Search results for: emerging agent

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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Authors: Anushaa A.

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In this work, silver nanoparticles (AgNP) were manufactured directly without harmful chemicals utilising methanol extract (SNLME) Solanum nigrume leaves. We are using nigrum leaf extract from Solanum, which converts silver nitrate to silver ions, for synthesization purposes. An examination of the AgNP produced was performed using ultraviolet (UV-VIS) spectroscopy, infrared spectroscopy (FTIR) transformed from Fourier and scanning electrons (SEM). Biological activity was also tested. UV-VIS has proven that biosynthesized AgNP exists (420-450 nm). The FTIR spectrum has been utilised to confirm the presence of different functional groups within the biomolecules, which are a nanoparticular capping agent and the spectroscopic and crystal nature of AgNP. The viability of the silver nanoparticles was evaluated using zeta potential calculations. Negative zeta potential of -33.4 mV demonstrated the stability of silver-nanoparticles. The morphology of AgNP was examined using a scanning electron microscope. Greenly generated AgNP showed significant anti-Staphylococcus aureus, Candida, and Escherichia coli action. The green AgNP demonstration indicated that the IC50 for the human teratocarcinoma cell line was 29.24 μg/ml during 24 hours of therapy (PA1 Ovarian cell line). The dose-dependent effects were reported in both antibacterial and cytotoxicity assays and as an effective agent. Finally, the findings of this research showed that silver nanoparticles generated might serve as a viable therapeutic agent to combat microorganisms killing and curing cancer.

Keywords: antimicrobial activity, PA1 ovarian cancer cell line, silver nanoparticles, Solanum nigrum

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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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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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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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Authors: Kai Zhu, Shanhua He, Yujiao Chang

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This paper explores the virtual linguistic landscape of an emerging virtual language community in TikTok, a language community realizing immediate and non-immediate communication without a precise Spatio-temporal domain or a specific socio-cultural boundary or interpersonal network. This kind of language community generates a large number and various forms of virtual linguistic landscape, with which we conducted a virtual ethnographic survey together with telephone interviews to collect data from coping. We have been following two language communities in TikTok for several months so that we can illustrate the composition of the two language communities and some typical virtual language landscapes in both language communities first. Then we try to explore the reasons why and how they are formed through the organization, transcription, and analysis of the interviews. Our analysis reveals the richness and diversity of the virtual linguistic landscape, and finally, we summarize some of the characteristics of this language community.

Keywords: virtual linguistic landscape, virtual language community, virtual ethnographic survey, TikTok

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Authors: Nousheen Tariq Bhutta, Syed Zulfiqar Ali Shah

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Financial crises become a key impediment towards the development of countries especially in emerging economies. Based on standard finance, many researchers investigated the financial crises in different countries in order to find the underlying reason regarding occurrence these event; however they were unable to provide it. In this essence behavioral finance may be helpful in providing answers to some queries regarding occurrence and prevention of financial crises. In this paper, we explore the some psychological factors comprises of our inspiration, emotion, cognition and culture along with their reflection companies, financial markets and governments that present some supportive arguments. Moreover, we compared the views of Keynes and Minsky in order to validate the underling justification towards occurrence of financial crises and their prevention in future. This study helps the practitioners and policy makers through providing valuable recommendation in order to protect the economies.

Keywords: financial crises, behavioral finance, financial markets, emerging economies

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Authors: Mohamed Mahdi Alshahni, Takashi Tamura, Koichi Makimura

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Objective: The objective of this study is to evaluate roles of ABC-type efflux transporters in the resistance of Candida auris against common antifungal agents. Material and Methods: A wild-type C. auris strain and its antifungal resistant derivative strain that is generated through induction by antifungal agents were used in this study. The strains were cultured onto media containing beauvericin alone or in combination with azole agents. Moreover, expression levels of four ABC-type transporter’s homologs in those strains were analyzed by real time PCR with or without antifungal stress by fluconazole or voriconazole. Results: Addition of beauvericin helped to partially restore the susceptibility of the resistant strain against fluconazole, suggesting participation of ABC-type transporters in the resistance mechanism. Real time PCR results showed that mRNA levels of three out of the four analyzed transporters in the resistant strain were more than 2-fold higher than their counterparts in the wild-type strain under negative control and antifungal agent-containing conditions. Conclusion: C. auris is an emerging multidrug-resistant pathogen causing human mortality worldwide. Providing effective treatment has been hampered by the resistance to antifungal drugs, demanding understanding the resistance mechanism in order to devise new therapeutic strategies. Our data suggest a partial contribution of ABC-type transporters to the resistance of this pathogen.

