Search results for: artificial cell

Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

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Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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Authors: F. Z. Benabid, F. Zouai, A. Douibi, D. Benachour

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These Fluorinated polymers and polyacrylics have known a wide use in the field of historical monuments. PVDF provides a great easiness to processing, a good UV resistance and good chemical inertia. Although the quality of physical characteristics of the PMMA and its low price with a respect to PVDF, its deterioration against UV radiations limits its use as protector agent for the stones. On the other hand, PVDF/PMMA blend is a compromise of a great development in the field of architectural restoration, since it is the best method in term of quality and price to make new polymeric materials having enhanced properties. Films of different compositions based on the two polymers within an adequate solvent (DMF) were obtained to perform an exposition to artificial ageing and to the salted fog, a spectroscopic analysis (FTIR and UV) and optical analysis (refractive index). Based on its great interest in the field of building, a variety of standard tests has been elaborated for the first time at the central laboratory of ENAP (Souk-Ahras) in order to evaluate our blend performance. The obtained results have allowed observing the behavior of the different compositions of the blend under various tests. The addition of PVDF to PMMA enhances the properties of this last to know the exhibition to the natural and artificial ageing and to the saline fog. On the other hand, PMMA enhances the optical properties of the blend. Finally, 70/30 composition of the blend is in concordance with results of previous works and it is the adequate proportion for an eventual application.

Keywords: blend, PVDF, PMMA, preservation, historic monuments

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Authors: Adiba Matin, Daniel Cabrera, Javiera Bellolio, Jasmine Stewart, Dana Gerberi (librarian), Nathan Cummins, Fernanda Bellolio

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OBJECTIVES: Artificial intelligence (AI) tools are becoming more prevalent in healthcare settings, particularly for diagnostic and therapeutic recommendations, with an expected surge in the incoming years. The bedside use of this technology for clinicians opens the possibility of disagreements between the recommendations from AI algorithms and clinicians’ judgment. There is a paucity in the literature analyzing nature and possible outcomes of these potential conflicts, particularly related to ethical considerations. The goal of this scoping review is to identify, analyze and classify current themes and potential strategies addressing ethical conflicts originating from the conflict between AI and human recommendations. METHODS: A protocol was written prior to the initiation of the study. Relevant literature was searched by a medical librarian for the terms of artificial intelligence, healthcare and liability, ethics, or conflict. Search was run in 2021 in Ovid Cochrane Central Register of Controlled Trials, Embase, Medline, IEEE Xplore, Scopus, and Web of Science Core Collection. Articles describing the role of AI in healthcare that mentioned conflict between humans and AI were included in the primary search. Two investigators working independently and in duplicate screened titles and abstracts and reviewed full-text of potentially eligible studies. Data was abstracted into tables and reported by themes. We followed methodological guidelines for Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). RESULTS: Of 6846 titles and abstracts, 225 full texts were selected, and 48 articles included in this review. 23 articles were included as original research and review papers. 25 were included as editorials and commentaries with similar themes. There was a lack of consensus in the included articles on who would be held liable for mistakes incurred by following AI recommendations. It appears that there is a dichotomy of the perceived ethical consequences depending on if the negative outcome is a result of a human versus AI conflict or secondary to a deviation from standard of care. Themes identified included transparency versus opacity of recommendations, data bias, liability of outcomes, regulatory framework, and the overall scope of artificial intelligence in healthcare. A relevant issue identified was the concern by clinicians of the “black box” nature of these recommendations and the ability to judge appropriateness of AI guidance. CONCLUSION AI clinical tools are being rapidly developed and adopted, and the use of this technology will create conflicts between AI algorithms and healthcare workers with various outcomes. In turn, these conflicts may have legal, and ethical considerations. There is limited consensus about the focus of ethical and liability for outcomes originated from disagreements. This scoping review identified the importance of framing the problem in terms of conflict between standard of care or not, and informed by the themes of transparency/opacity, data bias, legal liability, absent regulatory frameworks and understanding of the technology. Finally, limited recommendations to mitigate ethical conflicts between AI and humans have been identified. Further work is necessary in this field.

