Search results for: iodinated contrast agents

Authors: Roy. H. A. Lindelauf

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Cyberattacks are complex processes consisting of multiple interwoven tasks conducted by a set of agents. Interdictions and defenses against such attacks often rely on cyber kill chain (CKC) models. A CKC is a framework that tries to capture the actions taken by a cyber attacker. There exists a growing body of literature on CKCs. Most of this work either a) describes the CKC with respect to one or more specific cyberattacks or b) discusses the tools and technologies used by the attacker at each stage of the CKC. Defenders, facing scarce resources, have to decide where to allocate their resources given the CKC and partial knowledge on the tools and techniques attackers use. In this presentation CKCs are analyzed through the lens of covert projects, i.e., interrelated tasks that have to be conducted by agents (human and/or computer) with the aim of going undetected. Various aspects of covert project models have been studied abundantly in the operations research and game theory domain, think of resource-limited interdiction actions that maximally delay completion times of a weapons project for instance. This presentation has investigated both cooperative and non-cooperative game theoretic covert project models and elucidated their relation to CKC modelling. To view a CKC as a covert project each step in the CKC is broken down into tasks and there are players of which each one is capable of executing a subset of the tasks. Additionally, task inter-dependencies are represented by a schedule. Using multi-glove cooperative games it is shown how a defender can optimize the allocation of his scarce resources (what, where and how to monitor) against an attacker scheduling a CKC. This study presents and compares several cooperative game theoretic solution concepts as metrics for assigning resources to the monitoring of agents.

Keywords: cyber defense, cyber kill chain, game theory, information warfare techniques

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Authors: Parastou Kharazmi

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Degradation of building materials particularly pipelines causes environmental damage during renovation or replacement and is a time consuming and costly process. Rehabilitation by polymer composites is a solution for renovation of degraded pipeline in heritage buildings and other structures which are less costly, faster and causes less damage to the environment; however, it is still not clear for how long these materials can perform as expected in the field and working condition. To study their service life, two types of composites based on Epoxy and Polyester resins have been evaluated by accelerated exposure and field exposure. The primary degradation agent used in accelerated exposure has been cycling temperature with half of the tests performed in presence of water. Thin films of materials used in accelerated testing were prepared in laboratory by using the same amount of material as well as technique of multi-layers application used in majority of the field installations. Extreme intensity levels of degradation agents have been used only to evaluate materials properties and as also mentioned in ISO 15686, are not directly correlated with degradation mechanisms that would be experienced in service. In the field exposure study, the focus has been to identify possible failure modes, causes, and effects. In field exposure, it has been observed that there are other degradation agents present which can be investigated further such as presence of contaminants and rust before application which prevents formation of a uniform layer of polymer or incompatibility between dissimilar materials. This part of the study also highlighted the importance of application’s quality of the materials in the field for providing the expected performance and service life. Results from extended accelerated exposure and field exposure can help in choosing inspection techniques, establishing the primary degradation agents and can be used for ageing exposure programs with clarifying relationship between different exposure periods and sites.

Keywords: building, renovation, service life, pipelines

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Authors: Raquel Camprubí

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Cultural tourism has been postulated as relevant motivation for tourist over the world during the last decades. In this context, museums are the main attraction for cultural tourists who are seeking to connect with the history and culture of the visited place. From the point of view of an urban destination, museums and other cultural resources are essential to have a strong tourist supply at the destination, in order to be capable of catching attention and interest of cultural tourists. In particular, museums’ challenge is to be prepared to offer the best experience to their visitors without to forget their mission-based mainly on protection of its collection and other social goals. Thus, museums individually want to be competitive and have good positioning to achieve their strategic goals. The life cycle of the destination and the level of maturity of its tourism product influence the need of tourism agents to cooperate and collaborate among them, in order to rejuvenate their product and become more competitive as a destination. Additionally, prior studies have considered an approach of different models of a public and private partnership, and collaborative and cooperative relations developed among the agents of a tourism destination. However, there are no studies that pay special attention to museums and the strategic alliances developed to obtain mutual benefits. Considering this background, the purpose of this study is to analyze in what extent museums of a given urban destination have established strategic links and relations among them, in order to improve their competitive position at both individual and destination level. In order to achieve the aim of this study, the city of Girona (Spain) and the museums located in this city are taken as a case study. Data collection was conducted using in-depth interviews, in order to collect all the qualitative data related to nature, strengthen and purpose of the relational ties established among the museums of the city or other relevant tourism agents of the city. To conduct data analysis, a Social Network Analysis (SNA) approach was taken using UCINET software. Position of the agents in the network and structure of the network was analyzed, and qualitative data from interviews were used to interpret SNA results. Finding reveals the existence of strong ties among some of the museums of the city, particularly to create and promote joint products. Nevertheless, there were detected outsiders who have an individual strategy, without collaboration and cooperation with other museums or agents of the city. Results also show that some relational ties have an institutional origin, while others are the result of a long process of cooperation with common projects. Conclusions put in evidence that collaboration and cooperation of museums had been positive to increase the attractiveness of the museum and the city as a cultural destination. Future research and managerial implications are also mentioned.

