Search results for: Olive leaf extract

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

Procedia PDF Downloads 211

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

Procedia PDF Downloads 168

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

Procedia PDF Downloads 218

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: Disciglio G., Lops F., Carlucci A., Gatta G., Tarantino A., Frabboni L, Tarantino E.

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The Phelipanche ramosa is considered the most damaging obligate flowering parasitic weed on a wide species of cultivated plants. The semiarid regions of the world are considered the main center of this parasitic weed, where heavy infestation are due to the ability to produce high numbers of seeds (up to 200,000), that remain viable for extended period (more than 19 years). In this paper 13 treatments of parasitic weed control, as physical, chemical, biological and agronomic methods, including the use of the resistant plants, have been carried out. In 2014 a trial was performed on processing tomato (cv Docet), grown in pots filled with soil taken from a plot heavily infested by Phelipanche ramosa, at the Department of Agriculture, Food and Environment, University of Foggia (southern Italy). Tomato seedlings were transplanted on August 8, 2014 on a clay soil (USDA) 100 kg ha-1 of N; 60 kg ha-1 of P2O5 and 20 kg ha-1 of S. Afterwards, top dressing was performed with 70 kg ha-1 of N. The randomized block design with 3 replicates was adopted. During the growing cycle of the tomato, at 70-75-81 and 88 days after transplantation the number of parasitic shoots emerged in each pot was detected. Also values of leaf chlorophyll Meter SPAD of tomato plants were measured. All data were subjected to analysis of variance (ANOVA) using the JMP software (SAS Institute Inc., Cary, NC, USA), and for comparison of means was used Tukey's test. The results show lower values of the color index SPAD in tomato plants parasitized compared to those healthy. In addition, each treatment studied did not provide complete control against Phelipanche ramosa. However the virulence of the attacks was mitigated by some treatments: radicon product, compost activated with Fusarium, mineral fertilizer nitrogen, sulfur, enzone and resistant tomato genotype. It is assumed that these effects can be improved by combining some of these treatments each other, especially for a gradual and continuing reduction of the “seed bank” of the parasite in the soil.

Keywords: control methods, Phelipanche ramose, tomato crop

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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

Procedia PDF Downloads 146

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: 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 929

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

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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

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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

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Authors: Surendra Bodakhe

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In this investigation, anticataract activity was determined using cataract formation in developing chick embryo by hydrocortisone. Lenses were evaluated firstly for the extent of opacity and secondly, for lens glutathione (GSH) levels. Betulinic acid was isolated from the chloroform fraction of the crude ethanolic extract of Bauhinia variegata bark (SBE). Fourteen days old Australorp fertilized eggs were divided into different groups of six eggs each. After 24 hrs incubation in a humidified incubator (37οC), at 15 days of age; hydrocortisone (0.25µM/0.2ml/egg) was administered to the chorioallantoic membrane of chick embryos through a small hole in the egg shell on the air sack. Ascorbic acid (standard) or Betulinic acid (test) were administered at 3, 10 and 20 hr after hydrocortisone administration at a specified dose. The puncture was sealed with a cellophane tape and eggs were incubated for 48 hrs in a humidified incubator at 37οC. After 48 hrs, the lenses were isolated for the determination of the extent of opacity and Glutathione level. The betulinic acid prevented the opacification of the chick embryo lenses induced by hydrocortisone. The betulinic acid also prevented the decline of GSH content caused by hydrocortisone. The results indicate that betulinic acid protect the cataract formation in chick embryo lenses induced by hydrocortisone.

Keywords: betulinic acid, cataract, cloudiness, ovine

Procedia PDF Downloads 343

Authors: Saleh H. Salmen, Sulaiman Ali Alharbi, Hany M. Yehia, Mohammad A. Khiyami, Milton Wainwright, Naiyf S. Alharbi, Arunachalam Chinnathambi

