces the incidence, rate, volume, and tumor weight in a very significant manner. Histological examination revealed that mice treated with 250 mg/kg showed strong inhibition of squamous cell carcinoma formation with thickening of the epithelial layer and mild acanthosis and hyperkeratosis. A dose of 500 mg/kg prevented invasion and the occurrence of hyperkeratosis. Fenugreek sprouts appear to be a promising natural product for preventing keratoacanthoma skin cancer. Nevertheless, further studies in the same field need to be developed to evaluate the antineoplastic potential of germinated seeds.

Keywords: anticancer, fenugreek, keratoacanthoma, sprouts

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Authors: Boris M. Popović, Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović

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Green solvents are environmentally friendly and greatly improve the sustainability of chemical processes. There is a growing interest in the green extraction of polyphenols from fruits. In this study, we consider three Natural Deep Eutectic Solvents (NADES) systems based on choline chloride as a hydrogen bond acceptor and malic acid, urea, and fructose as hydrogen bond donors. NADES systems were prepared by heating and stirring, ultrasound, and microwave (MW) methods. Sour cherry pomace was used as a natural source of polyphenols. Polyphenol extraction from cherry pomace was performed by ultrasound-assisted extraction and microwave-assisted extraction and compared with conventional heat and stirring method extraction. It was found that MW-assisted preparation of NADES was the fastest, requiring less than 30 s. Also, MW extraction of polyphenols was the most rapid, with less than 5 min necessary for the extract preparation. All three NADES systems were highly efficient for anthocyanin extraction, but the most efficient was the system with malic acid as a hydrogen bond donor (yield of anthocyanin content was enhanced by 62.33% after MW extraction with NADES compared with the conventional solvent).

Keywords: anthocyanins, green extraction, NADES, polyphenols

Procedia PDF Downloads 86

Authors: Mohamed I. D. Helal, Mohamed M. El-Mogy, Hassan A. Khater, Muhammad A. Fathy, Fatma E. Ibrahim, Yuncong C. Li, Zhaohui Tong, Karima F. Abdelgawad

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Minimizing the consumption of agrochemicals, particularly nitrogen, is the ultimate goal for achieving sustainable agricultural production with low cost and high economic and environmental returns. The use of biopolymers instead of petroleum-based synthetic polymers for CRFs can significantly improve the sustainability of crop production since biopolymers are biodegradable and not harmful to soil quality. Lignin is one of the most abundant biopolymers that naturally exist. In this study, controlled-release fertilizers were developed using a biobased nanocomposite of lignin and bentonite clay mineral as a coating material for urea to increase nitrogen use efficiency. Five types of controlled-release urea (CRU) were prepared using two ratios of modified bentonite as well as techniques. The efficiency of the five controlled-release nano-urea (CRU) fertilizers in improving the growth of tomato plants was studied under field conditions. The CRU was applied to the tomato plants at three N levels representing 100, 50, and 25% of the recommended dose of conventional urea. The results showed that all CRU treatments at the three N levels significantly enhanced plant growth parameters, including plant height, number of leaves, fresh weight, and dry weight, compared to the control. Additionally, most CRU fertilizers increased total yield and fruit characteristics (weight, length, and diameter) compared to the control. Additionally, marketable yield was improved by CRU fertilizers. Fruit firmness and acidity of CRU treatments at 25 and 50% N levels were much higher than both the 100% CRU treatment and the control. The vitamin C values of all CRU treatments were lower than the control. Nitrogen uptake efficiencies (NUpE) of CRU treatments were 47–88%, which is significantly higher than that of the control (33%). In conclusion, all CRU treatments at an N level of 25% of the recommended dose showed better plant growth, yield, and fruit quality of tomatoes than the conventional fertilizer.