Keywords: cultural tourism, competitiveness, museums, Social Network analysis

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Authors: W. Mazari, K. Boucherit, Z. Boucherit-Otmani, M. N. Rahmoun, M. Benabdallah

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The hospital or any other establishment of care can be considered as an ecosystem where the patient comes into contact with a frightening microbial universe and a risk to contract infection that is referred to as nosocomial or health care-associated. In these last years, the incidence of these infections has risen sharply. Several microorganisms are the cause of these nosocomial infections and the emergence of resistance of the microbial strains against antibiotics creates a danger to public health. The search for new antimicrobial agents to overcome this problem has produced interesting compounds through chemical synthesis, which plays a very important role in the research and discovery of new drugs. It is in this framework that our study was conducted at our laboratory and it involves evaluating the antibacterial activity of thirteen 2-pyridone derivatives synthesized by two methods, the diffusion disc method and the dilution method against eight Gram negative bacterial strains. The results seem interesting especially for two products that have shown the best activities against Escherichia coli ATCC 25922 and Enterobacter cloacae ATCC 13047 with CMI of 512µg/ml.

Keywords: heterocyclic derivatives, chemical synthesis, antimicrobial activity, biotechnology

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Authors: Z. Mortezaie, H. Hassanpour, S. Asadi Amiri

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Captured images may suffer from Gaussian blur due to poor lens focus or camera motion. Unsharp masking is a simple and effective technique to boost the image contrast and to improve digital images suffering from Gaussian blur. The technique is based on sharpening object edges by appending the scaled high-frequency components of the image to the original. The quality of the enhanced image is highly dependent on the characteristics of both the high-frequency components and the scaling/gain factor. Since the quality of an image may not be the same throughout, we propose an adaptive unsharp masking method in this paper. In this method, the gain factor is computed, considering the gradient variations, for individual pixels of the image. Subjective and objective image quality assessments are used to compare the performance of the proposed method both with the classic and the recently developed unsharp masking methods. The experimental results show that the proposed method has a better performance in comparison to the other existing methods.

Keywords: unsharp masking, blur image, sub-region gradient, image enhancement

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Authors: A. Hol

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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

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Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Tabassum Yasmin, Hamid Pahlevan

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HIV/Hepatitis C co-infection treatments have evolved substantially and they have similar sustained virologic response rates as those of Hepatitis C monoinfected population. There are a few studies on therapy of patients with dual genotypes, especially in HIV/Hepatic C coinfected group. Most studies portrayed case reports of dual genotype chronic Hepatitis C coinfection treatment with Sofosbuvir/Ledipasvir and Ribavirin. A 79-year-old male with a history of HIV on Truvada and Isentress had chronic Hepatitis C with 1a and 2 genotypes. The patient has a history of alcohol intake for 40 years but recently stopped drinking alcohol. He has a history of intravenous drug use in the past and currently is not using any recreational drugs. Patient has Fibro score of 0.7 with Metavir score F2 to F4. AFP is 3.2. The HCV RNA is 493,034 IU/ML. The HBV viral DNA is < 1.30 (not detected). The CD4 is 687CU/MM. The FIB 4 is 3.34 with APRI index 0.717. The HIV viral load is 101 copies/ML. MRI abdomen did not show any liver abnormality. Fixed dose Sofosbuvir/Ledipasvir was used for therapy without Ribavirin. He tolerated medication except for some minor gastrointestinal side effects like abdominal bloating. He demonstrated 100% adherence rate. Patient completed 12 weeks of therapy. HCV RNA was undetectable at 4 and 12 weeks. He achieved SVR at week 12 and subsequently had undetectable RNA for 2 years. Dual genotype prevalence in chronic hepatitis C population is rare, especially in HIV/hepatic coinfection. Our case demonstrates that dual genotypic cases can still be successfully treated with Direct Acting Antiviral agents. The newer agents for therapy for pan genotypes were not available at the time the patient was being treated. We demonstrated that dual agent therapy was still able to maintain SVR in our patient.

