Search results for: antibacterial agent
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1968

Search results for: antibacterial agent

1518 Development and application of Humidity-Responsive Controlled Release Active Packaging Based on Electrospinning Nanofibers and In Situ Growth Polymeric Film in Food preservation

Authors: Jin Yue

Abstract:

Fresh produces especially fruits, vegetables, meats and aquatic products have limited shelf life and are highly susceptible to deterioration. Essential oils (EOs) extracted from plants have excellent antioxidant and broad-spectrum antibacterial activities, and they can play as natural food preservatives. But EOs are volatile, water insoluble, pungent, and easily decomposing under light and heat. Many approaches have been developed to improve the solubility and stability of EOs such as polymeric film, coating, nanoparticles, nano-emulsions and nanofibers. Construction of active packaging film which can incorporate EOs with high loading efficiency and controlled release of EOs has received great attention. It is still difficult to achieve accurate release of antibacterial compounds at specific target locations in active packaging. In this research, a relative humidity-responsive packaging material was designed, employing the electrospinning technique to fabricate a nanofibrous film loaded with a 4-terpineol/β-cyclodextrin inclusion complexes (4-TA/β-CD ICs). Functioning as an innovative food packaging material, the film demonstrated commendable attributes including pleasing appearance, thermal stability, mechanical properties, and effective barrier properties. The incorporation of inclusion complexes greatly enhanced the antioxidant and antibacterial activity of the film, particularly against Shewanella putrefaciens, with an inhibitory efficiency of up to 65%. Crucially, the film realized controlled release of 4-TA under 98% high relative humidity conditions by inducing the plasticization of polymers caused by water molecules, swelling of polymer chains, and destruction of hydrogen bonds within the cyclodextrin inclusion complex. This film with a long-term antimicrobial effect successfully extended the shelf life of Litopenaeus vannamei shrimp to 7 days at 4 °C. To further improve the loading efficiency and long-acting release of EOs, we synthesized the γ-cyclodextrin-metal organic frameworks (γ-CD-MOFs), and then efficiently anchored γ-CD-MOFs on chitosan-cellulose (CS-CEL) composite film by in situ growth method for controlled releasing of carvacrol (CAR). We found that the growth efficiency of γ-CD-MOFs was the highest when the concentration of CEL dispersion was 5%. The anchoring of γ-CD-MOFs on CS-CEL film significantly improved the surface area of CS-CEL film from 1.0294 m2/g to 43.3458 m2/g. The molecular docking and 1H NMR spectra indicated that γ-CD-MOF has better complexing and stabilizing ability for CAR molecules than γ-CD. In addition, the release of CAR reached 99.71±0.22% on the 10th day, while under 22% RH, the release pattern of CAR was a plateau with 14.71 ± 4.46%. The inhibition rate of this film against E. coli, S. aureus and B. cinerea was more than 99%, and extended the shelf life of strawberries to 7 days. By incorporating the merits of natural biopolymers and MOFs, this active packaging offers great potential as a substitute for traditional packaging materials.

Keywords: active packaging, antibacterial activity, controlled release, essential oils, food quality control

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1517 One Step Green Synthesis of Silver Nanoparticles and Their Biological Activity

Authors: Samy M. Shaban, Ismail Aiad, Mohamed M. El-Sukkary, E. A. Soliman, Moshira Y. El-Awady

Abstract:

In situ and green synthesis of cubic and spherical silver nanoparticles were developed using sun light as reducing agent in the presence of newly prepared cationic surfactant which acting as capping agents. The morphology of prepared silver nanoparticle was estimated by transmission electron microscope (TEM) and the size distribution determined by dynamic light scattering (DLS). The hydrophobic chain length of the prepared surfactant effect on the stability of the prepared silver nanoparticles as clear from zeta-potential values. Also by increasing chain length of the used capping agent the amount of formed nanoparticle increase as indicated by increasing the absorbance. Both prepared surfactants and surfactants capping silver nanoparticles showed high antimicrobial activity against gram positive and gram-negative bacteria.

Keywords: photosynthesis, hexaonal shapes, zetapotential, biological activity

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1516 Investigating the Combined Medicinal Effects of Withania Somnifera (Ashwaghandha) and Murraya Koenigii (Curry Pata) in Vitro

Authors: Sadia Roshan, Kulsoom Sughra, Shazia Shamas, Shamaila Irum, Haleema Sadia

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To evaluate synergistic medicinal effects of Withania somnifera (Ashwaghandha) and Murraya koenigii (Curry pata) in vitro. Antimicrobial activity was determined using the disc diffusion method against five bacterial and two fungal strains. The antioxidant activity was evaluated by the DPPH assay. The antidiabetic activity was evaluated by alpha-glucosidase inhibition assay and alpha-amylase inhibition assay. Synergistic antibacterial activity was observed against all the strains of bacteria, either Gram-positive or Gram-negative and fungi under study conditions. The maximum antibacterial activity was displayed by combined extract against E. coli i.e. 26±0.4mm. Maximum antifungal activity was shown by combined extract against Aspergillus niger, i.e., 17.3±0.5mm. The antioxidant activity of the combined extract was also significant. Alpha-glucosidase inhibition and alpha-amylase inhibition assays also showed synergism. Results indicate that Withania somnifera and Murraya koengii have medicinal properties. The combined extract of both plants is more potent than their individual extracts, suggesting that these can work in synergism. The research suggests that different plant extracts could be used in combination to increase their medicinal activities by many folds, thus giving an insight into future use of herbal medication.