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An antifungal protein synthesized by Bacillus cereus has been partially purified by the use of ammonium sulfate precipitation and Sephadex-G-200 column chromatography. The protein was produced from Bacillus cereus grown in potato Dextrose Broth Medium (PDB) at 30 ºC for 3 days at 100 rpm. The protein showed antagonistic effect against some fungi and yeasts. Crude extract from medium and semi-purified protein were tested in vitro against both fungi and yeasts using the disc diffusion method in order to detect the inhibitory effect of the protein. Zones of inhibition of the following diameter were found (mm) were Alternaria alternate (28), Rhodotorula glutinis (20), Fusarium sp. (16), Rhizopus sp. (15), Penicillium digitatum (13), Mucor sp. (13) and Aspergillus niger (10). The isolated protein was found to have a molecular weight of ~35kDa by sodium deodecyl sulfate-poly acrylamide gel electrophoresis. The data showed that the protein of Bacillus cereus has antifungal activity, a fact which points to the possibility of using it as a bio-control agent against some fungi, findings which emphasize the potential role of B. cereus as an important bio-control agent.

Keywords: bacillus cereus, ~35kDa protein, molds, yeasts

Procedia PDF Downloads 291

Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

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There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

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Authors: Xu Yingqiang, Wang Zhongde

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In the age of stock development, the contradiction between the protection and development of historical blocks in China has become increasingly prominent, among which how to reconcile the contradiction between tourists and local residents and inherit urban culture is an important proposition. Based on this, this paper introduces the theory of " staged authenticity ", combs its development process and related research progress, constructs an analysis and research model of historical blocks based on the theory of " staged authenticity ", and puts forward the protection and renewal strategy of historical blocks from the perspective of " staged authenticity ", which provides theoretical basis for coordinating the tourism-residence contradiction and protecting urban characteristics in the protection and renewal of historical blocks. The research holds that we should pay attention to the important value of "curtain" space, rationally arrange "curtain" and divide "foreground" and "background"; extract "props" from real history and culture to restore the authenticity of "stage" scenes; clever arrangement of tour streamline, so that all scenes are connected in series rhythmically; make the "actors" perform interactively in the "foreground" space, so as to enhance the "audience" sense of scene substitution.

Keywords: historic block, protection and renewal, staged authenticity, curtain

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Authors: Amira Ben Rabeh, Faouzi Benzarti, Hamid Amiri, Mouna Bouaziz

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Alzheimer is a disease that affects the brain. It causes degeneration of nerve cells (neurons) and in particular cells involved in memory and intellectual functions. Early diagnosis of Alzheimer Diseases (AD) raises ethical questions, since there is, at present, no cure to offer to patients and medicines from therapeutic trials appear to slow the progression of the disease as moderate, accompanying side effects sometimes severe. In this context, analysis of medical images became, for clinical applications, an essential tool because it provides effective assistance both at diagnosis therapeutic follow-up. Computer Assisted Diagnostic systems (CAD) is one of the possible solutions to efficiently manage these images. In our work; we proposed an application to detect Alzheimer’s diseases. For detecting the disease in early stage we used the three sections: frontal to extract the Hippocampus (H), Sagittal to analysis the Corpus Callosum (CC) and axial to work with the variation features of the Cortex(C). Our method of classification is based on Support Vector Machine (SVM). The proposed system yields a 90.66% accuracy in the early diagnosis of the AD.

Keywords: Alzheimer Diseases (AD), Computer Assisted Diagnostic(CAD), hippocampus, Corpus Callosum (CC), cortex, Support Vector Machine (SVM)

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Authors: Motlatsi Eric Morojele, Moleboheng Patricia Lekota, Pulane Nkhabutlane, Motanyane Stanley Motake

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Soybean was introduced in Lesotho to increase the spectrum of nutritious foods, especially protein, oil and carbohydrates. However, since then, determination of nutritional value has not been performed, hence this study. The objective of the study was to distinguish soybean genotypes on the basis of nutritive value. The experiment was laid out using a Randomized Complete Block Design with 27 treatments (genotypes) and three replications. Compound fertilizer 2:3:2 (22) was broadcasted over the experimental plot at the rate of 250kg ha-1. Dimensions of the main experimental plot were 135m long and 10m wide, with each sub-plot being 4m and 3.6m. Inter-row and intra-row spacing were 0.9m and 0.20m, respectively. Samples of seeds from each plot were taken to the laboratory to analyze protein content, ash, ca, mg, fiber, starch and ether extract. There were significant differences (P>0.05) among 28 soybean genotypes for protein content, acid detergent fiber, calcium, magnesium and ash. The soybean cultivars with the highest amount of protein were P48T48R, PAN 1663 and PAN 155R. High ADF content was expressed by PAN 1521R. LS 6868 exhibited the highest value of 0.788mg calcium, and the cultivars with the highest magnesium were NA 5509 with 1.306mg. PAN 1663, LCD 5.9, DM5302 RS and NS 6448R revealed higher nutritional values than other genotypes.