Keywords: HIV/Hepatitis C, SVR (sustained virologic response), DAA (direct active antiviral agents, dual genotype

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Authors: William Huang

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Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

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Authors: Nneka Augustina Akwu, Yougasphree Naidoo

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Molecular advancement in technology has created a means whereby the atoms and molecules (solid forms) of certain materials such as plants, can now be reduced to a range of 1-100 nanometres. Green synthesis of silver nanoparticles (AgNPs) was carried out at room temperature (RT) 25 ± 2°C and 80°C, using the metabolites in the aqueous extracts of the leaves and stem bark of Grewia lasiocarpa as reductants and stabilizing agents. The biosynthesized AgNPs were characterized by UV-Vis spectrophotometry, attenuated total reflectance - Fourier transforms infrared (ATR-FTIR) spectroscopy, nanoparticle tracking analysis (NTA), Energy Dispersive X-ray fluorescence scanning electron microscope (SEM-EDXRF) and high-resolution transmission electron microscopy (HRTEM). The AgNPs were biologically evaluated for antioxidant, antibacterial and cytotoxicity activities. The phytochemical and FTIR analyses revealed the presence of metabolites that act as reducing and capping agents, while the UV-Vis spectroscopy of the biosynthesized NPs showed absorption between 380-460 nm, confirming AgNP synthesis. The Zeta potential values were between -9.1 and -20.6 mV with a hydrodynamics diameter ranging from 38.3 to 46.7 nm. SEM and HRTEM analyses revealed that AgNPs were predominately spherical with an average particle size of 2- 31 nm for the leaves and 5-27 nm for the stem bark. The cytotoxicity IC50 values of the AgNPs against HeLa, Caco-2 and MCF-7 were >1 mg/mL. The AgNPs were sensitive to all strains of bacteria used, with methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922) being more sensitive to the AgNPs. Our findings propose that antibacterial and anticancer agents could be derived from these AgNPs of G. lasiocarpa, and warrant their further investigation.

Keywords: antioxidant, cytotoxicity, Grewia lasiocarpa, silver nanoparticles, Zeta potentials

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

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Authors: Ravi J. Shah

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The present study deals with the synthesis of novel spiro[azetidine-2, 3’-indole]-2’, 4(1’H)-dione derivative from the reactions of 3-(phenylimino)-1,3-dihydro-2H-indol-2-one derivatives with chloracetyl chloride in presence of triethyl amine (TEA). All the compounds were characterized using IR, 1H NMR, MS and elemental analysis. They were screened for their antibacterial and antifungal activities. Results revealed that, compounds (7a), (7b), (7c), (7d) and (7e) showed very good activity with MIC value of 6.25-12.5 μg/ml against three evaluated bacterial strains and the remaining compounds showed good to moderate activity comparable to standard drugs as antibacterial agents. Compounds (7c) and (7h) displayed equipotent antifungal activity in comparison to standard drugs. Structure-activity relationship study of the compounds showed that the presence of electron withdrawing group substitution at 5’ and 7’ positions of indoline ring and on ortho or para position of phenyl ring increases both antibacterial and antifungal activity of the compound. Henceforth, our findings will have a good impact on chemists and biochemists for further investigations in search of bromine containing spiro fused antimicrobial agents.

Keywords: antibacterial activity, antifungal activity, 2-Azetidinone, indoline

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Authors: Lorena G. Calvo, Marta Lores, Trinidad de Miguel

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Natural extracts containing high polyphenolic concentration possess antibacterial and antifungal activity. The present research characterizes a hydro-organic extract with a high polyphenolic content as an antimicrobial candidate. As a result of this composition, the extract showed pronounced bioactivities with potential uses in agricultural, veterinary, pharmaceutical, and cosmetic industries. Polyphenol compounds were extracted by using hydro-organic solvent mixtures from the shrub Cytisus scoparius. The in vitro antimicrobial activity of this extract was evaluated on Gram-positive and Gram-negative bacteria and the fungus Candida albicans. Microbial species investigated, Bacillus cereus, Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa, are causing agents of several human and animal diseases. The extract showed activity against all tested species. So, it could be used for the development of biocides to control a wide range of pathogenic agents and contribute to the creation of economic and eco-friendly alternatives to antibiotics.