Keywords: withania somnifera, murraya koenigii, antimicrobial activity, gram-positive bacetria, gram-negative bacteria

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1515 Agro-Industrial Waste as a Source of Catalyst Production

Authors: Brenda Cecilia Ledesma, Andrea Beltramone

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This work deals with the bio-waste valorization approach for catalyst development, the use of products derived from biomass as raw material and the obtaining of biofuels. In this research, activated carbons were synthesized from the orange peel using different synthesis conditions. With the activated carbons obtained with the best structure and texture, PtIr bimetallic catalysts were prepared. Carbon activation was carried out through a chemical process with phosphoric acid as an activating agent, varying the acid concentration, the ratio substrate/activating agent and time of contact between them. The best support was obtained using a carbonization time of 1 h, the temperature of carbonization of 470oC, the phosphoric acid concentration of 50 wt.% and a BET area of 1429 m2/g. Subsequently, the metallic nanoparticles were deposited in the activated carbon to use the solid as a catalytic material for the hydrogenation of HMF to 2,5-DMF. The catalyst presented an excellent performance for biofuels generation.

Keywords: orange peel, bio-waste valorization, platinum, iridium, 5-hydroxymethylfurfural

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1514 Development of Bioactive Medical Textiles by Immobilizing Nanoparticles at Cotton Fabric

Authors: Munir Ashraf, Shagufta Riaz

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Personal protective equipment (PPE) and bioactive textiles are highly important for the health care of front line hospital workers, patients, and the general population to be safe from highly infectious diseases. This was even more critical in the wake of COVID-19 outbreak. Most of the medical textiles are inactive against various viruses and bacteria, hence there is a need to wash them frequently to avoid the spread of microorganisms. According to survey conducted by the world health organization, more than 500 million people get infected from hospitals, and more than 13 million died due to these hospitals’ acquired deadly diseases. The market available PPE are though effective against the penetration of pathogens and to kill bacteria but, they are not breathable and active against different viruses. Therefore, there was a great need to develop textiles that are not only effective against bacteria, fungi, and viruses but also are comfortable to the medical personnel and patients. In the present study, waterproof breathable, and biologically active textiles were developed using antiviral and antibacterial nanomaterials. These nanomaterials like TiO₂, ZnO, Cu, and Ag were immobilized at the surface of cotton fabric by using different silane coupling agents and electroless deposition that they retained their functionality even after 30 industrial laundering cycles. Afterwards, the treated fabrics were coated with a waterproof breathable film to prevent the permeation of liquid droplets, any particle or microorganisms greater than 80 nm. The developed cotton fabric was highly active against bacteria and viruses. The good durability of nanomaterials at the cotton surface after several industrial washing cycles makes this fabric an ideal candidate for bioactive textiles used in the medical field.

Keywords: antibacterial, antiviral, cotton, durable

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1513 Synthesis, Crystal Structure Characterization, Hirshfeld Surface Analysis and Biological Activities of Two Schiff Base Polymorphs Derived From 2-Aminobenzonitrile

Authors: Nesrine Benarous, Hassiba Bougueria, Nabila Moussa Slimane, Aouatef Cherouana

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Crystal polymorphism is important for the synthesis of more potent and bioactive pharmaceutical compounds, including their different properties, such as packing arrangement and conformation. In fact, polymorphism plays a vital role in drug development. Different parameters affect the crystallization and give their degree of freedom. Severalproperties affected polymorphism, like kinetics, thermodynamics, spectroscopy, and mechanical property. Various techniques are used for characterizing polymorphs, are crystallography, morphology, phase transitions, molecular motion, and chemical environment. In this work, crystal structures of two polymorphs (I and II) of the Schiff base (SB) title compound were prepared by condensation reaction. The crystal structures of both polymorphs were determined by single X-ray analysis. The two polymorphs crystallize in two different space groups: P21/c for I and Pbca for II. The dihedral angles between the two phenyl rings are 4.81º for I and 82.27º for II. Both crystal structures are built on the basis of moderate and weak hydrogen bonds, 𝜋-stacking, and halogen⋯halogeninteractions. On the other hand, Hirshfeld surface (HS) analysis indicates that the most important contributions to the crystal packing for the two polymorphs are from Cl⋯H/H⋯Cl, H⋯H, and N⋯H/H⋯N contacts. These are followed by C⋯H/H⋯C for compound I and C⋯C and by C⋯H/H⋯C contacts for compound II. Afterwards, the in vitro antibacterial activity revealed that the SB have been found effective against G- bacteria Klebsiella pneumonia andG+ bacteria Staphylococcus aureuswith MIC value of14.37μg/mL. Moreover, the SBexhibited moderate toxicity against Brine Shrimp with LC50 value of 44.19μg/mL.

Keywords: polymorph, crystal structure, hirshfeld surface analysis, in vitro antibacterial activity, toxicity

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1512 Prediction of Dubai Financial Market Stocks Movement Using K-Nearest Neighbor and Support Vector Regression

Authors: Abdulla D. Alblooshi

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The stock market is a representation of human behavior and psychology, such as fear, greed, and discipline. Those are manifested in the form of price movements during the trading sessions. Therefore, predicting the stock movement and prices is a challenging effort. However, those trading sessions produce a large amount of data that can be utilized to train an AI agent for the purpose of predicting the stock movement. Predicting the stock market price action will be advantageous. In this paper, the stock movement data of three DFM listed stocks are studied using historical price movements and technical indicators value and used to train an agent using KNN and SVM methods to predict the future price movement. MATLAB Toolbox and a simple script is written to process and classify the information and output the prediction. It will also compare the different learning methods and parameters s using metrics like RMSE, MAE, and R².