Keywords: ethics, artificial intelligence, emergency medicine, review

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Authors: Tran Duong Nguyen, Marwan Shagar, Qinghao Zeng, Aras Maqsoodi, Pardis Pishdad, Eunhwa Yang

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Construction supply chain management (CSCM) involves the collaboration of many disciplines and actors, which generates vast amounts of data. However, inefficient, fragmented, and non-standardized data storage often hinders this data exchange. The industry has adopted building information modeling (BIM) -a digital representation of a facility's physical and functional characteristics to improve collaboration, enhance transmission security, and provide a common data exchange platform. Still, the volume and complexity of data require tailored information categorization, aligning with stakeholders' preferences and demands. To address this, artificial intelligence (AI) can be integrated to handle this data’s magnitude and complexities. This research aims to develop an integrated and efficient approach for data exchange in CSCM by utilizing AI. The paper covers five main objectives: (1) Investigate existing framework and BIM adoption; (2) Identify challenges in data exchange; (3) Propose an integrated framework; (4) Enhance data transmission security; and (5) Develop data exchange in CSCM. The proposed framework demonstrates how integrating BIM and other technologies, such as cloud computing, blockchain, and AI applications, can significantly improve the efficiency and accuracy of data exchange in CSCM.

Keywords: construction supply chain management, BIM, data exchange, artificial intelligence

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Authors: Ahmed M. Hjazi, Bader M. Hjazi

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Protein 4.1 is a crucial component of complex interactions between the cytoskeleton and other junctional complex proteins. When the gene encoding this protein is altered, resulting in reduced expression, or when the protein is absent, the red cell undergoes a significant structural change. This research aims to achieve a deeper comprehension of the biochemical effects of red cell protein deficiency. A Tandem Mass Spectrometry Analysis (TMT-MS/MS) of patient cells lacking protein 4.1 compared to three healthy controls was achieved by the Proteomics Institute of the University of Bristol. The SDS-PAGE and Western blotting were utilized on the original patient sample and controls to partially confirm TMT MS/MS data analysis of the protein-4.1-deficient cells. Compared to healthy controls, protein levels in samples lacking protein 4.1 had a significantly higher concentration of proteins that probably originated from reticulocytes. This could occur if the patient has an elevated reticulocyte count. The increase in chaperone and reticulocyte-associated proteins was most notable in this study. This may result from elevated quantities of reticulocytes in patients with hereditary elliptocytosis.

Keywords: hereditary elliptocytosis, protein 4.1, red cells, tandem mass spectrometry data.

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Authors: Reza Ziaie Moayed, Saeideh Mohammadi

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Soft soil is used in many of civil engineering projects like coastal, marine and road projects. Because of low shear strength and stiffness of soft soils, large settlement and low bearing capacity will occur under superstructure loads. This will make the civil engineering activities more difficult and costlier. In the case of soft soils, improvement is a suitable method to increase the shear strength and stiffness for engineering purposes. In recent years, the artificial cementation of soil by cement and lime has been extensively used for soft soil improvement. Cement stabilization is a well-established technique for improving soft soils. Artificial cementation increases the shear strength and hardness of the natural soils. On the other hand, in soft soils, the use of piles to transfer loads to the depths of ground is usual. By using cement treated soil around the piles, high bearing capacity and low settlement in piles can be achieved. In the present study, lateral bearing capacity of short piles in cemented soils is investigated by numerical approach. For this purpose, three dimensional (3D) finite difference software, FLAC 3D is used. Cement treated soil has a strain hardening-softening behavior, because of breaking of bonds between cement agent and soil particle. To simulate such behavior, strain hardening-softening soil constitutive model is used for cement treated soft soil. Additionally, conventional elastic-plastic Mohr Coulomb constitutive model and linear elastic model are used for stress-strain behavior of natural soils and pile. To determine the parameters of constitutive models and also for verification of numerical model, the results of available triaxial laboratory tests on and insitu loading of piles in cement treated soft soil are used. Different parameters are considered in parametric study to determine the effective parameters on the bearing of the piles on cemented treated soils. In the present paper, the effect of various length and height of the artificial cemented area, different diameter and length of the pile and the properties of the materials are studied. Also, the effect of choosing a constitutive model for cemented treated soils in the bearing capacity of the pile is investigated.