Keywords: antimicrobial properties, antioxidant properties, Cytisus scoparius, polyphenolic extract

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Authors: Ravinder Kaur

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Introduction Global cerebrovascular reactivity (CVR) mapping is a promising clinical assessment for stress-testing the brain using physiological challenges, such as CO₂, to elicit changes in perfusion. It enables real-time assessment of cerebrovascular integrity and health. Conventional imaging approaches solely use steady-state parameters, like cerebral blood flow (CBF), to evaluate the integrity of the resting parenchyma and can erroneously show a healthy brain at rest, despite the underlying pathogenesis in the presence of cerebrovascular disease. Conversely, coupling CO₂ inhalation with phase-contrast MRI neuroimaging interrogates the capacity of the vasculature to respond to changes under stress. It shows promise in providing prognostic value as a novel health marker to measure neurovascular function in disease and to detect early brain vasculature dysfunction. Objective This exploratory study was established to:(a) quantify the CBF response to CO₂ in hypocapnia and hypercapnia,(b) evaluate disparities in CVR between internal carotid (ICA) and vertebral artery (VA), and (c) assess sex-specific variation in CVR. Methodology Phase-contrast MRI was employed to measure the cerebrovascular reactivity to CO₂ (±10 mmHg). The respiratory interventions were presented using the prospectively end-tidal targeting RespirActTM Gen3 system. Post-processing and statistical analysis were conducted. Results In 9 young, healthy subjects, the CBF increased from hypocapnia to hypercapnia in all vessels (4.21±0.76 to 7.20±1.83 mL/sec in ICA, 1.36±0.55 to 2.33±1.31 mL/sec in VA, p < 0.05). The CVR was quantitatively higher in ICA than VA (slope of linear regression: 0.23 vs. 0.07 mL/sec/mmHg, p < 0.05). No statistically significant effect was observed in CVR between male and female (0.25 vs 0.20 mL/sec/mmHg in ICA, 0.09 vs 0.11 mL/sec/mmHg in VA, p > 0.05). Conclusions The principal finding in this investigation validated the modulation of CBF by CO₂. Moreover, it has indicated that regional heterogeneity in hemodynamic response exists in the brain. This study provides scope to standardize the quantification of CVR prior to its clinical translation.

Keywords: cerebrovascular disease, neuroimaging, phase contrast MRI, cerebrovascular reactivity, carbon dioxide

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Authors: Felix Golla

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In an era where technology increasingly intersects with education, the potential of chatbots and ChatGPT agents in enhancing student learning experiences in higher education is both significant and timely. This study explores the integration of these AI-driven tools in educational settings, emphasizing their design and functionality to meet the specific needs of students. Recognizing the gap in literature concerning student-centered AI applications in education, this research offers valuable insights into the role and efficacy of chatbots and ChatGPT agents as educational tools. Employing qualitative research methodologies, the study involved conducting semi-structured interviews with university students. These interviews were designed to gather in-depth insights into the students' experiences and expectations regarding the use of AI in learning environments. The High-Performance Cycle Model, renowned for its focus on goal setting and motivation, served as the theoretical framework guiding the analysis. This model helped in systematically categorizing and interpreting the data, revealing the nuanced perceptions and preferences of students regarding AI tools in education. The major findings of the study indicate a strong preference among students for chatbots and ChatGPT agents that offer personalized interaction, adaptive learning support, and regular, constructive feedback. These features were deemed essential for enhancing student engagement, motivation, and overall learning outcomes. Furthermore, the study revealed that students perceive these AI tools not just as passive sources of information but as active facilitators in the learning process, capable of adapting to individual learning styles and needs. In conclusion, this study underscores the transformative potential of chatbots and ChatGPT agents in higher education. It highlights the need for these AI tools to be designed with a student-centered approach, ensuring their alignment with educational objectives and student preferences. The findings contribute to the evolving discourse on AI in education, suggesting a paradigm shift towards more interactive, responsive, and personalized learning experiences. This research not only informs educators and technologists about the desirable features of educational chatbots but also opens avenues for future studies to explore the long-term impact of AI integration in academic curricula.