Keywords: KNN, ANN, style, SVM, stocks, technical indicators, RSI, MACD, moving averages, RMSE, MAE

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1511 Multi-Pass Shape Drawing Process Design for Manufacturing of Automotive Reinforcing Agent with Closed Cross-Section Shape using Finite Element Method Analysis

Authors: Mok-Tan Ahn, Hyeok Choi, Joon-Hong Park

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Multi-stage drawing process is an important technique for forming a shape that cannot be molded in a single process. multi-stage drawing process in number of passes and the shape of the die are an important factor influencing the productivity and moldability of the product. The number and shape of the multi-path in the mold of the drawing process is very influencing the productivity and moldability of the product. Half angle of the die and mandrel affects the drawing force and it also affects the completion of the final shape. Thus reducing the number of pass and the die shape optimization are necessary to improve the formability of the billet. The purpose of this study, Analyzing the load on the die through the FEM analysis and in consideration of the formability of the material presents a die model.

Keywords: automotive reinforcing agent, multi-pass shape drawing, automotive parts, FEM analysis

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1510 Deep Reinforcement Learning with Leonard-Ornstein Processes Based Recommender System

Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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1509 Comparative Analysis of Reinforcement Learning Algorithms for Autonomous Driving

Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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1508 Ayurvastra: A Study on the Ancient Indian Textile for Healing

Authors: Reena Aggarwal

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The use of textile chemicals in the various pre and post-textile manufacturing processes has made the textile industry conscious of its negative contribution to environmental pollution. Popular environmentally friendly fibers such as recycled polyester and organic cotton have been now increasingly used by fabrics and apparel manufacturers. However, after these textiles or the finished apparel are manufactured, they have to be dyed in the same chemical dyes that are harmful and toxic to the environment. Dyeing is a major area of concern for the environment as well as for people who have chemical sensitivities as it may cause nausea, breathing difficulties, seizures, etc. Ayurvastra or herbal medical textiles are one step ahead of the organic lifestyle, which supports the core concept of holistic well-being and also eliminates the impact of harmful chemicals and pesticides. There is a wide range of herbs that can be used not only for dyeing but also for providing medicinal properties to the textiles like antibacterial, antifungal, antiseptic, antidepressant and for treating insomnia, skin diseases, etc. The concept of herbal dyeing of fabric is to manifest herbal essence in every aspect of clothing, i.e., from production to end-use, additionally to eliminate the impact of harmful chemical dyes and chemicals which are known to result in problems like skin rashes, headache, trouble concentrating, nausea, diarrhea, fatigue, muscle and joint pain, dizziness, difficulty breathing, irregular heartbeat and seizures. Herbal dyeing or finishing on textiles will give an extra edge to the textiles as it adds an extra function to the fabric. The herbal extracts can be applied to the textiles by a simple process like the pad dry cure method and mainly acts on the human body through the skin for aiding in the treatment of disease or managing the medical condition through its herbal properties. This paper, therefore, delves into producing Ayurvastra, which is a perfect amalgamation of cloth and wellness. The aim of the paper is to design and create herbal disposable and non-disposable medical textile products acting mainly topically (through the skin) for providing medicinal properties/managing medical conditions. Keeping that in mind, a range of antifungal socks and antibacterial napkins treated with turmeric and aloe vera were developed, which are recommended for the treatment of fungal and bacterial infections, respectively. Both Herbal Antifungal socks and Antibacterial napkins have proved to be efficient enough in managing and treating fungal and bacterial infections of the skin, respectively.

Keywords: ayurvastra, ayurveda, herbal, pandemic, sustainable

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1507 Adsorption of Reactive Dye Using Entrapped nZVI

Authors: P. Gomathi Priya, M. E. Thenmozhi

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Iron nanoparticles were used to cleanup effluents. This paper involves synthesis of iron nanoparticles chemically by sodium borohydride reduction of ammonium ferrous sulfate solution (FAS). Iron oxide nanoparticles have lesser efficiency of adsorption than Zero Valent Iron nanoparticles (nZVI). Glucosamine acts as a stabilizing agent and chelating agent to prevent Iron nanoparticles from oxidation. nZVI particles were characterized using Scanning Electron Microscopy (SEM). Thus, the synthesized nZVI was subjected to entrapment in biopolymer, viz. barium (Ba)-alginate beads. The beads were characterized using SEM. Batch dye degradation studies were conducted using Reactive black Water soluble Nontoxic Natural substances (WNN) dye which is one of the most hazardous dyes used in textile industries. Effect of contact time, effect of pH, initial dye concentration, adsorbent dosage, isotherm and kinetic studies were carried out.

