Search results for: microalgae crude extract
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2703

Search results for: microalgae crude extract

843 Metamorphic Computer Virus Classification Using Hidden Markov Model

Authors: Babak Bashari Rad

Abstract:

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

Procedia PDF Downloads 298
842 Improvement of Plantain Leaves Nutritive Value in Goats by Urea Treatment and Nitrogen Supplements

Authors: Marie Lesly Fontin, Audalbert Bien-Aimé, Didier Marlier, Yves Beckers

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Fecal digestibility of mature plantain leaves was determined in castrated Creolegoatsin order to better assess them. Five diets made from plantain leaves were used in an in vivo digestibility study on 20 castrated Creole goats over three periods using a completely random design in order to assess their apparent fecal digestibility (Dg). These diets consisted of sun-dried leaves (DL), sun-dried urea treated leaves (DUTL, 5kg of urea per 100kg of raw product ensilaged during 90 days with 60 kg of water), sun-dried leaves + hoopvine (Trichostigma octandrum, L)(DLH, DL: 61.4% + Hoopvine: 38.6%), sun-dried leaves + urea (DLU, DL: 98.2%+ U: 1.8%), and fresh leaves. (FL).0.5% of salt diluted with water was added to diets before distribution to the goats. A mineral lick block was available for each goat in its digestibility cage. During each period, diets were distributed to meet the maintenance needs of the goats for 21 days, including 14 days of adaptation and 7 days of measurement. Offered and refused diets and feces were weighed every day, and samples were taken for laboratory analysis. Results showed that the urea treatment increasedCP (Crude Protein) content of DL by 44% (from 10.4% for DL to 15.0% for DUTL) and decreased their NDF (Neutral Detergent Fiber) content (55.5% to 52.4%). Large amounts of refused feed (around 40%) were observed in goats fed with FL, DLU, and DL diets, for which no significant difference was observed for DM (Dry Matter) intakes (40.3; 36.6 and 35.1g/kg0.75 respectively) (p>0.05). DM intakes of DUTL (59.9 g/kg0.75) were significantly (p<0.05) greater than DLH (50.2 g/kg0.75). DM Dg of DL was very low (29.2%). However, supplementation with hoopvine and urea treatment resulted in a significant increase of DM Dg (40.3% and 42.1%, respectively), but the addition of urea (DLU) had no effect on it. FL showed a DM Dg similar to DHL and DUTL diets (39.0%). OM (Organic Matter)Dg was higher for the DUTL diet (45.1%), followed by DLH (40.9%), then by DLU and FL (32.9% and 40.7% respectively) and finally by DL (29.8%). CP Dg was higher for the FL diet (65.7%) and lower for the DL diet (39.9%). NDF Dg was also increased with urea treatment (54.8% for DUTL) and with the addition of hoopvine (41.4%) compared to the DL diet (31.0% for DLH). In conclusion, urea treatment and complementation with hoopvine of plantain leaves are the best treatments among those tested for increasing the nutritive value of this foragein the castrated Creole goats.

Keywords: apparent fecal digestibility, nitrogen supplements, plantain leaves, urea treatment

Procedia PDF Downloads 192
841 Water Budget in High Drought-Borne Area in Jaffna District, Sri Lanka during Dry Season

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

Procedia PDF Downloads 347
840 Process Mining as an Ecosystem Platform to Mitigate a Deficiency of Processes Modelling

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

Procedia PDF Downloads 123
839 Neighborhood Graph-Optimized Preserving Discriminant Analysis for Image Feature Extraction

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

Procedia PDF Downloads 135
838 Two-Photon-Exchange Effects in the Electromagnetic Production of Pions

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

Procedia PDF Downloads 116
837 Rheological Characterization of Gels Based on Medicinal Plant Extracts Mixture (Zingibar Officinale and Cinnamomum Cassia)

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

Abstract:

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

Procedia PDF Downloads 67
836 Pathophysiological Implications in Immersion Treatment Methods of Icthyophthiriasis Disease in African Catfish (Clarias gariepinus) Using Moringa oleifera Extract

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

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

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

Procedia PDF Downloads 368
835 Association between Dental Caries and Asthma among 12-15 Years Old School Children Studying in Karachi, Pakistan: A Cross Sectional Study