Keywords: nitrogen use efficiency, quality, urea, nano particles, ecofriendly

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Authors: M. A. Ashour

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As it is known Egypt is one of the countries having oldest sugarcane industry, which goes back to the year 710 AD. Cane plantations are the main agricultural product in five governorates in Upper Egypt (El-Menia, Sohag, Qena, Luxor, and Aswan), producing not less than 16 million tons a year. Eight factories (Abou-korkas, Gena, Nagaa-Hamadi, Deshna, Kous, Armant, Edfuo, and Komombo), located in such upper Egypt governorates generates huge amount of wastes during the manufacturing stage, the so called bagasse which is the fibrous, and cellulosic materials remaining after the era of the sugarcane and the juice extraction, presents about 30% of such wastes. The amount of bagasse generated yearly through the manufacturing stage of the above mentioned 8 factories is approximately about 2.8 million tons, getting red safely of such huge amount, presents a serious environmental problem. Storage of that material openly in the so hot climate in upper Egypt, may cause its self-ignition under air temperature reaches 50 degrees centigrade in summer, due to the remained residual content of sugar. At the same time preparing places for safely storage for such amount is very expensive with respect to the valueless of it. So the best way for getting rid of bagasse is converting it into an added value environmentally friendly material, especially till now the utilization of it is so limited. Since oil pollution became a serious concern, the issue of environmental cleaning arises. With the structure of sugarcane bagasse, which contains fiber and high content of carbon, it can be an adsorbent to adsorb the oil contamination from the water. The present study is a trail to introduce a new material for the purification of water systems to score two goals at once, the first is getting rid of that harmful waste safely, the second is converting it to a commercial valuable material for cleaning, and purifying the water from oil spills, and petroleum pollution. Introduced the new material proved very good performance, and higher efficiency than other similar materials available in the local market, in both closed and open systems. The introduced modified material can absorb 10 times its weight of oil, while don't absorb any water.

Keywords: environment, water resources, agricultural wastes, oil pollution control, sugarcane

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Authors: Belayneh Matebie, Michael Melese

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The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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Authors: Noureddine Mohtaram, Jeremy Patrix, Jerome Verny

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As an enormous number of online services have been developed into web applications, security problems based on web applications are becoming more serious now. Most intrusion detection systems rely on each request to find the cyber-attack rather than on user behavior, and these systems can only protect web applications against known vulnerabilities rather than certain zero-day attacks. In order to detect new attacks, we analyze the HTTP protocols of web servers to divide them into two categories: normal attacks and malicious attacks. On the other hand, the quality of the results obtained by deep learning (DL) in various areas of big data has given an important motivation to apply it to cybersecurity. Deep learning for attack detection in cybersecurity has the potential to be a robust tool from small transformations to new attacks due to its capability to extract more high-level features. This research aims to take a new approach, deep learning to cybersecurity, to classify these two categories to eliminate attacks and protect web servers of the defense sector which encounters different web traffic compared to other sectors (such as e-commerce, web app, etc.). The result shows that by using a machine learning method, a higher accuracy rate, and a lower false alarm detection rate can be achieved.

Keywords: anomaly detection, HTTP protocol, logs, cyber attack, deep learning

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Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva

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Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.

Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining

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Authors: Huseyin Arasli, Maryam Abdullahi, Tugrul Gunay

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One of the prominence elements used by the destination marketing organization (DMO) as a marketing strategy is the application of Social media tools. During the current spread of coronavirus disease (COVID-19), travel restriction was placed in most countries of the world, leading to the closure of borders movement. It should be noted that most tourism travelers depend on social media to obtain and exchange different kinds of information about COVID-19 in an unprecedented scale. The situational information people received is valued, which calls for the response of the tourism industry on the epidemic. Therefore, it is highly important to recognize such situational information and to understand how people spread this propaganda on social media platforms so that suitable information that relates the COVID-19 epidemic is available in a manner that will not tarnish the marketing strategies, festival planners. Data for this research study was collected from the desk review, which is a secondary source data, online blogs, and interview through social media chat. The results of this research show that the widespread of COVID-19 pandemics led to rapid lockdown in states and cities all over Nigeria, causing declining demands in hotels, airlines, recreation, and tourism centers. Additionally, billions of dollars lost has been recorded in the high increase of hotels and travel bookings cancellations which caused hundreds and thousands of job loss in the country. The result of this research also revealed that COVID-19 is causing more havoc on the unemployment rate indices of the country. Similarly, the over-dependence of government on petroleum has further caused considerable revenue loss, thereby raising a high poverty rate among less privileged Nigerians. Based on this result, the study suggested that there is an urgent need for the government to diversify its economy by looking at other different sectors such as tourism and agricultural farm produce to harmonize other commercial trades sectors in the country.