Keywords: resistance, C. auris, transporters, antifungi

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Authors: Charlie Yang

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The idea that business practitioners urgently need a more holistic and humanistic philosophy about the free market economy has gained some attraction among business practitioners and business professors. Those who have endorsed “conscious capitalism” as an emerging business philosophy also contended that business education should be grounded in a more positive understanding of capitalism, which enables future business leaders to have a greater impact on the world. This study is designed to critically examine the theoretical foundations of conscious capitalism and its practical and pedagogical possibilities as an emerging business movement. Based on the analysis of qualitative data collected through reflective essays written by business students, I will discuss the pedagogical and practical implications for developing conscious leadership in the context of more transformative and contemplative management education.

Keywords: conscious capitalism, conscious leadership, contemplative management education, contemplative pedagogy

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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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Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

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Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

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Authors: Mahmoud F. Mohamadin, Ahmed Abdel Malek, Wessam Said

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Achieving energy efficient architecture in general, and in emerging countries in particular, is a challenging process that requires the contribution of various governmental, institutional, and individual entities. The rule of architectural design is essential in this process as it is considered as one of the earliest steps on the road to sustainability. Architectural firms have a moral and professional responsibility to respond to these challenges and deliver buildings that consume less energy. This study aims to evaluate the design processes and tools in practice of Egyptian architectural firms based on a limited survey to investigate if their processes and methods can lead to projects that meet the Egyptian Code of Energy Efficiency Improvement. A case study of twenty architectural firms in Cairo was selected and categorized according to their scale; large-scale, medium-scale, and small-scale. A questionnaire was designed and distributed to the firms, and personal meetings with the firms’ representatives took place. The questionnaire answered three main points; the design processes adopted, the usage of performance-based simulation tools, and the usage of BIM tools for energy efficiency purposes. The results of the study revealed that only little percentage of the large-scale firms have clear strategies for building energy efficiency in their building design, however the application is limited to certain project types, or according to the client request. On the other hand, the percentage of medium-scale firms is much less, and it is almost absent in the small-scale ones. This demonstrates the urgent need of enhancing the awareness of the Egyptian architectural design community of the great importance of implementing these methods starting from the early stages of the building design. Finally, the study proposed recommendations for such firms to be able to create a healthy built environment and improve the quality of life in emerging countries.

Keywords: architectural firms, emerging countries, energy efficiency, performance-based simulation tools

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Authors: Priyanka Gupta, Nilanjana Bairagi, Deepti Gupta

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New pathogenic strains of microbes are continually emerging and resistance of bacteria to antibiotics is growing. Hospitals in India have a high burden of infections in their intensive care units and general wards. Rising incidence of hospital infections is a matter of great concern in India. This growth is often attributed to the absence of effective infection control strategies in healthcare facilities. Government, therefore, is looking for cost effective strategies that are effective against HAIs. One possible method is by application of an antimicrobial finish on the uniform. But there are limited studies to show the effect of antimicrobial activity of antimicrobial finish treated nurses’ uniforms in a real hospital set up. This paper proposes a prospective non-destructive sampling technique, based on the use of a detachable fabric patch, to assess the effectiveness of silver based antimicrobial agent across five wards in a tertiary care government hospital in Delhi, India. Fabrics like polyester and polyester cotton blend fabric which are more prevalent for making coats were selected for the study. Polyester and polyester cotton blend fabric was treated with silver based antimicrobial (AM) finish. At the beginning of shift, a composite patch of untreated and treated fabric respectively was stitched on the abdominal region on the left and right side of the washed white coat of participating nurse. At the end of the shift, the patch was removed and taken for bacterial sampling on Brain Heart Infusion (BHI) plates. Microbial contamination on polyester and blend fabrics after 6 hours shift was compared in Brain Heart Infusion broth (BHI). All patches treated with silver based antimicrobial agent showed decreased bacterial counts. Percent reduction in the bacterial colonies after the antimicrobial treatment in both fabrics was 81.0 %. Antimicrobial finish was equally effective in reducing microbial adhesion on both fabric types. White coats of nurses become progressively contaminated during clinical care. Type of fabric used to make the coat can affect the extent of contamination which is higher on polyester cotton blend as compared to 100% polyester. The study highlights the importance of silver based antimicrobial finish in the area of uniform hygiene. Bacterial load can be reduced by using antimicrobial finish on hospital uniforms. Hospital staff uniforms endowed with antimicrobial properties may be of great help in reducing the occurrence and spread of infections.

