Search results for: ginger extract

Authors: Chung-Young Lee, Se-Hee Ahn, Jun-Gu Choi, Youn-Jeong Lee, Hyuk-Joon Kwon, Jae-Hong Kim

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A/chicken/Korea/01310/2001 (H9N2) (01310) was passaged through embryonated chicken eggs (ECEs) by 20 times (01310-E20), and it has been used for an inactivated oil emulsion vaccine in Korea. After sequential passages, 01310-E20 showed higher pathogenicity in ECEs and acquired multiple mutations including a potential N-glycosylation at position 133 (H3 numbering) in HA and 18aa-deletion in NA stalk. To evaluate the effect of these mutations on the mammalian pathogenicity and resistance to non-specific inhibitors, we generated four PR8-derived recombinant viruses with different combinations of HA and NA from 01310-E2 and 01310-E20 (rH2N2, rH2N20, rH20N2, and rH20N20). According to our results, recombinant viruses containing 01310 E20 HA showed higher growth property in MDCK cells and higher virulence on mice than those containing 01310 E2 HA regardless of NA. The hemagglutination activity of rH20N20 was less inhibited by egg white and mouse lung extract than that of other recombinant viruses. Thus, the increased pathogenicity of 01310-E20 may be related to both higher replication efficiency and resistance to non-specific inhibitors in mice.

Keywords: avian influenza virus, egg adaptation, H9N2, N-glycosylation, stalk deletion of neuraminidase

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Authors: Chung-Ming Lo, Kevin Li-Chun Hsieh

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The central nervous system in the World Health Organization defines grade 2, 3, 4 gliomas according to the aggressiveness. For brain tumors, using image examination would have a lower risk than biopsy. Besides, it is a challenge to extract relevant tissues from biopsy operation. Observing the whole tumor structure and composition can provide a more objective assessment. This study further proposed a computer-aided diagnosis (CAD) system based on a convolutional neural network to quantitatively evaluate a tumor's malignancy from brain magnetic resonance imaging. A total of 30 grade 2, 43 grade 3, and 57 grade 4 gliomas were collected in the experiment. Transferred parameters from AlexNet were fine-tuned to classify the target brain tumors and achieved an accuracy of 98% and an area under the receiver operating characteristics curve (Az) of 0.99. Without pre-trained features, only 61% of accuracy was obtained. The proposed convolutional neural network can accurately and efficiently classify grade 2, 3, and 4 gliomas. The promising accuracy can provide diagnostic suggestions to radiologists in the clinic.

Keywords: convolutional neural network, computer-aided diagnosis, glioblastoma, magnetic resonance imaging

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Authors: Khaled Halimi, Hassina Seridi-Bouchelaghem

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The purpose of this paper is to describe how learning analytics approaches based on social semantic web techniques can be applied to enhance the lifelong learning experiences in a connectivist perspective. For this reason, a prototype of a system called SoLearn (Social Learning Environment) that supports this approach. We observed and studied literature related to lifelong learning systems, social semantic web and ontologies, connectivism theory, learning analytics approaches and reviewed implemented systems based on these fields to extract and draw conclusions about necessary features for enhancing the lifelong learning process. The semantic analytics of learning can be used for viewing, studying and analysing the massive data generated by learners, which helps them to understand through recommendations, charts and figures their learning and behaviour, and to detect where they have weaknesses or limitations. This paper emphasises that implementing a learning analytics approach based on social semantic web representations can enhance the learning process. From one hand, the analysis process leverages the meaning expressed by semantics presented in the ontology (relationships between concepts). From the other hand, the analysis process exploits the discovery of new knowledge by means of inferring mechanism of the semantic web.

Keywords: connectivism, learning analytics, lifelong learning, social semantic web

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Authors: M. Miriam Hernández-Arroyo, Ivonne Caro-Gonzales, Miguel Ángel Plascencia-Espinosa, Sergio R. Trejo-Estrada

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A large biodiversity of Lactobacillus strains has been detected in traditional foods and beverages from Mexico. A selected strain of Lactobacillus sp - PODI-20, used for the obtained from an artisanal fermented beverage was cultivated in different carbon sources in a complex medium, in order to define which carbon sourced induced more effectively the isomerization of arabinose by cell fractions obtained by fermentation. Four different carbon sources were tested in a medium containing peptone and yeast extract and mineral salts. Glucose, galactose, arabinose, and lactose were tested individually at three different concentrations: 3.5, 6, and 10% w/v. The biomass yield ranged from 1.72 to 17.6 g/L. The cell pellet was processed by mechanical homogenization. Both fractions, the cellular debris, and the lysis supernatant were tested for their ability to isomerize arabinose into ribulose. The highest yield of isomer was 12 % of isomerization in the supernatant fractions; whereas up to 9.3% was obtained by the use of cell debris. The isomerization of arabinose has great significance in the production of lactic acid by fermentation of complex carbohydrate hydrolysates.