Keywords: ammonium ferrous sulfate solution, barium, alginate beads, reactive black WNN dye, zero valent iron nanoparticles

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1506 Interaction between Space Syntax and Agent-Based Approaches for Vehicle Volume Modelling

Authors: Chuan Yang, Jing Bie, Panagiotis Psimoulis, Zhong Wang

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Modelling and understanding vehicle volume distribution over the urban network are essential for urban design and transport planning. The space syntax approach was widely applied as the main conceptual and methodological framework for contemporary vehicle volume models with the help of the statistical method of multiple regression analysis (MRA). However, the MRA model with space syntax variables shows a limitation in vehicle volume predicting in accounting for the crossed effect of the urban configurational characters and socio-economic factors. The aim of this paper is to construct models by interacting with the combined impact of the street network structure and socio-economic factors. In this paper, we present a multilevel linear (ML) and an agent-based (AB) vehicle volume model at an urban scale interacting with space syntax theoretical framework. The ML model allowed random effects of urban configurational characteristics in different urban contexts. And the AB model was developed with the incorporation of transformed space syntax components of the MRA models into the agents’ spatial behaviour. Three models were implemented in the same urban environment. The ML model exhibit superiority over the original MRA model in identifying the relative impacts of the configurational characters and macro-scale socio-economic factors that shape vehicle movement distribution over the city. Compared with the ML model, the suggested AB model represented the ability to estimate vehicle volume in the urban network considering the combined effects of configurational characters and land-use patterns at the street segment level.

Keywords: space syntax, vehicle volume modeling, multilevel model, agent-based model

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1505 Buffer Allocation and Traffic Shaping Policies Implemented in Routers Based on a New Adaptive Intelligent Multi Agent Approach

Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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1504 Semantic Platform for Adaptive and Collaborative e-Learning

Authors: Massra M. Sabeima, Myriam lamolle, Mohamedade Farouk Nanne

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Adapting the learning resources of an e-learning system to the characteristics of the learners is an important aspect to consider when designing an adaptive e-learning system. However, this adaptation is not a simple process; it requires the extraction, analysis, and modeling of user information. This implies a good representation of the user's profile, which is the backbone of the adaptation process. Moreover, during the e-learning process, collaboration with similar users (same geographic province or knowledge context) is important. Productive collaboration motivates users to continue or not abandon the course and increases the assimilation of learning objects. The contribution of this work is the following: we propose an adaptive e-learning semantic platform to recommend learning resources to learners, using ontology to model the user profile and the course content, furthermore an implementation of a multi-agent system able to progressively generate the learning graph (taking into account the user's progress, and the changes that occur) for each user during the learning process, and to synchronize the users who collaborate on a learning object.

Keywords: adaptative learning, collaboration, multi-agent, ontology

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1503 Development of Multifunctional Yarns and Fabrics for Interactive Textiles

Authors: Muhammad Bilal Qadir, Danish Umer, Amir Shahzad

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The use of conductive materials in smart and interactive textiles is gaining significant importance for creating value addition, innovation, and functional product development. These products find their potential applications in health monitoring, military, protection, communication, sensing, monitoring, actuation, fashion, and lifestyles. The materials which are most commonly employed in such type of interactive textile include intrinsically conducting polymers, conductive inks, and metallic coating on textile fabrics and inherently conducting metallic fibre yarns. In this study, silver coated polyester filament yarn is explored for the development of multifunctional interactive gloves. The composite yarn was developed by covering the silver coated polyester filament around the polyester spun yarn using hollow spindle technique. The electrical and tensile properties of the yarn were studied. This novel yarn was used to manufacture a smart glove to explore the antibacterial, functional, and interactive properties of the yarn. The change in electrical resistance due to finger movement at different bending positions and antimicrobial properties were studied. This glove was also found useful as an interactive tool to operate the commonly used touch screen devices due to its conductive nature. The yarn can also be used to develop the sensing elements like stretch, strain, and piezoresistive sensors. Such sensor can be effectively used in medical and sports textile for performance monitoring, vital signs monitoring and development of antibacterial textile for healthcare and hygiene.

Keywords: conductive yarn, interactive textiles, piezoresistive sensors, smart gloves

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1502 An Agent-Based Model of Innovation Diffusion Using Heterogeneous Social Interaction and Preference

Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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1501 Fabrication of Antimicrobial Dental Model Using Digital Light Processing (DLP) Integrated with 3D-Bioprinting Technology

Authors: Rana Mohamed, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Bio-fabrication is a multidisciplinary research field that combines several principles, fabrication techniques, and protocols from different fields. The open-source-software movement is a movement that supports the use of open-source licenses for some or all software as part of the broader notion of open collaboration. Additive manufacturing is the concept of 3D printing, where it is a manufacturing method through adding layer-by-layer using computer-aided designs (CAD). There are several types of AM system used, and they can be categorized by the type of process used. One of these AM technologies is Digital light processing (DLP) which is a 3D printing technology used to rapidly cure a photopolymer resin to create hard scaffolds. DLP uses a projected light source to cure (Harden or crosslinking) the entire layer at once. Current applications of DLP are focused on dental and medical applications. Other developments have been made in this field, leading to the revolutionary field 3D bioprinting. The open-source movement was started to spread the concept of open-source software to provide software or hardware that is cheaper, reliable, and has better quality. Objective: Modification of desktop 3D printer into 3D bio-printer and the integration of DLP technology and bio-fabrication to produce an antibacterial dental model. Method: Modification of a desktop 3D printer into a 3D bioprinter. Gelatin hydrogel and sodium alginate hydrogel were prepared with different concentrations. Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum were extracted, and extractions were selected on different levels (Powder, aqueous extracts, total oils, and Essential oils) prepared for antibacterial bioactivity. Agar well diffusion method along with the E. coli have been used to perform the sensitivity test for the antibacterial activity of the extracts acquired by Zingiber officinale, Syzygium aromaticum, and Allium sativum. Lastly, DLP printing was performed to produce several dental models with the natural extracted combined with hydrogel to represent and simulate the Hard and Soft tissues. Result: The desktop 3D printer was modified into 3D bioprinter using open-source software Marline and modified custom-made 3D printed parts. Sodium alginate hydrogel and gelatin hydrogel were prepared at 5% (w/v), 10% (w/v), and 15%(w/v). Resin integration with the natural extracts of Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum was done following the percentage 1- 3% for each extract. Finally, the Antimicrobial dental model was printed; exhibits the antimicrobial activity, followed by merging with sodium alginate hydrogel. Conclusion: The open-source movement was successful in modifying and producing a low-cost Desktop 3D Bioprinter showing the potential of further enhancement in such scope. Additionally, the potential of integrating the DLP technology with bioprinting is a promising step toward the usage of the antimicrobial activity using natural products.