Keywords: social media, destination marketing organizations, DMOs, cultural COVID-19, coronavirus, hospitality, travel tour, tourism

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of CO2 emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), carbon dioxide (CO2) emissions and gross domestic product (GDP) for Turkey using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Phillips–Perron (PP) test for stationarity, Johansen maximum likelihood method for cointegration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. All the variables in this study show very strong significant effects on GDP in the country for the long term. The long-run equilibrium in the VECM suggests negative long-run causalities from consumption of petroleum products and the direct combustion of crude oil, coal and natural gas to GDP. Conversely, positive impacts of CO2 emissions and electricity consumption on GDP are found to be significant in Turkey during the period. There exists a short-run bidirectional relationship between electricity consumption and natural gas consumption. There exists a positive unidirectional causality running from electricity consumption to natural gas consumption, while there exists a negative unidirectional causality running from natural gas consumption to electricity consumption. Moreover, GDP has a negative effect on electricity consumption in Turkey in the short run. Overall, the results support arguments that there are relationships among environmental quality, energy use and economic output but the associations can to be differed by the sources of energy in the case of Turkey over of period 1980-2010.

Keywords: CO2 emissions, energy consumption, GDP, Turkey, time series analysis

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Authors: Manea A. I. Alqrad, Alaa Sirwi, Sabrin R. M. Ibrahim, Hossam M. Abdallah, Gamal A. Mohamed

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Phytochemical study of the methanolic extract of the air dried powdered of the parts of Viscum schemperi Engl. (Family: Viscaceae) using different chromatographic techniques led to the isolation of five compounds: -amyrenone (1), betulinic acid (2), (3β)-olean-12-ene-3,23-diol (3), -oleanolic acid (4), and α-oleanolic acid (5). Their structures were established based on physical, chemical, and spectral data. Anti-inflammatory and anti-apoptotic activities of oleanolic acid in a mouse model of acute hepatorenal damage were assessed. This study showed the efficacy of oleanolic acid to counteract thioacetamide-induced hepatic and kidney injury in mice through the reduction of hepatocyte oxidative damage, suppression of inflammation, and apoptosis. More importantly, oleanolic acid suppressed thioacetamide-induced hepatic and kidney injury by inhibiting NF-κB/TNF-α-mediated inflammation/apoptosis and enhancing SIRT1/Nrf2/Heme-oxygenase signalling pathway. These promising pharmacological activities suggest the potential use of oleanolic acid against hepatorenal damage.

Keywords: oleanolic acid, viscum schimperi, thioacetamide, SIRT1/Nrf2/NF-κB, hepatorenal damage

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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Authors: Ramandeep Kaur, Ashok Kumar Malik

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Fabric Phase Sorptive Extraction (FPSE) combined with Gas chromatography Mass Spectrometry (GCMS) has been developed for the determination of nineteen organochlorine pesticides in various aqueous samples. The method consolidates the features of sol-gel derived microextraction sorbents with rich surface chemistry of cellulose fabric substrate which could directly extract sample from complex sample matrices and incredibly improve the operation with decreased pretreatment time. Some vital parameters such as kind and volume of extraction solvent and extraction time were examinedand optimized. Calibration curves were obtained in the concentration range 0.5-500 ng/mL. Under the optimum conditions, the limits of detection (LODs) were in the range 0.033 ng/mL to 0.136 ng/mL. The relative standard deviations (RSDs) for extraction of 10 ng/mL 0f OCPs were less than 10%. The developed method has been applied for the quantification of these compounds in aqueous and fruit juice samples. The results obtained proved the present method to be rapid and feasible for the determination of organochlorine pesticides in aqueous samples.