Keywords: isomerase, tagatose, aguamiel, isomerization

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Authors: Mehran Fadaeinasab, Hamed Karimian, Najihah Mohd Hashim, Hapipah Mohd Ali

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In this study, three indole alkaloids namely; rauvolfine B, macusine B, and isoreserpiline have been isolated from the dichloromethane crude extract of Rauvolfia reflexa bark (Apocynaceae). The structural elucidation of the isolated compounds has been performed using spectral methods such as UV, IR, MS, 1D, and 2D NMR. Rauvolfine B showed anti proliferation activity on HCT-116 cancer cell line, its cytotoxicity induction was observed using MTT assay in eight different cell lines. Annexin-V is serving as a marker for apoptotic cells and the Annexin-V-FITC assay was carried out to observe the detection of cell-surface Phosphatidylserine (PS). Apoptosis was confirmed by using caspase-8 and -9 assays. Cell cycle arrest was also investigated using flowcytometric analysis. rauvolfine B had exhibited significantly higher cytotoxicity against HCT-116 cell line. The treatment significantly arrested HCT-116 cells in the S phase. Together, the results presented in this study demonstrated that rauvolfine B inhibited the proliferation of HCT-116 cells and programmed cell death followed by cell cycle arrest.

Keywords: apocynacea, indole alkaloid, apoptosis, cell cycle arrest

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Authors: Zine Souhila Rached, Mazari Benyounes Bouzid, Mohamed Amine, Allaoui Tayeb

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, its high cost is a major constraint, especially on the less windy sites. The purpose of wind energy systems is to maximize energy efficiency, and extract maximum power from the wind speed. In other words, having a power coefficient is maximum and therefore the maximum power point tracking. In this case, the MPPT control becomes important.To realize this control, strategy conventional proportional and integral (PI) controller is usually used. However, this strategy cannot achieve better performance. This paper proposes a robust control of a turbine which optimizes its production, that is improve the quality and energy efficiency, namely, a strategy of sliding mode control. The proposed sliding mode control strategy presents attractive features such as robustness to parametric uncertainties of the turbine; the proposed sliding mode control approach has been simulated on three-blade wind turbine. The simulation result under Matlab\Simulink has validated the performance of the proposed MPPT strategy.

Keywords: wind turbine, maximum power point tracking, sliding mode, energy conversion systems

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Authors: Hashem Barati, Afshin Farahbakhsh

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The flowers of saffron contain anthocyanins. Generally, extraction of anthocyanins takes place at low temperatures (below 30 °C), preferably under vacuum (to minimize degradation) and in an acidic environment. In order to extract anthocyanins, the dried petals were added to 30 ml of acidic ethanol (pH=2). Amount of petals, extraction time, temperature, and ethanol percentage which were selected. Total anthocyanin content was a function of both variables of ethanol percent and extraction time.To prepare SW with pH of 3.5, different concentrations of 100, 400, 700, 1,000, and 2,000 ppm of sodium metabisulfite were added to aqueous sodium citrate. At this selected concentration, different extraction times of 20, 40, 60, 120, 180 min were tested to determine the optimum extraction time. When the extraction time was extended from 20 to 60 min, the total recovered anthocyanins of sulfur method changed from 650 to 710 mg/100 g. In the EW method Cellubrix and Pectinex enzymes were added separately to the buffer solution at different concentrations of 1%, 2.5%, 5%, 7%, 10%, and 12.5% and held for 2 hours reaction time at an ambient temperature of 40 °C. There was a considerable and significant difference in trends of Acys content of tepals extracted by pectinex enzymes at 5% concentration and AE solution.

Keywords: saffron, anthocyanins, acidic environment, acidic ethanol, pectinex enzymes, Cellubrix enzymes, sodium metabisulfite

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Authors: Girma Yohannis Bade, Olga Kolesnikova, Grigori Sidorov

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Named entity recognition (NER) is a building block for information extraction. Though the information extraction process has been automated using a variety of techniques to find and extract a piece of relevant information from unstructured documents, the discovery of targeted knowledge still poses a number of research difficulties because of the variability and lack of structure in Web data. NER, a subtask of information extraction (IE), came to exist to smooth such difficulty. It deals with finding the proper names (named entities), such as the name of the person, country, location, organization, dates, and event in a document, and categorizing them as predetermined labels, which is an initial step in IE tasks. This survey paper presents the roles and importance of NER to IE from the perspective of different algorithms and application area domains. Thus, this paper well summarizes how researchers implemented NER in particular application areas like finance, medicine, defense, business, food science, archeology, and so on. It also outlines the three types of sequence labeling algorithms for NER such as feature-based, neural network-based, and rule-based. Finally, the state-of-the-art and evaluation metrics of NER were presented.