Authors: Wajeeha Zahid, Shafquat Rozi, Farhan Raza, Masood Kadir

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Background: Dental caries affects the overall health and well-being of children. Findings from various international studies regarding the association of dental caries with asthma are inconsistent. With the increasing burden of caries and childhood asthma, it becomes imperative for an underdeveloped country like Pakistan where resources are limited to identify whether there is a relationship between the two. This study aims to identify an association between dental caries and asthma. Methods: A cross-sectional study was conducted on 544 children aged 12-15 years recruited from five private schools in Karachi. Information on asthma was collected through the International Study of Asthma and Allergies in Childhood (ISAAC) questionnaire. The questionnaire addressed questions regarding child’s demographics, physician diagnoses of asthma, type of medication administered, family history of asthma and allergies, dietary habits and oral hygiene behavior. Dental caries was assessed using DMFT Index (Decayed, Missing, Filled teeth) index The data was analyzed using Cox proportional Hazard algorithm and crude and adjusted prevalence ratios with 95% CI were reported. Results: This study comprises of 306 (56.3%) boys and 238 (43.8%) girls. The mean age of children was 13.2 ± (0.05) years. The total number of children with carious teeth (DMFT > 0) were 166/544 (30.5%), and the decayed component contributed largely (22.8%) to the DMFT score. The prevalence of physician’s diagnosed asthma was 13%. This study identified almost 7% asthmatic children using the internationally validated International Study of Asthma and Allergies in Childhood (ISAAC) tool and 8 children with childhood asthma were identified by parent interviews. Overall prevalence of asthma was 109/544 (20%). The prevalence of caries in asthmatic children was 28.4% as compared to 31% among non-asthmatic children. The adjusted prevalence ratio of dental caries in asthmatic children was 0.8 (95% CI 0.59-1.29). After adjusting for carious food intake, age, oral hygiene index and dentist visit, the association between asthma and dental caries turned out to be non-significant. Conclusion: There was no association between asthma and dental caries among children who participated in this study.

Keywords: asthma, caries, children, school-based

Procedia PDF Downloads 229
834 Protective Effect of Germinated Fenugreek Seeds on Keratoachantoma Cancer Skin

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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833 Effect of Crystallographic Characteristics on Toughness of Coarse Grain Heat Affected Zone for Different Heat Inputs

Authors: Trishita Ray, Ashok Perka, Arnab Karani, M. Shome, Saurabh Kundu

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Line pipe steels are used for long distance transportation of crude oil and gas under extreme environmental conditions. Welding is necessary to lay large scale pipelines. Coarse Grain Heat Affected Zone (CGHAZ) of a welded joint exhibits worst toughness because of excessive grain growth and brittle microstructures like bainite and martensite, leading to early failure. Therefore, it is necessary to investigate microstructures and properties of the CGHAZ for different welding heat inputs. In the present study, CGHAZ for two heat inputs of 10 kJ/cm and 50 kJ/cm were simulated in Gleeble 3800, and the microstructures were investigated in detail by means of Scanning Electron Microscopy (SEM) and Electron Backscattered Diffraction (EBSD). Charpy Impact Tests were also done to evaluate the impact properties. High heat input was characterized with very low toughness and massive prior austenite grains. With the crystallographic information from EBSD, the area of a single prior austenite grain was traced out for both the welding conditions. Analysis of the prior austenite grains showed the formation of high angle boundaries between the crystallographic packets. Effect of these packet boundaries on secondary cleavage crack propagation was discussed. It was observed that in the low heat input condition, formation of finer packets with a criss-cross morphology inside prior austenite grains was effective in crack arrest whereas, in the high heat input condition, formation of larger packets with higher volume of low angle boundaries failed to resist crack propagation resulting in a brittle fracture. Thus, the characteristics in a crystallographic packet and impact properties are related and should be controlled to obtain optimum properties.