Keywords: fabric phase sorptive extraction, gas chromatography-mass spectrometry, organochlorine pesticides, sample pretreatment

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Authors: Hamdi Belfeki, Belgacem Chandoul, Mnasser Hassouna, Mondher Mejri

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Aqueous and ethanolic extracts of eight Tunisian aromatic and medicinal plants (TAMP) were characterized by studying their composition in polyphenols and also their antiradical and antioxidant capacities. In absence and in the presence of the various extracts, α-amylase from Bacillus subtlis activity, was measured in order to detect a potential inhibition. The total contents of polyphenols and flavonoid vary in function of TAMP and the mobile phase used for the extraction (distilled water or ethanol). The ethanolic extracts showed the most significant antiradical and antioxidant activities. Only the extracts from Coriandrum sativum showed a significant inhibiting effect on the α-amylase activity. This inhibiting capacity could be correlated with the chemical profile of the two extracts, due to the fact that they have the greatest amount of total flavonoid. The ethanolic extract has the most important antioxidant and anti-radicalizing activities among the sixteen extracts studied. The inhibition kinetics of the two coriander extracts were evaluated by pre-incubation method, using Lineweaver-Burk’s equation, obtained by linearization of Michaeilis-Menten’s expression. The results showed that both extracts exercised a competitive inhibition mechanism.

Keywords: α-amylase, antioxidant activity, aromatic and medicinal plants, inhibition

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Authors: Maryam Heidari, James H. Jones Jr.

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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Baharuddin Patandjengi, A. Pabborong, T. Kuswinanti

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Bacterial ring rot caused by a gram-positive Coryneform bacterium Corynebacterium michiganensis subsp. sepedonicus is an important disease on potato crops in the world. The disease still belongs to an A1 quarantine pathogen in Indonesia, although it was found in West Java since 2013. The objective of this study was to know the presence of bacterial ring rot in four potato district areas in South Sulawesi. Infected samples were collected from potato fields and storage warehouses in Enrekang, Gowa, Jeneponto and Bantaeng districts. Potato tuber samples were cut and observed their vasiculer vessels and the bacterial ooze was used for isolation on Nutrient Agar and Nutrient Broth–Yeast extract medium. Bacterial isolates were then morphologically and physiologically characterized. A patogenicity test on eggplant and molecular characterization using PCR with specific primer for Cms (50F and Cms 50 R) was revealed for further identification. The results showed that Cms has become widespread in four districts of South Sulawesi. The bacterial ringrot disease incidence in these districts was reached above 30 %. All of 14 bacterial isolates that identified before using standard methods of EPPO, showed DNA band in size of 224 bp in PCR test, which indicated positively belong to C. michiganensis subsp. sepedonicus.

Keywords: bacterial ring rot, clavibacter michiganensis pv. sepedonicus, PCR, potato

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Authors: H. J. Pramod, S. Pethkar

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The evaluation of antiurolithiatic potentials from the extracts of Cucumis sativus fruits at different doses and cystone (standard formulation) at a dose of 750 mg/kg were measured for both preventive and curative regimen in wistar rats by adding 0.75% v/v ethylene glycol (EG) to drinking water for 28 days, except normal rats. After the completion of the experimental period, (28th day) urinary parameters like (urine volume, routine urine analysis, levels of calcium, phosphate, oxalate, magnesium, sodium) serum biomarkers like (creatinine, BUN, uric acid, ALP, ALT, AST) kidney homogenate analysis for (levels of calcium, oxalate and phosphate) were analysed. The treated groups shows increased in the urine output significantly compared to the normal. The extract shows significantly decreased in the urinary excretion of the calcium, phosphate, magnesium, sodium and oxalate. The both preventive and curative treatment of extracts showed decrease in the stone forming constituents in the kidneys of urolithiatic rats further the kidneys of all the groups were excised and sectioned for histopathological examination which further claims to posses antiurolithiatic activity.