Keywords: chatbot design in education, high-performance cycle model application, qualitative research in AI, student-centered learning technologies

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Authors: Adnan Bekhit, Eskedar Lodebo, Ariaya Hymete, Hanan Ragab, Alaa El-Din Bekhit

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Malaria and leishmaniasis have emerged as serious universal health problems throughout history of mankind. According to the WHO 2008 malarial report, half of the world population is at risk of malarial infection with an estimate of 1 million deaths occurring annually mainly in the African region. Furthermore, 12-15 million people are infected with Leishmaniasis worldwide. Despite the continuous introduction of a large number of agents for the treatment of malaria, there is still unmet medical needs due to the emergence of resistance. Resistance has occurred for almost all therapeutic agents approved for the treatment of malaria. Accordingly, it was the aim of this work to design and synthesis a group of antimalarial-antileshmanial agents that would show inhibitory activity against chloroquine-resistant strain of Plasmodium falciparum. The synthesized compounds were designed to contain a pyrazolylpyrazoline moiety having an aromatic group (p-tolyl or p-chlorophenyl) at N1-position of one pyrazoline ring due to the reports of promising activities of such compounds. A formyl or acyl substituent was introduced at the N1-position of the other pyrazoline ring, to investigate the effect of bulkiness of acyl substituents at this position. The synthesized compounds were evaluated for their in-vivo antimalarial activity against Plasmodium berghei infected mice at dose levels of 20 and 30 mg/Kg. the two most active compounds were evaluated for their antimalarial activity against chloroquin-resistant strain (RKL9) of Plasmodium falciparum. In addition, the synthesized compounds were tested for their in-vitro antileshmanial activity against Leishmania aethiopica promastigotes and amastigotes. For both antimalarial and antileishmanial activities, compounds having an N1-p-tolyl group at the first pyrazoline ring did not require bulkiness at the second pyrazoline ring nitrogen where the compound bearing an acetyl group proved to be the most active of the whole series. On the other hand, bulkiness at the N1-position of the second pyazoline ring was necessary in case of compounds carrying the p-chlorophenyl group, where the two derivatives having an N1-butanoyl and an N1-benzoyl moieties at the second pyrazoline showed the best activity. Furthermore, the toxicity of the active compounds were tested and were proved to be non-toxic at 125, 250 and 500 mg/Kg. In addition, docking of the most active compound (having a p-tolyl group at the first pyrazoline-N and an acetyl moiety on the other pyrazoline-N) was performed against dihydrofolate reductase enzyme.

Keywords: pyrazoline derivatives, in-vivo antimalarial activity, docking, dihydrofolate reductase

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Authors: Rodrigo I. Ullauri, Santiago E. Tinajero, Omar O. Ramos, Paola R. Quintana

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The increase of CO₂ emissions in the atmosphere and its impact on climate change is a global concern. The transportation sector is a significant consumer of fossil fuels and contributes significantly to greenhouse gas emissions. The current challenge is to find ways to reduce the use of fossil fuels in transportation. In Ecuador, where 92% of electricity is generated from clean sources, the concept of e-mobility is considered an attractive alternative to address the challenge of sustainable mobility. The proposal is to migrate from combustion-powered vehicles to electric vehicles in the electric companies of Ecuador, using a methodology to standardize criteria, determine specific requirements, contrast technical characteristics, and estimate emission reductions. The results showed that there are three categories of vehicles that have electric counterparts suitable for performing activities under certain operation parameters inherent to current technology limitations but with a significant contribution to the reduction of annual CO₂ emissions.

Keywords: climate change, electro mobility, energy, sustainable transportation

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Authors: Amna J. Ghith, Khaled Abu Zid, Khairia Youssef, Nasser Saad

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Backgrounds: The multikinase and vascular endothelial growth factor (VEGF) receptor inhibitors interrupt the pathway by which angiogenesis becomes established and promulgated, resulting in the inadequate nourishment of metastatic disease. VEGFR-2 has been the principal target of anti-angiogenic therapies. We disclose the new thieno pyrimidines as inhibitors of VEGFR-2 designed by a molecular modeling approach with increased synergistic activity and decreased side effects. Purpose: 2-substituted thieno pyrimidines are designed and synthesized with anticipated anticancer activity based on its in silico molecular docking study that supports the initial pharmacophoric hypothesis with a same binding mode of interaction at the ATP-binding site of VEGFR-2 (PDB 2QU5) with high docking score. Methods: A series of compounds were designed using discovery studio 4.1/CDOCKER with a rational that mimic the pharmacophoric features present in the reported active compounds that targeted VEGFR-2. An in silico ADMET study was also performed to validate the bioavailability of the newly designed compounds. Results: The Compounds to be synthesized showed interaction energy comparable to or within the range of the benzimidazole inhibitor ligand when docked with VEGFR-2. ADMET study showed comparable results most of the compounds showed absorption within (95-99) zone varying according to different substitutions attached to thieno pyrimidine ring system. Conclusions: A series of 2-subsituted thienopyrimidines are to be synthesized with anticipated anticancer activity and according to docking study structure requirement for the design of VEGFR-2 inhibitors which can act as powerful anticancer agents.