Keywords: antimicrobial finish, bacteria, infection control, silver, white coat

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Authors: Lee Soo-Kyoung, Kim Young-Su

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This study established a network related to metabolic syndrome intervention by conducting a social network analysis of titles, keywords, and abstracts, and it identified emerging topics of research. It visualized an interconnection between critical keywords and investigated their frequency of appearance to construe the trends in metabolic syndrome intervention measures used in studies conducted over 38 years (1979–2017). It examined a collection of keywords from 8,285 studies using text rank analyzer, NetMiner 4.0. The analysis revealed 5 groups of newly emerging keywords in the research. By examining the relationship between keywords with reference to their betweenness centrality, the following clusters were identified. Thus if new researchers refer to existing trends to establish the subject of their study and the direction of the development of future research on metabolic syndrome intervention can be predicted.

Keywords: intervention, metabolic syndrome, network analysis, research, the trend

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Authors: E.George, P. Ojeaga, O. Matthew, A. Adekola

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Can foreign direct investment (FDI), promote growth in Africa? What does the inflow of investment hold for African emerging economies? Are the determinants of FDI different for different regional blocs in Africa? This study reviews the implication of FDI for different regional blocs in Africa. FDI was found to have a significant effect on growth in North Africa but had no significant effect in East, Southern and West Africa. FDI was also found not to be driving growth in the whole of Africa in a significant manner. The implications of the findings are that even though trade openness seems to be a major factor driving FDI. Poor domestic markets were still preventing many African economies from taking full advantage of the gains from foreign direct investment. The study results could be useful to scholars who study the dynamics surrounding FDI disbursement and strategies on how FDI can drive growth in developing countries.

Keywords: Africa, political economy, FDI, regional policy, markets

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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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Authors: Alexander Rodríguez-Hernández, Arnulfo Rojas-Perez, Liz Diaz-Vazquez

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The rise in consumerism over the past century has resulted in the creation of higher amounts of plasticizers, personal care products and other chemical substances, which enter and accumulate in water systems. Other sources of pollutants in Neotropical regions experience large inputs of nutrients with these pollutants resulting in eutrophication of water which consume large quantities of oxygen, resulting in high fish mortality. This dilemma has created a need for the development of targeted detection in complex matrices and remediation of emerging contaminants. We have synthesized carbon nanoparticles from macro algae (Ulva fasciata) by oxidizing the graphitic carbon network under extreme acidic conditions. The resulting material was characterized by STEM, yielding a spherical 12 nm average diameter nanoparticles, which can be fixed into a polysaccharide aerogel synthesized from the same macro algae. Spectrophotometer analyses show a pH dependent fluorescent behavior varying from 450-620 nm in aqueous media. Heavily oxidized edges provide for easy functionalization with enzymes for a more targeted analysis and remediation technique. Given the optical properties of the carbon base nanoparticles and the numerous possibilities of functionalization, we have developed a selective and robust targeted bio-detection and bioremediation technique for the treatment of emerging contaminants in complex matrices like estuarine embayment.