Keywords: 3D printing, 3D bio-printing, DLP, hydrogel, antibacterial activity, zingiber officinale, syzygium aromaticum, allium sativum, panax ginseng, dental applications

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1500 Voting Representation in Social Networks Using Rough Set Techniques

Authors: Yasser F. Hassan

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Social networking involves use of an online platform or website that enables people to communicate, usually for a social purpose, through a variety of services, most of which are web-based and offer opportunities for people to interact over the internet, e.g. via e-mail and ‘instant messaging’, by analyzing the voting behavior and ratings of judges in a popular comments in social networks. While most of the party literature omits the electorate, this paper presents a model where elites and parties are emergent consequences of the behavior and preferences of voters. The research in artificial intelligence and psychology has provided powerful illustrations of the way in which the emergence of intelligent behavior depends on the development of representational structure. As opposed to the classical voting system (one person – one decision – one vote) a new voting system is designed where agents with opposed preferences are endowed with a given number of votes to freely distribute them among some issues. The paper uses ideas from machine learning, artificial intelligence and soft computing to provide a model of the development of voting system response in a simulated agent. The modeled development process involves (simulated) processes of evolution, learning and representation development. The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of structure. We employ agent-based computer simulation to demonstrate the formation and interaction of coalitions that arise from individual voter preferences. We are interested in coordinating the local behavior of individual agents to provide an appropriate system-level behavior.

Keywords: voting system, rough sets, multi-agent, social networks, emergence, power indices

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1499 Prediction of Antibacterial Peptides against Propionibacterium acnes from the Peptidomes of Achatina fulica Mucus Fractions

Authors: Suwapitch Chalongkulasak, Teerasak E-Kobon, Pramote Chumnanpuen

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Acne vulgaris is a common skin disease mainly caused by the Gram–positive pathogenic bacterium, Propionibacterium acnes. This bacterium stimulates inflammation process in human sebaceous glands. Giant African snail (Achatina fulica) is alien species that rapidly reproduces and seriously damages agricultural products in Thailand. There were several research reports on the medical and pharmaceutical benefits of this snail mucus peptides and proteins. This study aimed to in silico predict multifunctional bioactive peptides from A. fulica mucus peptidome using several bioinformatic tools for determination of antimicrobial (iAMPpred), anti–biofilm (dPABBs), cytotoxic (Toxinpred), cell membrane penetrating (CPPpred) and anti–quorum sensing (QSPpred) peptides. Three candidate peptides with the highest predictive score were selected and re-designed/modified to improve the required activities. Structural and physicochemical properties of six anti–P. acnes (APA) peptide candidates were performed by PEP–FOLD3 program and the five aforementioned tools. All candidates had random coiled structure and were named as APA1–ori, APA2–ori, APA3–ori, APA1–mod, APA2–mod and APA3–mod. To validate the APA activity, these peptide candidates were synthesized and tested against six isolates of P. acnes. The modified APA peptides showed high APA activity on some isolates. Therefore, our biomimetic mucus peptides could be useful for preventing acne vulgaris and further examined on other activities important to medical and pharmaceutical applications.

Keywords: Propionibacterium acnes, Achatina fulica, peptidomes, antibacterial peptides, snail mucus

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1498 Ultrasound-Assisted Extraction of Bioactive Compounds from Cocoa Shell and Their Encapsulation in Gum Arabic and Maltodextrin: A Technology to Produce Functional Food Ingredients

Authors: Saeid Jafari, Khursheed Ahmad Sheikh, Randy W. Worobo, Kitipong Assatarakul

Abstract:

In this study, the extraction of cocoa shell powder (CSP) was optimized, and the optimized extracts were spray-dried for encapsulation purposes. Temperature (45-65 ◦C), extraction time (30–60 min), and ethanol concentration (60–100%) were the extraction parameters. The response surface methodology analysis revealed that the model was significant (p ≤ 0.05) in interactions between all variables (total phenolic compound, total flavonoid content, and antioxidant activity as measured by 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP assays), with a lack of fit test for the model being insignificant (p > 0.05). Temperature (55 ◦C), time (45 min), and ethanol concentration (60%) were found to be the optimal extraction conditions. For spray-drying encapsulation, some quality metrics (e.g., water solubility, water activity) were insignificant (p > 0.05). The microcapsules were found to be spherical in shape using a scanning electron microscope. Thermogravimetric and differential thermogravimetric measurements of the microcapsules revealed nearly identical results. The gum arabic + maltodextrin microcapsule (GMM) showed potential antibacterial (zone of inhibition: 11.50 mm; lower minimum inhibitory concentration: 1.50 mg/mL) and antioxidant (DPPH: 1063 mM trolox/100g dry wt.) activities (p ≤ 0.05). In conclusion, the microcapsules in this study, particularly GMM, are promising antioxidant and antibacterial agents to be fortified as functional food ingredients for the production of nutraceutical foods with health-promoting properties.