Keywords: docking, discovery studio 4.1/CDOCKER, heterocycles based anticancer agents, 2-subsituted thienopyrimidines

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Authors: Mahmoud H. Abu Elella, Riham R. Mohamed, Magdy W. Sabaa

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Introduction: Microbial pollution is global problem threatening the human health. It is resulted by pathogenic microorganisms such as Escherichia coli (E. coli), Staphylococcus aureus (S. aureus) and other pathogenic strains. They cause a dangerous effect on human health, so great efforts have been exerted to produce new and effective antimicrobial agents. Nowadays, natural polysaccharides, such as chitosan and its derivatives are used as antimicrobial agents. The aim of our work is to synthesize of a biodegradable polymer such as N-quaternized chitosan (NQC) then Characterization of NQC by using different analysis techniques such as Fourier transform infrared (FTIR) and Scanning electron microscopy (SEM) and using it as an antibacterial agent against different pathogenic bacteria. Methods: Synthesis of NQC using dimethylsulphate. Results: FTIR technique exhibited absorption peaks of NQC, SEM images illustrated that surface of NQC was smooth and antibacterial results showed that NQC had a high antibacterial effect. Discussion: NQC was prepared and it was proved by FTIR technique and SEM images antibacterial results exhibited that NQC was an antibacterial agent.

Keywords: antimicrobial agent, N-quaternized chitosan chloride, silver nanocomposites, sodium polyacrylate

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Authors: Yu-Fong Lin

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The main purpose of this study is to explore the impact of different lighting arrangements that create different visual environments in a 3C retail store on the perception, psychology, and shopping tendencies of consumers of different genders. In recent years, the ‘emotional shopping’ model has been widely accepted in the consumer market; in addition to the emotional meaning and value of a product, the in-store ‘shopping atmosphere’ has also been increasingly regarded as significant. The lighting serves as an important environmental stimulus that influences the atmosphere of a store. Altering the lighting can change the color, the shape, and the atmosphere of a space. A successful retail lighting design can not only attract consumers’ attention and generate their interest in various goods, but it can also affect consumers’ shopping approach, behavior, and desires. 3C electronic products have become mainstream in the current consumer market. Consumers of different genders may demonstrate different behaviors and preferences within a 3C store environment. This study tests the impact of a combination of lighting contrasts and color temperatures in a 3C retail store on the visual perception and psychological reactions of consumers of different genders. The research design employs an experimental method to collect data from subjects and then uses statistical analysis adhering to a 2 x 2 x 2 factorial design to identify the influences of different lighting environments. This study utilizes virtual reality technology as the primary method by which to create four virtual store lighting environments. The four lighting conditions are as follows: high contrast/cool tone, high contrast/warm tone, low contrast/cool tone, and low contrast/warm tone. Differences in the virtual lighting and the environment are used to test subjects’ visual perceptions, emotional reactions, store satisfaction, approach-avoidance intentions, and spatial atmosphere preferences. The findings of our preliminary test indicate that female subjects have a higher pleasure response than male subjects in a 3C retail store. Based on the findings of our preliminary test, the researchers modified the contents of the questionnaires and the virtual 3C retail environment with different lighting conditions in order to conduct the final experiment. The results will provide information about the effects of retail lighting on the environmental psychology and the psychological reactions of consumers of different genders in a 3C retail store lighting environment. These results will enable useful practical guidelines about creating 3C retail store lighting and atmosphere for retailers and interior designers to be established.

Keywords: 3C retail store, environmental stimuli, lighting, virtual reality

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Authors: Rasha A.Ibrahim El-Ghazawy, Ashraf M. El-Saeed, Heusin El-Shafey, M. Abdel-Raheim, Maher A. El-Sockary

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Two thermotropic liquid crystalline curing agents based on abietic acid with different mesogens (LCC1 and LCC2) were synthesized for producing thermally stable liquid crystal networks suitable for high performance epoxy coatings. Differential scanning calorimetry (DSC) and polarized optical microscope (POM) was used to identify the liquid crystal phase transformation temperatures and texture, respectively. POM micro graphs for both LCCs revealing cholesteric texture. A multifunctional epoxy resin with two abietic acid moieties was also synthesized. Dynamic mechanical (DMA) and thermogravimetric (TGA) analyses show that the fully bio-based cured epoxies by either LCCs possess high glass transition temperature (Tg), high modulus (G`) and improved thermal stability. The chemical structure of the synthesized LCCs and epoxy resin was investigated through FTIR and 1HNMR spectroscopic techniques.