Keywords: bearing capacity, cement-treated soils, FLAC 3D, pile

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Authors: Sheelagh Heugh, Michael Upton, Kriya Kalidas, Stephen Breen

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This article aims to create awareness of the opportunities and issues the artificial intelligence (AI) tool GPT-3 (Generative Pre-trained Transformer-3) brings to higher education. Technological disruptors have featured in higher education (HE) since Konrad Klaus developed the first functional programmable automatic digital computer. The flurry of technological advances, such as personal computers, smartphones, the world wide web, search engines, and artificial intelligence (AI), have regularly caused disruption and discourse across the educational landscape around harnessing the change for the good. Accepting AI influences are inevitable; we took mixed methods through participatory action research and evaluation approach. Joining HE communities, reviewing the literature, and conducting our own research around Chat GPT-3, we reviewed our institutional approach to changing our current practices and developing policy linked to assessments and the use of Chat GPT-3. We review the impact of GPT-3, a high-powered natural language processing (NLP) system first seen in 2020 on HE. Historically HE has flexed and adapted with each technological advancement, and the latest debates for educationalists are focusing on the issues around this version of AI which creates natural human language text from prompts and other forms that can generate code and images. This paper explores how Chat GPT-3 affects the current educational landscape: we debate current views around plagiarism, research misconduct, and the credibility of assessment and determine the tool's value in developing skills for the workplace and enhancing critical analysis skills. These questions led us to review our institutional policy and explore the effects on our current assessments and the development of new assessments. Conclusions: After exploring the pros and cons of Chat GTP-3, it is evident that this form of AI cannot be un-invented. Technology needs to be harnessed for positive outcomes in higher education. We have observed that materials developed through AI and potential effects on our development of future assessments and teaching methods. Materials developed through Chat GPT-3 can still aid student learning but lead to redeveloping our institutional policy around plagiarism and academic integrity.

Keywords: artificial intelligence, Chat GPT-3, intellectual property, plagiarism, research misconduct

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Authors: Mahnaz Khalafehnilsaz, Rozina Rahnama

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Introduction: The elderly population is growing rapidly, and with this growth comes an increased demand for healthcare services. Artificial intelligence (AI) has the potential to revolutionize the delivery of healthcare services to the elderly population. In this study, the various ways in which AI is used to create health content for elderly people and its transformative impact on the healthcare industry will be explored. Method: A systematic review of the literature was conducted to identify studies that have investigated the role of AI in creating health content specifically for elderly people. Several databases, including PubMed, Scopus, and Web of Science, were searched for relevant articles published between 2000 and 2022. The search strategy employed a combination of keywords related to AI, personalized health content, and the elderly. Studies that utilized AI to create health content for elderly individuals were included, while those that did not meet the inclusion criteria were excluded. A total of 20 articles that met the inclusion criteria were identified. Finding: The findings of this review highlight the diverse applications of AI in creating health content for elderly people. One significant application is the use of natural language processing (NLP), which involves the creation of chatbots and virtual assistants capable of providing personalized health information and advice to elderly patients. AI is also utilized in the field of medical imaging, where algorithms analyze medical images such as X-rays, CT scans, and MRIs to detect diseases and abnormalities. Additionally, AI enables the development of personalized health content for elderly patients by analyzing large amounts of patient data to identify patterns and trends that can inform healthcare providers in developing tailored treatment plans. Conclusion: AI is transforming the healthcare industry by providing a wide range of applications that can improve patient outcomes and reduce healthcare costs. From creating chatbots and virtual assistants to analyzing medical images and developing personalized treatment plans, AI is revolutionizing the way healthcare is delivered to elderly patients. Continued investment in this field is essential to ensure that elderly patients receive the best possible care.