Keywords: aerogels, carbon nanoparticles, fluorescent, targeted analysis

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Authors: Josiah Damisa, Michelle Louise Richardson, Morenike Adewuyi

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Lower back pain is a significant cause of disability worldwide and associated with great implications in terms of the well-being of affected individuals and society as a whole due to its undeniable socio-economic impact. With its prevalence on the increase as a result of an aging global population, the need for novel forms of pain management is ever paramount. This review aims to provide further insight into current research regarding a role for the endocannabinoid signaling pathway as a target in the treatment of chronic pain, with particular emphasis on its potential use as part of the treatment of lower back pain. Potential advantages and limitations of cannabis-based medicines over other forms of analgesia currently licensed for medical use are discussed in addition to areas that require ongoing consideration and research. To evaluate the efficacy of cannabis-based medicines in chronic pain, studies pertaining to the role of medical cannabis in chronic disease were reviewed. Standard searches of PubMed, Google Scholar and Web of Science databases were undertaken with peer-reviewed journal articles reviewed based on the indication for pain management, cannabis treatment modality used and study outcomes. Multiple studies suggest an emerging role for cannabis-based medicines as therapeutic agents in the treatment of chronic back pain. A potential synergistic effect has also been purported if these medicines are co-administered with opiate analgesia due to the similarity of the opiate and endocannabinoid signaling pathways. However, whilst recent changes to legislation in the United Kingdom mean that cannabis is now licensed for medicinal use on NHS prescription for a number of chronic health conditions, concerns remain as to the efficacy and safety of cannabis-based medicines. Research is lacking into both their side effect profiles and the long-term effects of cannabis use. Legal and ethical considerations to the use of these products in standardized medical practice also persist due to the notoriety of cannabis as a drug of abuse. Despite this, cannabis is beginning to gain traction as an alternative or even complementary drug to opiates, with some preclinical studies showing opiate-sparing effects. Whilst there is a paucity of clinical trials in this field, there is scope for cannabinoids to be successful anti-nociceptive agents in managing chronic back pain. The ultimate aim would be to utilize cannabis-based medicines as alternative or complementary therapies, thereby reducing opiate over-reliance and providing hope to individuals who have exhausted all other forms of standard treatment.

Keywords: endocannabinoids, cannabis-based medicines, chronic pain, lower back pain

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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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Authors: Salma Ahmed, Anil Kumar

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This paper develops and estimates a model for understanding the drivers and barriers for Omni-Channel retail. This study serves as one of the first attempt to empirically test the effect of various factors on Omni-channel retail. Omni-channel is relative new and evolving, we hypothesize three drivers: (1) Innovative sales and marketing opportunities, (2) channel migration, (3) Cross channel synergies; and three barriers: (1) Integrated sales and marketing operations, (2) Visibility and synchronization (3) Integration and Technology challenges. The findings from the study strongly support that Omni-channel effects exist between cross channel synergy and channel migration. However, it partially supports innovative sales and marketing operations. We also found the variables which we identified as barriers to Omni-channel retail have a strong impact on Omni-channel retail.

Keywords: retailing, multichannel, Omni-channel, emerging market

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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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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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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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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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Authors: Thomas Chinwe Urama, Patrick Oseloka Ezepue, Peters Chimezie Nnanwa

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This paper investigates the universal financial dynamics in two dominant stock markets in Sub-Saharan Africa, through an in-depth analysis of the cross-correlation matrix of price returns in Nigerian Stock Market (NSM) and Johannesburg Stock Exchange (JSE), for the period 2009 to 2013. The strength of correlations between stocks is known to be higher in JSE than that of the NSM. Particularly important for modelling Nigerian derivatives in the future, the interactions of other stocks with the oil sector are weak, whereas the banking sector has strong positive interactions with the other sectors in the stock exchange. For the JSE, it is the oil sector and beverages that have greater sectorial correlations, instead of the banks which have the weaker correlation with other sectors in the stock exchange.

Keywords: random matrix theory, cross-correlations, emerging markets, option pricing, eigenvalues eigenvectors, inverse participation ratios and implied volatility

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Authors: Raana Babadi Fathipour

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Food packaging plays a crucial role in protecting food from unwanted external factors. Antibacterial edible films are a promising option for food packaging due to their biodegradability, environmental friendliness, and safety. This paper reviews recent research progress on antimicrobial edible films, focusing on those made from polysaccharides, proteins, and lipids. Polysaccharides and proteins are the primary components of antimicrobial edible films, while lipids primarily serve as plasticizers and carriers for active substances in composite films. For instance, second-generation liposomes have shown great potential as carriers for antimicrobial substances and other bioactive compounds due to their exceptional stability. Furthermore, this paper analyzes recent advancements and future trends in antimicrobial edible films. One promising direction is the integration of antimicrobial edible film materials with delivery systems, such as nanoemulsion and microencapsulation technologies, to ensure stable loading of bioactive substances. Another emerging area of interest is the development of smart and active packaging that allows consumers to assess the freshness of food products without opening the package. pH-sensitive films and smart fluorescent "on-off" sensors for humidity are currently being explored as materials for smart and active packaging to monitor food product freshness, with further exploration anticipated in the future.