Keywords: coarse grain heat affected zone, crystallographic packet, toughness, line pipe steel

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832 Green Delivery Systems for Fruit Polyphenols

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

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

Keywords: anthocyanins, green extraction, NADES, polyphenols

Procedia PDF Downloads 79
831 Effects of Cellular Insulin Receptor Stimulators with Alkaline Water on Performance, some Blood Parameters and Hatchability in Breeding Japanese Quail

Authors: Rabia Göçmen, Gülşah Kanbur, Sinan Sefa Parlat

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In this study, in the breeding Japanese quails (coturnix coturnix japonica), it was aimed to study the effects of cellular insulin receptor stimulation on the performance, some blood parameters, and hatchability features. In the study, a total of 84 breeding quails were used, which are in 6 weeks age, and whose 24 are male and 60 female. In the trial, rations which contain 2900 kcal/kg metabolic energy; crude protein of 20%, and water whose pH is calibrated to 7.45 were administered as ad-libitum, to the animals, as metformin source, metformin-HCl was used and as chrome resource, Chromium Picolinate. Trial groups were formed as control group (basal ration), metformin group (basal ration, added metformin at the level of fodder of 20 mg/kg), and chromium picolinate group (basal ration, added fodder of 1500 ppb Cr. When regarded to the results of performance at the end of trial, it is seen that live weight gain, fodder consumption, egg weight, fodder evaluation coefficient, and egg production were affected at the significant level (p < 0.05). When the results are evaluated in terms of incubation features at the end of trial, it was identified that incubation yield and hatchability are not affected by the treatments but in the groups, in which metformin and chromium picolinate are added to ration, that fertility rose at the significant level compared to control group (p < 0,05). According to the results of blood parameters and hormone at the end of the trial, while the level of plasma glucose level was not affected by treatments (p > 0.05), with the addition of metformin and chromium picolinate to ration, plasma, total control, cholesterol, HDL, LDL, and triglyceride levels were significantly affected from insulin receptor stimulators added to ration (p<0,05). Hormone level of Plasma T3 and T4 were also affected at the significant level from insulin receptor stimulators added to ration (p < 0,05).

Keywords: cholesterol, chromium picolinate, hormone, metformin, performance, quail

Procedia PDF Downloads 189
830 Identification of Bioactive Metabolites from Ficus carica and Their Neuroprotective Effects of Alzheimer's Disease

Authors: Hanan Khojah, RuAngelie Edrada-Ebel

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Neurodegenerative disease including Alzheimer’s disease is a major cause of long-term disability. Oxidative stress is frequently implicated as one of the key contributing factors to neurodegenerative diseases. Protection against neuronal damage remains a great challenge for researchers. Ficus carica (commonly known as fig) is a species of great antioxidant nutritional value comprising a protective mechanism against innumerable health disorders related to oxidative stress as well as Alzheimer’s disease. The purpose of this work was to characterize the non-polar active metabolites in Ficus carica endocarp, mesocarp, and exocarp. Crude extracts were prepared using several extraction solvents, which included 1:1 water: ethylacetate, acetone and methanol. The dried extracts were then solvent partitioned between equivalent amounts of water and ethylacetate. Purification and fractionation were accomplished by high-throughput chromatography. The isolated metabolites were tested on their effect on human neuroblastoma cell line by cell viability test and cell cytotoxicity assay with acrolein. Molecular weights of the active metabolites were determined via LC–HRESIMS and GC-EIMS. Metabolomic profiling was performed to identify the active metabolites by using differential expression analysis software (Mzmine) and SIMCA for multivariate analysis. Structural elucidation and identification of the interested active metabolites were studied by 1-D and 2-D NMR. Significant differences in bioactivity against a concentration-dependent assay on acrolein radicals were observed between the three fruit parts. However, metabolites obtained from mesocarp and the endocarp demonstrated bioactivity to scavenge ROS radical. NMR profiling demonstrated that aliphatic compounds such as γ-sitosterol tend to induce neuronal bioactivity and exhibited bioactivity on the cell viability assay. γ-Sitosterol was found in higher concentrations in the mesocarp and was considered as one of the major phytosterol in Ficus carica.