Keywords: the role of NER, named entity recognition, information extraction, sequence labeling algorithms, named entity application area

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Sana Abbasa, Shahzad Bhattiab, Nadir Khan

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Sargassum siliquastrum is brown seaweed with traditional claims for some medicinal properties. This research was done to investigate the methanol extract of S. siliquastrum for antiproliferative activity against human cervical cancer cell line, HeLa and its mode of cell death. From methylene blue assay, S. siliquastrum exhibited antiproliferative activity on HeLa cells with IC50 of 3.87 µg/ml without affecting non-malignant cells. Phase contrast microscopy indicated the confluency reduction in HeLa cells and changes on the cell shape. Nuclear staining with Hoechst 33258 displayed the formation of apoptotic bodies and fragmented nuclei. S. siliquastrum also induced early apoptosis event in HeLa cells as confirmed by FITC-Annexin V/propidium iodide staining by flow cytometry analysis. Cell cycle analysis indicated growth arrest of HeLa cells at G1/S phase. Protein study by flow cytometry indicated the increment of p53, slight increase of Bax and unchanged level of Bcl-2. In conclusion, S. siliquastrum demonstrated an antiproliferative activity in HeLa cell by inducing G1/S cell cycle arrest via p53-mediated pathway.

Keywords: sargassum siliquastrum, cervical cancer, P53, antiproleferation

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Authors: Mohammed Auwal Ibrahim, Isa Yunusa, Nafisa Kabir, Shazali Ali Baba, Amina Muhammad Yushau, Suraj Suraj Ibrahim, Zaharaddeen Idris Bello, Suleiman Haruna Suleiman, Murtala Bindawa Isah

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Background: Inhibition of intestinal maltase and sucrase prevents postprandial blood glucose excursions which are beneficial in ameliorating diabetes-associated complications. Objective: In this study, the inhibitory effects of fruit extracts of Parinari macrophylla, Detarium microcarpum, Ziziphus spina-christi, Z. mairei and Parkia biglobosa were investigated against intestinal maltase and sucrase. Methods: Rats were given co-administration of the fruit extracts with maltose or sucrose and blood glucose levels were measured at 0, 30, 90 and 120 min. Results: The glucose-time curves indicated that all the fruits had the most potent inhibitory effects on both maltase and sucrase within the first 30 min. The computed Area Under the Curves (AUC0-120)for all the fruits indicated more potent inhibitory effects against intestinal maltase than sucrase.The ED50 range for the fruits extract against maltase and sucrase were 647.15-1118.35 and 942.44-1851.94 mg/kg bw respectively. Conclusion: The data suggests that the fruits could prevent postprandial hyperglycemia via inhibition of intestinal maltase and sucrase.

Keywords: diabetes mellitus, fruits, α-glucosidases, maltase, sucrase

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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Authors: Babak Bashari Rad

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A metamorphic computer virus uses different code transformation techniques to mutate its body in duplicated instances. Characteristics and function of new instances are mostly similar to their parents, but they cannot be easily detected by the majority of antivirus in market, as they depend on string signature-based detection techniques. The purpose of this research is to propose a Hidden Markov Model for classification of metamorphic viruses in executable files. In the proposed solution, portable executable files are inspected to extract the instructions opcodes needed for the examination of code. A Hidden Markov Model trained on portable executable files is employed to classify the metamorphic viruses of the same family. The proposed model is able to generate and recognize common statistical features of mutated code. The model has been evaluated by examining the model on a test data set. The performance of the model has been practically tested and evaluated based on False Positive Rate, Detection Rate and Overall Accuracy. The result showed an acceptable performance with high average of 99.7% Detection Rate.

Keywords: malware classification, computer virus classification, metamorphic virus, metamorphic malware, Hidden Markov Model

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Authors: R. Kandiah, K. Miyamoto

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In Sri Lanka, the Jaffna area is a high drought affected area and depends mainly on groundwater aquifers for water needs. Water for daily activities is extracted from wells. As households manually extract water from the wells, it is not drawn from mid evening to early morning. The water inflow at night provides the maximum water level that decreases during the daytime due to extraction. The storage volume of water in wells is limited or at its lowest level during the dry season. This study analyzes the domestic water budget during the dry season in the Jaffna area. In order to evaluate the water inflow rate into wells, storage volume and extraction volume from wells over time, water pressure is measured at the bottom of three wells, which are located in coastal area denoted as well A, in nonspecific area denoted as well B, and agricultural area denoted as well C. The water quality at the wells A, B, and C, are mostly fresh, modest fresh, and saline respectively. From the monitoring, we can find that the daily inflow amount of water into the wells and daily water extraction depend on each other, that is, higher extraction yields higher inflow. And, in the dry season, the daily inflow volume and the daily extraction volume of each well are almost in balance.