Keywords: functional foods, coco shell powder, antioxidant activity, encapsulation, extraction

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1497 Modeling Influence on Petty Corruption Attitudes

Authors: Nina Bijedic, Drazena Gaspar, Mirsad Hadzikadic

Abstract:

Corruption is an influential and widespread problem. One part of it is so-called petty corruption, related to large-scale bribe giving by ordinary citizens trying to influence the works of public administration or public services. As it is with all means of corruption, petty corruption is related to the level of democracy (or administration efficiency) in a society. The developed model captures some of the factors related to corruptive behavior, as well as people’s attitude towards petty corruption. It has four basic elements: user’s perception of corruption in the society of interest, the influence of social interactions, the influence of penalizing mechanism, and influence of campaigns against petty corruption. The model is agent-based, developed in NetLogo, with a lot of random settings that provide a wider scope of responses. Interactions of different settings for variables of elements provide insight into the influence of each element on attitude towards petty corruption, as well as petty corruptive behavior.

Keywords: agent-based model, attitude, influence, petty corruption, society

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1496 Comparative Study of Antimicrobial Activity of Bacteriocin Producing Lactic Acid Bacteria from Fermented Batter of Green Gram And Bengal Gram Against Food-Borne Pathogens

Authors: Bandi Aruna

Abstract:

The increase of multidrug-resistant pathogens and the restriction on the use of antibiotics due to its side effects have drawn attention to the search for possible alternatives. Bacteriocins are ribosomally synthesized antimicrobial peptides that are active against Gram-positive and Gram-negative bacteria. The bacteriocins from lactic acid bacteria represent an important application of these peptides as clinical drugs or as food biopreservatives. The present study describes the isolation of bacteriocin producing lactic acid bacteria (LAB) from fermented batter of green gram and bengal gram using Man, Rogosa and Sharpe (MRS) media. The bacteriocin produced by these organisms inhibited the growth of Staphylococcus aureus, Escherichia coli, Klebsiella species, Pseudomonas aeruginosa, The isolates G1, G2 were isolated from green gram; B1 and B2 were isolated from fermented bengal gram batter. G1 and G2 were identified as Lactobacillus casie and B1 and B2 were identified as Streptococcus species. Antimicrobial activity of the bacteriocin produced by these strains was studied by agar well diffusion method. Bacteriocins produced by the Lactobacillus casie and Streptococcus secies retained their antagonistic property at pH of 5 and pH of 7. Exposure of bacteriocin to UV light for 4 min showed antibacterial activity. The antagonistic property was observed even at 100°C demonstrating stability at higher temperatures of the bacteriocin. The bacteriocins were stable for a period of 15 days at 27°C. The bacteriocins of G1, G2, and B2 exhibited highest antagonistic activity at pH of 5 and B1 at pH of 7. Therefore, the bacteriocins of the isolates may find important application in controlling the food-borne pathogens.

Keywords: Keywords: Antibacterial activity, Lactic acid bacteria, Bacteriocin

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1495 Freight Forwarders’ Liability: A Need for Revival of Unidroit Draft Convention after Six Decades

Authors: Mojtaba Eshraghi Arani

Abstract:

The freight forwarders, who are known as the Architect of Transportation, play a vital role in the supply chain management. The package of various services which they provide has made the legal nature of freight forwarders very controversial, so that they might be qualified once as principal or carrier and, on other occasions, as agent of the shipper as the case may be. They could even be involved in the transportation process as the agent of shipping line, which makes the situation much more complicated. The courts in all countries have long had trouble in distinguishing the “forwarder as agent” from “forwarder as principal” (as it is outstanding in the prominent case of “Vastfame Camera Ltd v Birkart Globistics Ltd And Others” 2005, Hong Kong). It is not fully known that in the case of a claim against the forwarder, what particular parameter would be used by the judge among multiple, and sometimes contradictory, tests for determining the scope of the forwarder liability. In particular, every country has its own legal parameters for qualifying the freight forwarders that is completely different from others, as it is the case in France in comparison with Germany and England. The unpredictability of the courts’ decisions in this regard has provided the freight forwarders with the opportunity to impose any limitation or exception of liability while pretending to play the role of a principal, consequently making the cargo interests incur ever-increasing damage. The transportation industry needs to remove such uncertainty by unifying national laws governing freight forwarders liability. A long time ago, in 1967, The International Institute for Unification of Private Law (UNIDROIT) prepared a draft convention called “Draft Convention on Contract of Agency for Forwarding Agents Relating to International Carriage of Goods” (hereinafter called “UNIDROIT draft convention”). The UNIDROIT draft convention provided a clear and certain framework for the liability of freight forwarder in each capacity as agent or carrier, but it failed to transform to a convention, and eventually, it was consigned to oblivion. Today, after nearly 6 decades from that era, the necessity of such convention can be felt apparently. However, one might reason that the same grounds, in particular, the resistance by forwarders’ association, FIATA, exist yet, and thus it is not logical to revive a forgotten draft convention after such long period of time. It is argued in this article that the main reason for resisting the UNIDROIT draft convention in the past was pending efforts for developing the “1980 United Nation Convention on International Multimodal Transport of Goods”. However, the latter convention failed to become in force on due time in a way that there was no new accession since 1996, as a result of which the UNIDROIT draft convention must be revived strongly and immediately submitted to the relevant diplomatic conference. A qualitative method with the concept of interpretation of data collection has been used in this manuscript. The source of the data is the analysis of international conventions and cases.