Keywords: alzheimer, Ficus carica, γ-Sitosterol, metabolomics

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829 An Enzyme Technology - Metnin™ - Enables the Full Replacement of Fossil-Based Polymers by Lignin in Polymeric Composites

Authors: Joana Antunes, Thomas Levée, Barbara Radovani, Anu Suonpää, Paulina Saloranta, Liji Sobhana, Petri Ihalainen

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Lignin is an important component in the exploitation of lignocellulosic biomass. It has been shown that within the next years, the yield of added-value lignin-based chemicals and materials will generate renewable alternatives to oil-based products (e.g. polymeric composites, resins and adhesives) and enhance the economic feasibility of biorefineries. In this paper, a novel technology for lignin valorisation (METNIN™) is presented. METNIN™ is based on the oxidative action of an alkaliphilic enzyme in aqueous alkaline conditions (pH 10-11) at mild temperature (40-50 °C) combined with a cascading membrane operation, yielding a collection of lignin fractions (from oligomeric down to mixture of tri-, di- and monomeric units) with distinct molecular weight distribution, low polydispersity and favourable physicochemical properties. The alkaline process conditions ensure the high processibility of crude lignin in an aqueous environment and the efficiency of the enzyme, yielding better compatibility of lignin towards targeted applications. The application of a selected lignin fraction produced by METNIN™ as a suitable lignopolyol to completely replace a commercial polyol in polyurethane rigid foam formulations is presented as a prototype. Liquid lignopolyols with a high lignin content were prepared by oxypropylation and their full utilization in the polyurethane rigid foam formulation was successfully demonstrated. Moreover, selected technical specifications of different foam demonstrators were determined, including closed cell count, water uptake and compression characteristics. These specifications are within industrial standards for rigid foam applications. The lignin loading in the lignopolyol was a major factor determining the properties of the foam. In addition to polyurethane foam demonstrators, other examples of lignin-based products related to resins and sizing applications will be presented.

Keywords: enzyme, lignin valorisation, polyol, polyurethane foam

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828 Ensemble of Deep CNN Architecture for Classifying the Source and Quality of Teff Cereal

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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827 Deep Learning and Accurate Performance Measure Processes for Cyber Attack Detection among Web Logs

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 192
826 Emotion Classification Using Recurrent Neural Network and Scalable Pattern Mining

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 150
825 A phytochemical and Biological Study of Viscum schemperi Engl. Growing in Saudi Arabia

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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824 Aspect-Level Sentiment Analysis with Multi-Channel and Graph Convolutional Networks

Authors: Jiajun Wang, Xiaoge Li

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

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

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823 Use of Fabric Phase Sorptive Extraction with Gas Chromatography-Mass Spectrometry for the Determination of Organochlorine Pesticides in Various Aqueous and Juice Samples

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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822 α-Amylase Inhibitory Activity of Some Tunisian Aromatic and Medicinal Plants

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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821 Using Bidirectional Encoder Representations from Transformers to Extract Topic-Independent Sentiment Features for Social Media Bot Detection

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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820 Phytochemical Screening, Antioxidant Activity, Lipid Profile Effect of Citrus reticulata Fruit Peel, Zingiber officinale Rhizome, and Sesamum indicum Seed Extracts

Authors: Samar Saadeldin Abdelmotalab Omer, Ikram Mohammed Eltayeb Elsiddig, Amna Beshir Medani Ahmed, Saad Mohammed Hussein Ayoub

Abstract:

Many herbal medicinal products are considered as potential hypocholesterolemic agents with encouraging safety profiles, however, only a limited amount of clinical research exists to support their efficacy. The present study was designed to compare the antihypercholesterolaemic and antioxidant activities of the crude ethanolic extracts of Citrus reticulata peel, Zingiber officinale rhizome, and Sesamum indicum seeds. Forty-five rats were used throughout the experiment, which were divided into nine groups, five rats in each as follows; normal control group (normal rats fed with standard normal diet), rats fed hypercholesterolemic diet consisting of 1% cholesterol and 10% saturated animal fat, which were further divided into eight groups; hypercholesterolemic control group (rats only fed hypercholesterolemic diet), groups 3,4,5,6,7, and 8 were given Citrus reticulata, Zingiber officinale, and Sesamum indicum ethanolic extracts at doses of (250mg/kg and 500mg/kg, respectively) orally; and group 9 rats were given atorvastatin (0.18mg/kg) orally as a reference antihypercholesterolaemic drug. Blood samples were obtained four weeks following treatment from the retro-orbital venous plexus after fasting overnight from all groups and the lipid profile (serum total cholesterol (TC), high-density-lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and triglycerides levels) was measured and the risk ratio (TC/HDL-C) was assessed. The antioxidant activity of the three plant extracts was determined using DPPH free-radical assay. Results of in vivo and in vitro antihypercholesterolaemic and antioxidant assay, respectively, revealed that the three extracts possess comparable antioxidant and anti-hypercholesterolaemic activities.