Keywords: abietic acid, dynamic mechanical analysis, epoxy resin, liquid crystal, thermo gravimetric analysis

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Authors: Zerrin Erginkaya, Gözde Konuray

Abstract:

Microbial degradation of foods is defined as a decrease of food safety due to microorganism activity. Organic acids, sulfur dioxide, sulfide, nitrate, nitrite, dimethyl dicarbonate and several preservative gases have been used as chemical preservatives in foods as well as natural preservatives which are indigenous in foods. It is determined that usage of herbal preservatives such as blueberry, dried grape, prune, garlic, mustard, spices inhibited several microorganisms. Moreover, it is determined that animal origin preservatives such as whey, honey, lysosomes of duck egg and chicken egg, chitosan have antimicrobial effect. Other than indigenous antimicrobials in foods, antimicrobial agents produced by microorganisms could be used as natural preservatives. The antimicrobial feature of preservatives depends on the antimicrobial spectrum, chemical and physical features of material, concentration, mode of action, components of food, process conditions, and pH and storage temperature. In this review, studies about antimicrobial components which are indigenous in food (such as herbal and animal origin antimicrobial agents), antimicrobial materials synthesized by microorganisms, and their usage as an antimicrobial agent to preserve foods are discussed.

Keywords: animal origin preservatives, antimicrobial, chemical preservatives, herbal preservatives

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Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

Abstract:

The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT

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Authors: Antoine Villa, Moustapha Mohamedou, Florence Pilliere, Catherine Verdun-Esquer, Mathieu Molimard, Mohamed Sidatt Cheikh El Moustaph, Mireille Canal-Raffin

Abstract:

Context: In Mauritania, the activity of the National Center of Oncology (NCO) has steadily risen leading to an increase in the handling of antineoplastic drugs (AD) by healthcare professionals. In this context, the AD contamination of those professionals is a major concern for occupational physicians. It has been evaluated using biological monitoring of occupational exposure (BMOE). Methods: The intervention took place in 2015, in 2 care units, and evaluated nurses preparing and/or infusing AD and agents in charge of hygiene. Participants provided a single urine sample, at the end of the week, at the end of their shift. Five molecules were sought using specific high sensitivity methods (UHPLC-MS/MS) with very low limits of quantification (LOQ) (cyclophosphamide (CP), Ifosfamide (IF), methotrexate (MTX): 2.5ng/L; doxorubicin (Doxo): 10ng/L; α-fluoro-β-alanine (FBAL, 5-FU metabolite): 20ng/L). A healthcare worker was considered as 'contaminated' when an AD was detected at a urine concentration equal to or greater than the LOQ of the analytical method or at trace concentration. Results: Twelve persons participated (6 nurses, 6 agents in charge of hygiene). Twelve urine samples were collected and analyzed. The percentage of contamination was 66.6% for all participants (n=8/12), 100% for nurses (6/6) and 33% for agents in charge of hygiene (2/6). In 62.5% (n=5/8) of the contaminated workers, two to four of the AD were detected in the urine. CP was found in the urine of all contaminated workers. FBAL was found in four, MTX in three and Doxo in one. Only IF was not detected. Urinary concentrations (all drugs combined) ranged from 3 to 844 ng/L for nurses and from 3 to 44 ng/L for agents in charge of hygiene. The median urinary concentrations were 87 ng/L, 15.1 ng/L and 4.4 ng/L for FBAL, CP and MTX, respectively. The Doxo urinary concentration was found 218ng/L. Discussion: There is no current biological exposure index for the interpretation of AD contamination. The contamination of these healthcare professionals is therefore established by the detection of one or more AD in urine. These urinary contaminations are higher than the LOQ of the analytical methods, which must be as low as possible. Given the danger of AD, the implementation of corrective measures is essential for the staff. Biological monitoring of occupational exposure is the most reliable process to identify groups at risk, tracing insufficiently controlled exposures and as an alarm signal. These results show the necessity to educate professionals about the risks of handling AD and/or to care for treated patients.