Keywords: artificial intelligence, health content, older adult, healthcare

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

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Authors: Sylvie Michel, Sylvie Gerbaix, Marc Bidan

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Artificial intelligence (AI) can be held accountable for its detrimental impacts. This question gains heightened relevance given AI's pervasive reach across various domains, magnifying its power and potential. The expanding influence of AI raises fundamental ethical inquiries, primarily centering on biases, responsibility, and transparency. This encompasses discriminatory biases arising from algorithmic criteria or data, accidents attributed to autonomous vehicles or other systems, and the imperative of transparent decision-making. This article aims to stimulate reflection on AI accountability, denoting the necessity to elucidate the effects it generates. Accountability comprises two integral aspects: adherence to legal and ethical standards and the imperative to elucidate the underlying operational rationale. The objective is to initiate a reflection on the obstacles to this "accountability," facing the challenges of the complexity of artificial intelligence's system and its effects. Then, this article proposes to mobilize Edgar Morin's complex thought to encompass and face the challenges of this complexity. The first contribution is to point out the challenges posed by the complexity of A.I., with fractional accountability between a myriad of human and non-human actors, such as software and equipment, which ultimately contribute to the decisions taken and are multiplied in the case of AI. Accountability faces three challenges resulting from the complexity of the ethical issues combined with the complexity of AI. The challenge of the non-neutrality of algorithmic systems as fully ethically non-neutral actors is put forward by a revealing ethics approach that calls for assigning responsibilities to these systems. The challenge of the dilution of responsibility is induced by the multiplicity and distancing between the actors. Thus, a dilution of responsibility is induced by a split in decision-making between developers, who feel they fulfill their duty by strictly respecting the requests they receive, and management, which does not consider itself responsible for technology-related flaws. Accountability is confronted with the challenge of transparency of complex and scalable algorithmic systems, non-human actors self-learning via big data. A second contribution involves leveraging E. Morin's principles, providing a framework to grasp the multifaceted ethical dilemmas and subsequently paving the way for establishing accountability in AI. When addressing the ethical challenge of biases, the "hologrammatic" principle underscores the imperative of acknowledging the non-ethical neutrality of algorithmic systems inherently imbued with the values and biases of their creators and society. The "dialogic" principle advocates for the responsible consideration of ethical dilemmas, encouraging the integration of complementary and contradictory elements in solutions from the very inception of the design phase. Aligning with the principle of organizing recursiveness, akin to the "transparency" of the system, it promotes a systemic analysis to account for the induced effects and guides the incorporation of modifications into the system to rectify deviations and reintroduce modifications into the system to rectify its drifts. In conclusion, this contribution serves as an inception for contemplating the accountability of "artificial intelligence" systems despite the evident ethical implications and potential deviations. Edgar Morin's principles, providing a lens to contemplate this complexity, offer valuable perspectives to address these challenges concerning accountability.

Keywords: accountability, artificial intelligence, complexity, ethics, explainability, transparency, Edgar Morin

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Authors: Sam Weber, Deepak Mishra, Susan Wilde, Elizabeth Kramer