Keywords: Cucumis sativus, urolithiasis, ethylene glycol, cystone

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Authors: Jamil Jafari, Sharafat Karimi

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The Arabic Language has a complicated system of prosody invented by the great grammarian Khalil Ibn Ahmad Farahidi. He could extract 15 meters out of his innovative five circles, which were used in Arabic poetry of the 7th and 8th centuries. Then after a while, his student Akhfash added or compensated another meter to his tutor's meters, so overall, we now have 16 different meters in Arabic poetry. These meters have been formed by various combinations of 8 different feet and each foot is combined of rudimentary units called Sabab and Wated which are combinations of movement (/) and silent (ʘ) letters. On the other hand in English, we are dealing with another system of metrical prosody. In this language, feet are consisted of stressed and unstressed syllables and are of six types: iamb, trochee, dactyl, anapest, spondee, and pyrrhic. Using the descriptive-analytic method, in this research we aim at making a comparison between Arabic and English systems of metrical prosody to investigate their similarities and differences. The results show that both of them are quantitative and both of them rely on syllables in afoot. But unlike Arabic, English is utilizing another rhyme system and the number of feet in a line differs from Arabic; also, its feet are combined of stressed and unstressed syllables, while those of Arabic is a combination of movement and silent letters.

Keywords: Arabic prosody, English prosody, foot, meter, poetry

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Authors: Joseph Uzuazomaro Oju

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The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

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Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Zakiullah Kalwar, Shabeer Ahmed Abbasi

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This research encompasses the study of Cretaceous Sembar Formation Shale Gas potential at Hajipur area. This study has been done with the approach of geophysical data integration. The structure is NE – SW trending anticline with two map able compartments at Cretaceous Sembar level. The study area is located within proven petroleum system. Cretaceous Sembar/Goru formation is in a Wet gas window and Tertiary source is possibly in the oil window. Potential seals are present in Upper Ranikot shale beds and Intra-Lower Ranikot shales. The effectiveness and presence of source and reservoir rocks are favorable in the area of interest. Cretaceous Sembar Shale and Goru Shale beds with good organic content (TOC upto 4%, Type II/III) are currently in gas generation window in the area. Source rock intervals are also reported in Eocene Kirthar Group (TOC upto 8%, Type –II). Good reservoir quality Paleocene Lower Ranikot and Cretaceous Sembar shale beds exist in the area. The collision between Indian and Eurasian Plates during Tertiary initiated folding and thrusting. The first phase of thrusting involved ophiolite emplacement along the western margins of the Indian Plate (west of the area under review). The main phase of thrusting in the Sulaiman region was from Late Miocene to the present. The study area contains Permian to Recent clastics and carbonates. The succession generally is younger in the southeast than in northwest. Intraformational sedimentation breaks are pronounced in Permian and Jurassic. Sulaiman Range is bounded by the Western Sulaiman Transform Fault Zone (of which the Kingri Fault is the major fault) to the west and by the Domanda Fault to the east. The Domanda Fault also constitutes the western boundary of the Sulaiman Foredeep, lies in sulaiman foredeep where subsurface having prominent independent closure. Several reservoir horizons of Jurassic to Eocene are established hydrocarbon producers in the Hajipur area.

Keywords: enough size, good potential, shale gas, structure closure

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Authors: Mei-Yi Wu, Shang-Ming Huang

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The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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Authors: Rajesh Chandra, Uttam K. Ghosh