Keywords: anti hypercholesterolemic effects, antioxidant activity, HDL, LDL, TC, TGs, citrus reticulata, sesamum indicum, zingiber officinale

Procedia PDF Downloads 447
819 The Occurrence of Clavibacter michiganensis subsp. sepedonicus on Potato in South Sulawesi, Indonesia

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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818 Evalution of Antiurolithiatic Potentials from Cucumis sativus Fruits

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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817 An Analytic Comparison between Arabic and English Prosodies: Poetical Feet and Meters

Authors: Jamil Jafari, Sharafat Karimi

Abstract:

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

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

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816 Detecting Manipulated Media Using Deep Capsule Network

Authors: Joseph Uzuazomaro Oju

Abstract:

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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815 Proposing an Architecture for Drug Response Prediction by Integrating Multiomics Data and Utilizing Graph Transformers

Authors: Nishank Raisinghani

Abstract:

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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814 Nutritional Characteristics, Phytochemical and Antimicrobial Properties Vaccinium Pavifolium (Ericacea) Leaf Protein Concentrates

Authors: Sodamade A., Bolaji K. A.

Abstract:

Problems associated with protein malnutrition are still prevalent in third-world countries, leading to the constant search for plants that could serve as nutrients and medicinal purposes. Huckleberry is one of the plants that has been proven useful locally in the treatment of numerous ailments and diseases. A fresh sample of the plant (Vaccinium pavifolium) was collected from a vegetable garden situated near the Erelu dam of the Emmanuel Alayande College of Education Campus, Oyo. The sample was authenticated at the Forestry Research Institute of Nigeria (FRIN) Ibadan. The leaves of the plant were plucked and processed for leaf protein concentrates before proximate composition, mineral analysis phytochemical and antimicrobial properties were determined using a standard method of analysis. The results of proximate constituents showed; moisture content; 9.89±0.051g/100g, Ash; 3.23±0.12g/100g, crude fat; 3.96±0.11g/100g and 61.27±0.56g/100g of Nitrogen free extractive. The mineral analysis of the sample showed; Mg; 0.081±0.00mg/100g, Ca; 42.30±0.05mg/100g, Na; 27.57±0.09mg/100g, K; 6.81±0.01mg/100g, P; 8.90±0.03mg/100g, Fe; 0.51±0.00mg/100g, Zn; 0.021±0.00mg/100g, Cd; 0.04±0.04mg/100g, Pb; 0.002±0.00mg/100g, Cr; 0.041±0.00mg/100g Cadmium and Mercury were not detected in the sample. The result of phytochemical analysis of leaf protein concentrates of the Huckleberry showed the presence of Alkaloid, Saponin, Flavonoid, Tanin, Coumarin, Steroids, Terpenoids, Cardiac glycosides, Glycosides, Quinones, Anthocyanin, phytosterols, and phenols. Ethanolic extracts of the Vaccinium parvifolium L. leaf protein concentrates showed that it contains bioactive compounds that are capable of combating the following microorganisms; Staphylococcus aureus, Streptococcus pyogenes, Streptococcus faecalis, Pseudomonas aeruginosa, Klebisialae pneumonia and Proteus mirabilis. The results of the analysis of Vaccinium parvifolium L. leaf protein concentrates showed that the sample contains valuable nutrient and mineral constituents, and phytochemical compounds that could make the sample useful for medicinal activities.

Keywords: leaf protein concentrates, vaccinium parvifolium, nutritional characteristics, mineral composition, antimicrobial activity

Procedia PDF Downloads 58