Keywords: antimicrobial edible film, biopolymer, antimicrobial agent, encapsulation, antimicrobial assay

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Authors: Gabriela R. Silveira, Claudia S. Rocha, Lais S. Vitti, Jeane L. Borges, Helen B. Durgante

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Emerging adulthood occurs after adolescence in a period that maybe be marked by experimentation, identity reconfigurations, labor life demands, and insertion in the work environment, which tends to generate stress and emotional instability. Health promotion programs for the development of strengths and virtues, based on Positive Psychology, for emerging adults are sparse in Brazil. The aim of this study was to evaluate the preliminary effects of an online multi-component Positive Psychology program for the health promotion of emerging adults based on Cognitive Behavioural Therapy and Positive Psychology. The program included six online (synchronous) weekly group sessions of approximately two hours each and homework (asynchronous) activities. The themes worked were Values and self-care/Prudence, Optimism, Empathy, Gratitude, Forgiveness, and Meaning of life and work. This study presents data from a longitudinal, pre-experimental design with pre (T1) and post-test (T2) evaluation in the intervention group. 47 individuals aged between 19-30 years old participated, mean age of 24.53 years (SD=3.13), 37 females (78.7%). 42 (89.4%) self-defined as heterosexual, four (8.5%) as homosexual, and one (2.5%) as bisexual. 33 (70.2%) had incomplete higher education, four (8.5%) completed higher education, and seven (14.9%) had a graduate level of education. 27 participants worked (57.4%), out of which 25 were health workers (53.2%). 14 (29.8%) were caregivers, 27 (57.4%) had a spiritual belief, 36 (76.6%) had access to leisure, and 38 (80.9%) had perceived social support. The instruments used were a sociodemographic questionnaire, the 10-item Perceived Stress Scale, and the 12-item General Health Questionnaire. The program was advertised on social networks and interested participants filled out the Consent Form and the evaluation protocol at T1 and T2 via Google Docs form. The main research was approved (CEP n.1,899,368; 4,143,219; CAAE: 61997516.5.0000.5334) and complied with sanitary and Ethics criteria in research with human beings. Wilcoxon statistics revealed significant improvements in indicators of perceived stress between T1 (X=22.21, SD=6.79) and T2 (X=15.10, SD=5.82); (Z=-4.353; p=0.001) as well as depression and anxiety symptoms (T1:X=26.72, SD=8.84; T2: X=19.23, SD=4.68); (Z=-3.945, p=0.001) of the emerging adults after their participation in the programme. The programme has an innovative character not only for presenting an online Positive Psychology approach but also for being based on an intervention developed, evaluated, and manualized in Brazil. By focusing on emerging adults, this study contributes to advancing research on a relatively new field in developmental studies. As a limitation, this is a pre-experimental and pilot study, requiring an increase in sample size for greater statistical robustness, also qualitative data analysis is crucial for methodological complementarity. The importance of investing efforts to accompany this age group and provide advances in longitudinal research in the area of health promotion and disease prevention is highlighted.

Keywords: emerging adults, disease prevention, health promotion, online program

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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

Procedia PDF Downloads 186

Authors: Aura Alejandra Burbano Patino, Mariela Agotegaray, Veronica Lassalle, Fernanda Horst

Abstract:

Water pollution is of worldwide concern due to its importance as an essential resource for life. Industrial and urbanistic growth are anthropogenic activities that have caused an increase of undesirable compounds in water. In the last decade, emerging pollutants have become of great interest since, at very low concentrations (µg/L and ng/L), they exhibit a hazardous effect on wildlife, aquatic ecosystems, and human organisms. One group of emerging pollutants that are a matter of study are pharmaceuticals. Their high consumption rate and their inappropriate disposal have led to their detection in wastewater treatment plant influent, effluent, surface water, and drinking water. In consequence, numerous technologies have been developed to efficiently treat these pollutants. Adsorption appears like an easy and cost-effective technology. One of the most used adsorbents of emerging pollutants removal is carbon-based materials such as hydrochars. This study aims to use a magnetic hydrochar nanocomposite to be employed as an adsorbent for diclofenac removal. Kinetics models and the adsorption efficiency in real water samples were analyzed. For this purpose, a magnetic hydrochar nanocomposite was synthesized through the hydrothermal carbonization (HTC) technique hybridized to co-precipitation to add the magnetic component into the hydrochar, based on iron oxide nanoparticles. The hydrochar was obtained from sunflower husk residue as the precursor. TEM, TGA, FTIR, Zeta potential as a function of pH, DLS, BET technique, and elemental analysis were employed to characterize the material in terms of composition and chemical structure. Adsorption kinetics were carried out in distilled water and real water at room temperature, pH of 5.5 for distilled water and natural pH for real water samples, 1:1 adsorbent: adsorbate dosage ratio, contact times from 10-120 minutes, and 50% dosage concentration of DCF. Results have demonstrated that magnetic hydrochar presents superparamagnetic properties with a saturation magnetization value of 55.28 emu/g. Besides, it is mesoporous with a surface area of 55.52 m²/g. It is composed of magnetite nanoparticles incorporated into the hydrochar matrix, as can be proven by TEM micrographs, FTIR spectra, and zeta potential. On the other hand, kinetic studies were carried out using DCF models, finding percent removal efficiencies up to 85.34% after 80 minutes of contact time. In addition, after 120 minutes of contact time, desorption of emerging pollutants from active sites took place, which indicated that the material got saturated after that t time. In real water samples, percent removal efficiencies decrease up to 57.39%, ascribable to a possible mechanism of competitive adsorption of organic or inorganic compounds, ions for active sites of the magnetic hydrochar. The main suggested adsorption mechanism between the magnetic hydrochar and diclofenac include hydrophobic and electrostatic interactions as well as hydrogen bonds. It can be concluded that the magnetic hydrochar nanocomposite could be valorized into a by-product which appears as an efficient adsorbent for DCF removal as a model emerging pollutant. These results are being complemented by modifying experimental variables such as pollutant’s initial concentration, adsorbent: adsorbate dosage ratio, and temperature. Currently, adsorption assays of other emerging pollutants are being been carried out.

Keywords: environmental remediation, emerging pollutants, hydrochar, magnetite nanoparticles

Procedia PDF Downloads 178

Authors: Chuang Bing-Kai, Shih Hsiang-Ju

Abstract:

Previous studies showed that emergent adults used dating applications the most since it would satisfy their needs for intimacy. It's also found that those emergent adults were mostly non-heterosexual. What’s more, in this digital era, more and more bisexuals and homosexuals choose to establish connections with others through Internet to seek a sense of belonging. However, studies rarely focused on gay men in their emergent adulthood to explore their experiences of dating applications. The purpose of this study was to explore the experience of gay men using dating applications in their emerging adulthood and to understand their self-presentations and the process of it among different relationships while interacting with others upon using dating applications. The semi-structured interview was conducted with those gay men who aged from 18 to 29, felt attracted to people with same gender physically and mentally, considered themselves homosexual from their subjective understanding and had been using dating applications for more than half a year. Research invitations were distributed with the assistance of social media platforms and LGBTQ+ friends in the community. This study adopted a qualitative research approach and applied hermeneutic phenomenology as the method to analyze the transcripts transcribed from the recorded audio, and to explore their using experiences and self-presentations while interacting with others while using dating apps. It’s expected to find out that there are four stages in the self-presentation process including establishing personal identity, self-exploration and experimentation, exploring shared interest and values, developing and maintaining connections. Plus, gay men’s motives to use dating apps play an important role in this process and thus influence how they position the apps in their life. Through this study, professional workers can better understand gay men’s considerations and strategies in their self-presentation process as well as the impact of using motives.

Keywords: dating applications, emerging adulthood, gay men, hermeneutic phenomenology

Procedia PDF Downloads 41