Keywords: freight forwarder, revival, agent, principal, uidroit, draft convention

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1494 Protein and Lipid Extraction from Microalgae with Ultrasound Assisted Osmotic Shock Method

Authors: Nais Pinta Adetya, H. Hadiyanto

Abstract:

Microalgae has a potential to be utilized as food and natural colorant. The microalgae components consists of three main parts, these are lipid, protein, and carbohydrate. Crucial step in producing lipid and protein from microalgae is extraction. Microalgae has high water level (70-90%), it causes drying process of biomass needs much more energy and also has potential to distract lipid and protein from microalgae. Extraction of lipid from wet biomass is able to take place efficiently with cell disruption of microalgae by osmotic shock method. In this study, osmotic shock method was going to be integrated with ultrasound to maximalize the extraction yield of lipid and protein from wet biomass Spirulina sp. with osmotic shock method assisted ultrasound. This study consisted of two steps, these were osmotic shock process toward wet biomass and ultrasound extraction assisted. NaCl solution was used as osmotic agent, with the variation of concentrations were 10%, 20%, and 30%. Extraction was conducted in 40°C for 20 minutes with frequency of ultrasound wave was 40kHz. The optimal yield of protein (2.7%) and (lipid 38%) were achieved at 20% osmotic agent concentration.

Keywords: extraction, lipid, osmotic shock, protein, ultrasound

Procedia PDF Downloads 331
1493 Antimicrobial Activity of Fatty Acid Salts against Microbes for Food Safety

Authors: Aya Tanaka, Mariko Era, Manami Masuda, Yui Okuno, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

Abstract:

Objectives— Fungi and bacteria are present in a wide range of natural environments. They are breed in the foods such as vegetables and fruit, causing corruption and deterioration of these foods in some cases. Furthermore, some species of fungi and bacteria are known to cause food intoxication or allergic reactions in some individuals. To prevent fungal and bacterial contamination, various fungicides and bactericidal have been developed that inhibit fungal and bacterial growth. Fungicides and bactericides must show high antifungal and antibacterial activity, sustainable activity, and a high degree of safety. Therefore, we focused on the fatty acid salt which is the main component of soap. We focused on especially C10K and C12K. This study aimed to find the effectiveness of the fatty acid salt as antimicrobial agents for food safety. Materials and Methods— Cladosporium cladosporioides NBRC 30314, Penicillium pinophilum NBRC 6345, Aspergillus oryzae (Akita Konno store), Rhizopus oryzae NBRC 4716, Fusarium oxysporum NBRC 31631, Escherichia coli NBRC 3972, Bacillus subtilis NBRC 3335, Staphylococcus aureus NBRC 12732, Pseudomonas aenuginosa NBRC 13275 and Serratia marcescens NBRC 102204 were chosen as tested fungi and bacteria. Hartmannella vermiformis NBRC 50599 and Acanthamoeba castellanii NBRC 30010 were chosen as tested amoeba. Nine fatty acid salts including potassium caprate (C10K) and laurate (C12K) at 350 mM and pH 10.5 were used as antifungal activity. The spore suspension of each fungus (3.0×10⁴ spores/mL) or the bacterial suspension (3.0×10⁵ or 3.0×10⁶ or 3.0×10⁷ CFU/mL) was mixed with each of the fatty acid salts (final concentration of 175 mM). Samples were counted at 0, 10, 60, and 180 min by plating (100 µL) on potato dextrose agar or nutrient agar. Fungal and bacterial colonies were counted after incubation for 1 or 2 days at 30 °C. Results— C10K was antifungal activity of 4 log-unit incubated time for 10 min against fungi other than A. oryzae. C12K was antifungal activity of 4 log-unit incubated time for 10 min against fungi other than P. pinophilum and A. oryzae. C10K and C12K did not show high anti-yeast activity. C10K was antibacterial activity of 6 or 7 log-unit incubated time for 10 min against bacteria other than B. subtilis. C12K was antibacterial activity of 5 to 7 log-unit incubated time for 10 min against bacteria other than S. marcescens. C12K was anti-amoeba activity of 4 log-unit incubated time for 10 min against H. vermiformis. These results suggest C10K and C12K have potential in the field of food safety.