Keywords: antineoplastic drugs, Mauritania, biological monitoring of occupational exposure, contamination

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

Abstract:

Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Mohamed Deyab

Abstract:

The global lubricant additives market size was USD 14.35 billion in 2015. The industry is characterized by increasing additive usage in base oil blending for longer service life and performance. These additives improve the viscosity of oil, act as detergents, defoamers, antioxidants, and antiwear agents. Since additives play a significant role in base oil blending and subsequent formulations as they are critical materials in improving specification and performance of oils. Herein, we report on the synthesis and characterization of three imidazolium derivatives and their application as antioxidants, detergents and antiwear agents. The molecular structure and characterizations of these ionic liquids were confirmed by elemental analysis, FTIR, X-Ray Diffraction (XRD) and 1HNMR spectroscopy. Thermo gravimetric analysis (TGA), is used to study the degradation and thermal stability of the studied base stock samples. It was found that all the prepared ionic liquids additives have excellent power of dispersion and detergency. The ionic liquids as additives to engine oil reduced the friction (38%) and wear volume (76%) of steel balls. The obtained results show that the ionic liquids have an oxidation inhibitor up to 95%.

Keywords: reused lubricating oil, waste, petroleum, ionic liquids

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Authors: Ruby Jean Hornsby

Abstract:

In our rapidly advancing techno-moral world, human-robot relationships are increasingly becoming a part of intimate human life. Indeed, social robots - that is, autonomous or semi-autonomous embodied artificial agents that generally possess human or animal-like qualities (such as responding to environmental stimuli, communicating, learning, performing human tasks, and making autonomous decisions) - have been designed to function as human friends. In light of such advances, immediate philosophical scrutiny is imperative in order to examine the extent to which human-robot interactions constitute genuine friendship and therefore contribute towards the good human life. Aristotle's conception of friendship is philosophically illuminating and sufficiently broad in scope to guide such analysis. On his account, it is necessary (though not sufficient) that for a friendship to exist between two agents - A and B - both agents must have a mutual love for one another. Aristotle claims that A loves B if: Condition 1: A desires those apparent good (qua pleasant, useful, or virtuous) properties attributable to B, and Condition 2: A has goodwill (wishes what is best) for B. This paper argues that human-robot interaction can (and does) successfully meet both conditions; as such, it demonstrates that robots and humans can reciprocally love one another. It will argue for this position by first justifying the claim that a human can desire apparent good features attributable to a robot (i.e., by taking them to be pleasant and/or useful) and outlining how it is that a human can wish a robot well in light of that robot's (quasi-) interests. Next, the paper will argue that a robot can (quasi-)desire certain properties that are attributable to a human before elucidating how it is possible for a robot to act in the interests of a human. Accordingly, this paper will conclude that it is already the case that humans can formulate relationships with robots that involve reciprocated love. This is significant because it suggests that social robots are candidates for human friendship and can therefore contribute toward flourishing human futures.

Keywords: ancient philosophy, friendship, inter-disciplinary applied ethics, love, social robotics

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Authors: Isabel Gouveia

Abstract:

Antimicrobial textile materials may significantly reduce the risk of infections and because they are able to absorb substances from the skin and release therapeutic compounds to the skin, they can also find applications as complementary therapy of skin-diseases as part of standard management. Although functional textiles may be a promising area in skin disease/injury management, as part of standard management, few offer complementary treatment even though they are well known to reduce scratching and aiding emollient absorption, reducing infection, and alleviating pruritus. The reason for this may rely on the low quality of supporting evidence and negative effect that antimicrobial agents may exert on skin microbiome, as for example additional irritation of the vulnerable skin, and by causing resistant bacteria. Several antimicrobial agents have been tested in textiles: quaternary ammonium compounds, silver, polyhexamethylene-biguanides and triclosan have been used, with success. They have powerful bactericidal activity but the majority have a reduce spectrum of microbial inhibition and may cause skin irritation, ecotoxicity and bacteria resistance. Furthermore, the rising flow of strains resistant to last-resort antibiotics rekindles interest in alternative strategies. In this regard, new functional textiles incorporating highly specific antimicrobial agents towards pathogenic bacteria, are required. Recent research has been conducted on naturally occurring antimicrobials as novel alternatives to antibiotics. Conscious of this need our team firstly reported new approaches using L-cysteine and antimicrobial peptides (AMP). Briefly, we were able to develop different immobilization processes towards 6 Log Reduction against bacteria such as S. aureus and K. pneumoniae. Therefore, here we present several innovative antimicrobial textiles incorporating AMP and L-Cysteine which may open new avenues for the medical textiles market and biomaterials in general. Team references will be discussed as an overview and for comparison purposes in terms of potential therapeutic applications.

Keywords: Antimicrobials, Antimicrobial Textiles, Biomedical Textiles, Biomimetic surface functionalization

Procedia PDF Downloads 97