Keywords: genotypes, Lesotho, nutritive value, proximate analysis, soya-bean

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Authors: Elena Iacob, Marie-Louise Ionescu, Elena Ionescu, Carmen Elena Tebrencu, Oana Teodora Ciuperca

Abstract:

Infrared spectroscopy (FT-IR) is an advanced technique frequently used to authenticate both raw materials and final products using their specific fingerprints and to determine plant extracts biomarkers based on their functional groups. In recent years the market for Hypericum has grown rapidly and also has grown the cases of adultery/replacement, especially for Hypericum perforatum L.specie. Presence/absence of same biomarkers provides preliminary identification of Hypericum species in safe use in the manufacture of food supplements. The main objective of the work was to characterize the main biomarkers of Hypericum perforatum L. (St. John's wort) and identify this species in herbal food supplements after specific FT-IR fingerprint. An experimental program has been designed in order to test: (1) raw material (St. John's wort); (2)intermediate raw materials (St. John's wort dry extract ); (3) the finished products: tablets based on powders, on extracts, on powder and extract, hydroalcoholic solution from herbal mixture based on St. John's wort. The analyze using FTIR infrared spectroscopy were obtained raw materials, intermediates and finished products spectra, respectively absorption bands corresponding and similar with aliphatic and aromatic structures; examination was done individually and through comparison between Hypericum perforatum L. plant species and finished product The tests were done in correlation with phytochemical markers for authenticating the specie Hypericum perforatum L.: hyperoside, rutin, quercetin, isoquercetin, luteolin, apigenin, hypericin, hyperforin, chlorogenic acid. Samples were analyzed using a Shimatzu FTIR spectrometer and the infrared spectrum of each sample was recorded in the MIR region, from 4000 to 1000 cm-1 and then the fingerprint region was selected for data analysis. The following functional groups were identified -stretching vibrations suggests existing groups in the compounds of interest (flavones–rutin, hyperoside, polyphenolcarboxilic acids - chlorogenic acid, naphtodianthrones- hypericin): oxidril groups (OH) free alcohol type: rutin, hyperoside, chlorogenic acid; C = O bond from structures with free carbonyl groups of aldehyde, ketone, carboxylic, ester: hypericin; C = O structure with the free carbonyl of the aldehyde groups, ketone, carboxylic acid, esteric/C = O free bonds present in chlorogenic acid; C = C bonds of the aromatic ring (condensed aromatic hydrocarbons, heterocyclic compounds) present in all compounds of interest; OH phenolic groups: present in all compounds of interest, C-O-C groups from glycoside structures: rutin, hyperoside, chlorogenic acid. The experimental results show that: (I)The six fingerprint region analysis indicated the presence of specific functional groups: (1) 1000 - 1130 cm-1 (C-O–C of glycoside structures); (2) 1200-1380 cm-1 (carbonyl C-O or O-H phenolic); (3) 1400-1450 cm-1 (C=C aromatic); (4) 1600- 1730 cm-1 (C=O carbonyl); (5) 2850 - 2930 cm-1 (–CH3, -CH2-, =CH-); (6) 338-3920 cm-1 (OH free alcohol type); (II)Comparative FT-IR spectral analysis indicate the authenticity of the finished products ( tablets) in terms of Hypericum perforatum L. content; (III)The infrared spectroscopy is an adequate technique for identification and authentication of the medicinal herbs , intermediate raw material and in the food supplements less in the form of solutions where the results are not conclusive.

Keywords: Authentication, FT-IR fingerprint, Herbal supplements, Hypericum perforatum L.