Keywords: food safety, microbes, antimicrobial, fatty acid salts

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1492 Relation between Electrical Properties and Application of Chitosan Nanocomposites

Authors: Evgen Prokhorov, Gabriel Luna-Barcenas

Abstract:

The polysaccharide chitosan (CS) is an attractive biopolymer for the stabilization of several nanoparticles in acidic aqueous media. This is due in part to the presence of abundant primary NH2 and OH groups which may lead to steric or chemical stabilization. Applications of most CS nanocomposites are based upon the interaction of high surface area nanoparticles (NPs) with different substance. Therefore, agglomeration of NPs leads to decreasing effective surface area such that it may decrease the efficiency of nanocomposites. The aim of this work is to measure nanocomposite’s electrical conductivity phenomena that will allow one to formulate optimal concentrations of conductivity NPs in CS-based nanocomposites. Additionally, by comparing the efficiency of such nanocomposites, one can guide applications in the biomedical (antibacterial properties and tissue regeneration) and sensor fields (detection of copper and nitrate ions in aqueous solutions). It was shown that the best antibacterial (CS-AgNPs, CS-AgNPs-carbon nanotubes) and would healing properties (CS-AuNPs) are observed in nanocomposites with concentrations of NPs near the percolation threshold. In this regard, the best detection limit in potentiometric and impedimetric sensors for detection of copper ions (using CS-AuNPs membrane) and nitrate ions (using CS-clay membrane) in aqueous solutions have been observed for membranes with concentrations of NPs near percolation threshold. It is well known that at the percolation concentration of NPs an abrupt increasing of conductivity is observed due to the presence of physical contacts between NPs; above this concentration, agglomeration of NPs takes place such that a decrease in the effective surface and performance of nanocomposite appear. The obtained relationship between electrical percolation threshold and performance of polymer nanocomposites with conductivity NPs is important for the design and optimization of polymer-based nanocomposites for different applications.

Keywords: chitosan, conductivity nanoparticles, percolation threshold, polymer nanocomposites

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1491 Mobile Application Set to Empower SME Farmers in Peri-Urban Sydney Region

Authors: A. Hol

Abstract:

Even in the well developed countries like Australia, Small to Medium Farmers do not often have the power over the market prices as they are more often than not set by the farming agents. This in turn creates problems as farmers only get to know for how much their produce has been sold for by the agents three to four weeks after the sale has taken the place. To see and identify if and how peri-urban Sydney farmers could be assisted, carefully selected group of peri-urban Sydney farmers of the stone fruit has been interviewed. Following the case based interviews collected data was analyzed in detail using the Scenario Based Transformation principles. Analyzed data was then used to create a most common transformation case. The case identified that a mobile web based system could be develop so that framers can monitor agent earnings and in turn gain more power over the markets. It is expected that after the system has been in action for six months to a year, farmers will become empowered and they will gain means to monitor the market and negotiate agent prices.

Keywords: mobile applications, farming, scenario-based analysis, scenario-based transformation, user empowerment

Procedia PDF Downloads 365
1490 An Artificially Intelligent Teaching-Agent to Enhance Learning Interactions in Virtual Settings

Authors: Abdulwakeel B. Raji

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This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

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1489 Identification of Phenolic Compounds and Study the Antimicrobial Property of Eleaocarpus Ganitrus Fruits

Authors: Velvizhi Dharmalingam, Rajalaksmi Ramalingam, Rekha Prabhu, Ilavarasan Raju

Abstract:

Background: The use of herbal products for various therapeutic regimens has increased tremendously in the developing countries. Elaeocarpus ganitrus(Rudraksha) is a broad-leaved tree, belonging to the family Elaeocarpaceae found in tropical and subtropical areas. It is popular in an indigenous system of medicine like Ayurveda, Siddha, and Unani. According to Ayurvedic medicine, Rudraksha is used in the managing of blood pressure, asthma, mental disorders, diabetes, gynaecological disorders, neurological disorders such as epilepsy and liver diseases. Objectives: The present study aimed to study the physicochemical parameters of Elaeocarpus ganitrus(fruits) and identify the phenolic compounds (gallic acid, ellagic acid, and chebulinic acid). To estimate the microbial load and the antibacterial activity of extract of Elaeocarpus ganitrus for selective pathogens. Methodology: The dried powdered fruit of Elaeocarpus ganitrus was performed the physicochemical parameters (such as Loss on drying, Alcohol soluble extractive, Water soluble extractive, Total ash and Acid insoluble ash) and pH was measured. The dried coarse powdered fruit of Elaeocarpus ganitrus was extracted successively with hexane, chloroform, ethylacetate and aqueous alcohol by cold percolation method. Identification of phenolic compounds (gallic acid, ellagic acid, chebulinic acid) was done by HPTLC method and confirmed by co-TLC using different solvent system.The successive extracts of Elaeocarpus ganitrus and standards (like gallic acid, ellagic acid, and chebulinic acid) was approximately weighed and made up with alcohol. HPTLC (CAMAG) analysis was performed on a TLC over silica gel 60F254 precoated aluminium plate, layer thickness 0.2 mm (E.Merck, Germany) by using ATS4, Visualizer and Scanner with wavelength at 254 nm, 366 nm and derivatized with different reagents. The microbial load such as total bacterial count, total fungal count, Enterobacteria, Escherichia coli, Salmonella species, Staphylococcus aureus and Pseudomonas aeruginosa by serial dilution method and antibacterial activity of was measured by Kirby bauer method for selective pathogens. Results: The physicochemical parameter of Elaeocarpus ganitrus was studied for standardization of crude drug. Among all the successive extracts were identified with phenolic compounds and Elaeocarpus ganitrus extract having potent antibacterial activity against gram-positive and gram-negative bacteria.

Keywords: antimicrobial activity, Elaeocarpus ganitrus, HPTLC, phenolic compounds

Procedia PDF Downloads 323