Keywords: accessible volume, consumption volume, inflow rate, water budget

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Authors: Yusra Abdulsalam Alqamati, Ahmed Alkilany

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The teaching staff is a distinct group whose impact is on the educational process and which plays an important role in enhancing the quality of the academic education process. To improve the management effectiveness of the academy, the Teaching Staff Management System (TSMS) proposes that all teacher processes be digitized. Since the BPMN approach can accurately describe the processes, it lacks a clear picture of the process flow map, something that the process mining approach has, which is extracting information from event logs for discovery, monitoring, and model enhancement. Therefore, these two methodologies were combined to create the most accurate representation of system operations, the ability to extract data records and mining processes, recreate them in the form of a Petri net, and then generate them in a BPMN model for a more in-depth view of process flow. Additionally, the TSMS processes will be orchestrated to handle all requests in a guaranteed small-time manner thanks to the integration of the Google Cloud Platform (GCP), the BPM engine, and allowing business owners to take part throughout the entire TSMS project development lifecycle.

Keywords: process mining, BPM, business process model and notation, Petri net, teaching staff, Google Cloud Platform

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Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

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Authors: Hui-Yun Cao, Hai-Qing Zhou

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The high precision measurements and experiments play more and more important roles in particle physics and atomic physics. To analyse the precise experimental data sets, the corresponding precise and reliable theoretical calculations are necessary. Until now, the form factors of elemental constituents such as pion and proton are still attractive issues in current Quantum Chromodynamics (QCD). In this work, the two-photon-exchange (TPE) effects in ep→enπ⁺ at small -t are discussed within a hadronic model. Under the pion dominance approximation and the limit mₑ→0, the TPE contribution to the amplitude can be described by a scalar function. We calculate TPE contributions to the amplitude, and the unpolarized differential cross section with the only elastic intermediate state is considered. The results show that the TPE corrections to the unpolarized differential cross section are about from -4% to -20% at Q²=1-1.6 GeV². After considering the TPE corrections to the experimental data sets of unpolarized differential cross section, we analyze the TPE corrections to the separated cross sections σ(L,T,LT,TT). We find that the TPE corrections (at Q²=1-1.6 GeV²) to σL are about from -10% to -30%, to σT are about 20%, and to σ(LT,TT) are much larger. By these analyses, we conclude that the TPE contributions in ep→enπ⁺ at small -t are important to extract the separated cross sections σ(L,T,LT,TT) and the electromagnetic form factor of π⁺ in the experimental analysis.

Keywords: differential cross section, form factor, hadronic, two-photon

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Authors: Zahia Aliche, Fatiha Boudjema, Benyoucef Khelidj, Selma Mettai, Zohra Bouriahi, Saliha Mohammed Belkebir, Ridha Mazouz

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The purpose of this work is the study of the viscoelastic behaviour formulating gels based plant extractions. The extracts of Zingibar officinale and Cinnamomum cassia were included in the gel at different concentrations of these plants in order to be applied in anti-inflammatory drugs. The yield of ethanolic extraction of Zingibar o. is 3.98% and for Cinnamomum c., essential oil by hydrodistillation is 1.67 %. The ethanolic extract of Zingibar.o, the essential oil of Cinnamomum c. and the mixture showed an anti-DPPH radicals’ activity, presented by EC50 values of 11.32, 13.48 and 14.39 mg/ml respectively. A gel based on different concentrations of these extracts was prepared. Microbiological tests conducted against Staphylococcus aureus and Escherichia colishowed moderate inhibition of Cinnamomum c. gel and less the gel based on Cinnamomum c./ Zingibar o. (20/80). The yeast Candida albicansis resistant to gels. The viscoelastic formulation property was carried out in dynamic and creep and modeled with the Kelvin-Voigt model. The influence of some parameters on the stability of the gel (time, temperature and applied stress) has been studied.

Keywords: Cinnamomum cassia, Zingibar officinale, antioxidant activity, antimicrobien activity, gel, viscoelastic behaviour

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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

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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: 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

Abstract:

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

Abstract:

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

Abstract:

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.

Abstract:

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

Abstract:

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

Procedia PDF Downloads 331