Procedia PDF Downloads 375

Authors: S. Boorboor, S. A. H. Feghhi, H. Jafari

Abstract:

The ionizing radiations cause different kinds of damages in electronic components. MOSFETs, most common transistors in today’s digital and analog circuits, are severely sensitive to TID damage. In this work, the threshold voltage shift of CD4007 device, which is an integrated circuit including P-channel and N-channel MOS transistors, was investigated for low dose gamma irradiation under different gate bias voltages. We used linear extrapolation method to extract threshold voltage from I_D-V_G characteristic curve. The results showed that the threshold voltage shift was approximately 27.5 mV/Gy for N-channel and 3.5 mV/Gy for P-channel transistors at the gate bias of |9 V| after irradiation by Co-60 gamma ray source. Although the sensitivity of the devices under test were strongly dependent to biasing condition and transistor type, the threshold voltage shifted linearly versus accumulated dose in all cases. The overall results show that the application of CD4007 as an electronic buffer in a radiation therapy system is limited by TID damage. However, this integrated circuit can be used as a cheap and sensitive radiation dosimeter for accumulated dose measurement in radiation therapy systems.

Keywords: threshold voltage shift, MOS transistor, linear extrapolation, gamma irradiation

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Authors: Mohammad A. M. Kewisha

Abstract:

Xerophilic fungi , which are responsible for many cases of biodeterioration monuments, have been known as an interesting source of antimicrobial compounds. Sixty nine fungal strains, isolated from different localities and species inside Egyptian museums, were screened for antimicrobial activity against some bacterial species and unicellular fungi. The most potent antimicrobial activity was obtained by Asperigillus fumigatus which was identified by ITS4 ……. and showed activity against Staphylococcus aureus with 20 mm and C. albicans with18 mm of inhibition zone. Different parameters were optimized to enhance this activity. The culture grown under stationary conditions for 8 days at 30°C and pH 8 gave the best antimicrobial activity. Moreover, both starch and yeast extract showed the most suitable carbon and nitrogen sources, respectively. The antimicrobial compound was purified and subjected to spectroscopic characterization, which revealed that the antimicrobial compound might be 5,7 ethoxy, 4\,5\ methoxy isorhamnetin -3- O- galactoside. This study suggests that Aspergillus fumagates as a potential candidate offering a better scope for the production, purification and isolation of broad-spectrum antimicrobial compounds. These findings will facilitate the scale-up and further purification to ascertain the compounds responsible for antimicrobial activity, which can be exploited for the treatment of biodeterioration monuments and pharmaceutical applications.

Keywords: antimicrobial activity, asperigillus fumigatus, Identification by ITS4, Staphylococcus aureus, C.albicans

Procedia PDF Downloads 54

Authors: Panatda Intanin, Sangutid Thongsawad, Chirapha Tannanonta, Todsaporn Fuangrod

Abstract:

Stereotactic radiosurgery (SRS) is a highly precision delivery technique that requires comprehensive quality assurance (QA) tests prior to treatment delivery. An isocenter of delivery beam plays a critical role that affect the treatment accuracy. The uncertainty of isocenter is traditionally accessed using circular cone equipment, Winston-Lutz (WL) phantom and film. This technique is considered time consuming and highly dependent on the observer. In this work, the development of multileaf collimator (MLC)-based isocenter verification tool using electronic portal imaging device (EPID) was proposed and evaluated. A mechanical isocenter alignment with ball bearing diameter 5 mm and circular cone diameter 10 mm fixed to gantry head defines the radiation field was set as the conventional WL test method. The conventional setup was to compare to the proposed setup; using MLC (10 x 10 mm) to define the radiation filed instead of cone. This represents more realistic delivery field than using circular cone equipment. The acquisition from electronic portal imaging device (EPID) and radiographic film were performed in both experiments. The gantry angles were set as following: 0°, 90°, 180° and 270°. A software tool was in-house developed using MATLAB/SIMULINK programming to determine the centroid of radiation field and shadow of WL phantom automatically. This presents higher accuracy than manual measurement. The deviation between centroid of both cone-based and MLC-based WL tests were quantified. To compare between film and EPID image, the deviation for all gantry angle was 0.26±0.19mm and 0.43±0.30 for cone-based and MLC-based WL tests. For the absolute deviation calculation on EPID images between cone and MLC-based WL test was 0.59±0.28 mm and the absolute deviation on film images was 0.14±0.13 mm. Therefore, the MLC-based isocenter verification using EPID present high sensitivity tool for SRS QA.

Keywords: isocenter verification, quality assurance, EPID, SRS

Procedia PDF Downloads 152