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This study demonstrates microalgal bio-diesel generation from a cheap, abundant, non-edible fruit pulp of Cassia fistula L. The Cassia fistula L. fruit pulp aqueous extract (CFAE) was utilized as a growth medium for cultivation of microalga Chlorella minutissima (C. minutissima). This microalga accumulated a high amount of lipids when cultivated with CFAE as a source of nutrition in comparison to BG-11 medium. Different concentrations (10, 20, 30, 40 and 50%) of CFAE diluted with distilled water were used to cultivate microalga. Effects of light intensity and photoperiod were also observed on biomass and lipid yield of microalga. Light intensity of 8000 lux with a photoperiod of 18 h resulted in maximum biomass and lipid yield of 1.28 ± 0.03 and 0.3968 ± 0.05 g/L, respectively when cultivated with 40% CFAE. Fatty acid methyl ester (FAME) profile of bio-diesel obtained shown the presence of myristic acid (C14:0), palmitic acid (C16:0), palmitoleic acid (C16:1), stearic acid (C18:0), linoleic acid (C18:2), linolenic acid (C18:3), arachidic acid (C20:0), and gondoic acid (C20:1), as major fatty acids. These facts reflect that the fruit pulp of Cassia fistula L. can be used for cultivation of C. minutissima.

Keywords: biomass, bio-diesel, Cassia fistula L., C. minutissima, GC-MS, lipid

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Authors: Rebecca Thombre, Aishwarya Borate

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Chemical synthesis of nanoparticles produces toxic by-products, as a result of which eco-friendly methods of synthesis are gaining importance. The synthesis of nanoparticles using plant derived extracts is economical, safe and eco-friendly. Biostabilized gold nanoparticles were synthesized using extracts of Garcinia indica. The gold nanoparticles were characterized using UV-Vis spectrophotometry and demonstrated a peak at 527 nm. The presence of plant derived peptides and phytoconstituents was confirmed using the FTIR spectra. TEM analysis revealed formation of gold nanopyramids and nanorods. The SAED analysis confirmed the crystalline nature of nanoparticles. The gold nanoparticles demonstrated antibacterial and antifungal activity against Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Aspergillus niger and Pichia pastoris. The cytotoxic activity of gold nanoparticles was studied using HEK, Hela and L929 cancerous cell lines and the apoptosis of cancerous cells were observed using propidium iodide staining. Thus, a simple and eco-friendly method for synthesis of biostabilized gold nanoparticles using fruit extracts of Garcinia indica was developed and the nanoparticles had potent antibacterial, antifungal and anticancer properties.

Keywords: cytotoxic, gold nanoparticles, green synthesis, Garcinia indica, anticancer

Procedia PDF Downloads 924

Authors: Qintao Shen, Lei Luo, Jun Ma, Jie Yu, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Control Flow Integrity (CFI) is one of the most promising technique to defend Code-Reuse Attacks (CRAs). Traditional CFI Systems and recent Context-Sensitive CFI use coarse control flow graphs (CFGs) to analyze whether the control flow hijack occurs, left vast space for attackers at indirect call-sites. Coarse CFGs make it difficult to decide which target to execute at indirect control-flow transfers, and weaken the existing CFI systems actually. It is an unsolved problem to extract CFGs precisely and perfectly from binaries now. In this paper, we present an algorithm to get a more precise CFG from binaries. Parameters are analyzed at indirect call-sites and functions firstly. By comparing counts of parameters prepared before call-sites and consumed by functions, targets of indirect calls are reduced. Then the control flow would be more constrained at indirect call-sites in runtime. Combined with CCFI, we implement our policy. Experimental results on some popular programs show that our approach is efficient. Further analysis show that it can mitigate COOP and other advanced attacks.

Keywords: contex-sensitive, CFI, binary analysis, code reuse attack

Procedia PDF Downloads 315

Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

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Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

Procedia PDF Downloads 131

Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

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The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: autochthonous Miocene, Carpathian foredeep, Poland, shale gas

Procedia PDF Downloads 224

Authors: Hillary Mwongyera

Abstract:

The Semliki basin has become a frontier for petroleum exploration in recent years. Exploration efforts have resulted into extensive seismic data acquisition and drilling of three wells namely; Turaco 1, Turaco 2 and Turaco 3. A petrophysical analysis of the Turaco 1 well was carried out to identify two reservoir zones on which AVO modeling was performed. A combination of seismic modeling and rock physics modeling was applied during reservoir characterization and monitoring to determine variations of seismic responses with amplitude characteristics. AVO intercept gradient analysis applied on AVO synthetic CDP gathers classified AVO anomalies associated with both reservoir zones as Class 1 AVO anomalies. Fluid replacement modeling was carried out on both reservoir zones using homogeneous mixing and patchy saturation patterns to determine effects of fluid substitution on rock property interactions. For both homogeneous mixing and saturation patterns, density (ρ) showed an increasing trend with increasing brine substitution while Shear wave velocity (Vs) decreased with increasing brine substitution. A study of compressional wave velocity (Vp) with increasing brine substitution for both homogeneous mixing and patchy saturation gave quite interesting results. During patchy saturation, Vp increased with increasing brine substitution. During homogeneous mixing however, Vp showed a slightly decreasing trend with increasing brine substitution but increased tremendously towards and at full brine saturation. A sensitivity analysis carried out showed that density was a very sensitive rock property responding to brine saturation except at full brine saturation during homogeneous mixing where Vp showed greater sensitivity with brine saturation. Rock physics modeling was performed to predict diagnostics of reservoir quality using an inverse deterministic approach which showed low shale content and a high degree of shale stiffness within reservoir zones.

Keywords: Amplitude Versus Offset (AVO), fluid replacement modelling, reservoir characterization, AVO attributes, rock physics modelling, reservoir monitoring

Procedia PDF Downloads 523

Authors: Khaled M. Khleifat

Abstract:

An extracellular methanol and ethanol tolerant lipase producing bacterial strain K5b4 was isolated from soil samples contaminated with hydrocarbon residues. It was identified by using morphological and biochemical characteristics and 16srRNA technique as Acinetobacter species. The immobilized lipase from Acinetobacter sp. K5b4 retained more than 98% of its residual activity after incubation with pure methanol and ethanol for 24 hours. The highest hydrolytic activity of the immobilized enzyme was obtained in the presence of 75% (v/v) methanol in the assay solution. In contrary, the enzyme was able to maintain its original activity up to only 25% (v/v) ethanol whereas at elevated concentrations of 50 and 75% (v/v) the enzyme activity was reduced to 10 and 40%, respectively. Maximum lipase activity of 31.5 mU/mL was achieved after 48 hr cultivation when the optimized medium (pH 7.0) that composed of 1.0% (w/v) olive oil, 0.2% (w/v) glycerol, 0.15% (w/v) yeast extract, and 0.05% (w/v) NaCl was inoculated with 0.4% (v/v) seed culture and incubated at 30°C and 150 rpm agitation speed. However, the presence of CaCl2 in the growth media did not show any inhibitory or stimulatory effect on the enzyme production as it compared to the control experiment. Meanwhile, the other mineral salts MgCl2, MnCl2, KCl and CoCl2 were negatively affected the production of lipase enzyme. The inhibition of lipase production from Acinetobacter sp. K5b4 in presence of glucose suggesting that lipase gene expression is prone to catabolic repression.

Keywords: K5B4, methanol and ethanol, acinetobacter, morphological

Procedia PDF Downloads 314

Authors: Jinen Daghrir, Anis Kricha, Karim Kalti

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The amount of incoming administrative documents is massive and manually processing these documents is a costly task especially on the timescale. In fact, this problem has led an important amount of research and development in the context of automatically extracting fields from administrative documents, in order to reduce the charges and to increase the citizen satisfaction in administrations. In this matter, we introduce an administrative document understanding system. Given a document in which a user has to select fields that have to be retrieved from a document class, a document model is automatically built. A document model is represented by an attributed relational graph (ARG) where nodes represent fields to extract, and edges represent the relation between them. Both of vertices and edges are attached with some feature vectors. When another document arrives to the system, the layout objects are extracted and an ARG is generated. The fields extraction is translated into a problem of matching two ARGs which relies mainly on the comparison of the spatial relationships between layout objects. Experimental results yield accuracy rates from 75% to 100% tested on eight document classes. Our proposed method has a good performance knowing that the document model is constructed using only one single document.

Keywords: administrative document understanding, logical labelling, logical layout analysis, fields extraction from administrative documents

Procedia PDF Downloads 206