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The frequency and severity of cyanobacteria harmful blooms (CyanoHABs) have been increasing over time, with point and non-point source eutrophication and shifting climate paradigms being blamed as the primary culprits. Excessive nutrients, warm temperatures, quiescent water, and heavy and less regular rainfall create more conducive environments for CyanoHABs. CyanoHABs have the potential to produce a spectrum of toxins that cause gastrointestinal stress, organ failure, and even death in humans and animals. To promote enhanced, proactive CyanoHAB management, risk modeling using geospatial tools can act as predictive mechanisms to supplement current CyanoHAB monitoring, management and mitigation efforts. The risk maps would empower water managers to focus their efforts on high risk water bodies in an attempt to prevent CyanoHABs before they occur, and/or more diligently observe those waterbodies. For this research, exploratory spatial data analysis techniques were used to identify the strongest predicators for CyanoHAB blooms based on remote sensing-derived cyanobacteria cell density values for 771 waterbodies in the Georgia Piedmont and landscape characteristics of their watersheds. In-situ datasets for cyanobacteria cell density, nutrients, temperature, and rainfall patterns are not widely available, so free gridded geospatial datasets were used as proxy variables for assessing CyanoHAB risk. For example, the percent of a watershed that is agriculture was used as a proxy for nutrient loading, and the summer precipitation within a watershed was used as a proxy for water quiescence. Cyanobacteria cell density values were calculated using atmospherically corrected images from the European Space Agency’s Sentinel-2A satellite and multispectral instrument sensor at a 10-meter ground resolution. Seventeen explanatory variables were calculated for each watershed utilizing the multi-petabyte geospatial catalogs available within the Google Earth Engine cloud computing interface. The seventeen variables were then used in a multiple linear regression model, and the strongest predictors of cyanobacteria cell density were selected for the final regression model. The seventeen explanatory variables included land cover composition, winter and summer temperature and precipitation data, topographic derivatives, vegetation index anomalies, and soil characteristics. Watershed maximum summer temperature, percent agriculture, percent forest, percent impervious, and waterbody area emerged as the strongest predictors of cyanobacteria cell density with an adjusted R-squared value of 0.31 and a p-value ~ 0. The final regression equation was used to make a normalized cyanobacteria cell density index, and a Jenks Natural Break classification was used to assign waterbodies designations of low, medium, or high risk. Of the 771 waterbodies, 24.38% were low risk, 37.35% were medium risk, and 38.26% were high risk. This study showed that there are significant relationships between free geospatial datasets representing summer maximum temperatures, nutrient loading associated with land use and land cover, and the area of a waterbody with cyanobacteria cell density. This data analytics approach to CyanoHAB risk assessment corroborated the literature-established environmental triggers for CyanoHABs, and presents a novel approach for CyanoHAB risk mapping in waterbodies across the greater southeastern United States.

Keywords: cyanobacteria, land use/land cover, remote sensing, risk mapping

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Authors: Humayun Kabir, Amirul Hasan, Yu Miyaoka, Makiko Yamaguchi, Chisaki Kadota, Kazuaki Takehara

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From field isolates of Newcastle disease virus (NDV) in Japan, one avirulent strain, APMV/northern pintail/Japan/Aomori/2003 (dk-Aomori/03, NDV 261), was selected for its excellent thermostability, and the strain was heat-treated at 56℃ temperatures for 30 min with each passage into Vero cells to maintain thermostability and to adapt Vero cells. After serial 20 passages in Vero cells, it was named NDV Vero20. When growth curves were tested in Vero cells, NDV Vero20 grew well to compare the original NDV261. The HN gene was sequenced, and found motifs that show thermostability. The intracerebral pathogenicity index (ICPI) test score was 0. The thermostability of the virus was confirmed by storing it at different temperatures, including at 37°C. When susceptible chicks were inoculated with NDV Vero20 through eye drops, induced adequate levels of antibody were measured using a serum neutralization test. The results showed that NDV Vero20, a vaccine candidate strain is thermostable, Vero cell adapted, and has immunogenic potential, which would make as an alternative to the traditional embryonated chicken eggs-based vaccine.

Keywords: Newcastle disease virus, thermostability, vaccine, Vero cell adaptability

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Authors: Mannar R. Maurya, Bithika Sarkar, Fernando Avecilla

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Peroxidase activity is possibly successfully used for different industrial processes in medicine, chemical industry, food processing and agriculture. However, they bear some intrinsic drawback associated with denaturation by proteases, their special storage requisite and cost factor also. Now a day’s artificial enzyme mimics are becoming a research interest because of their significant applications over conventional organic enzymes for ease of their preparation, low price and good stability in activity and overcome the drawbacks of natural enzymes e.g serine proteases. At present, a large number of artificial enzymes have been synthesized by assimilating a catalytic center into a variety of schiff base complexes, ligand-anchoring, supramolecular complexes, hematin, porphyrin, nanoparticles to mimic natural enzymes. Although in recent years a several number of vanadium complexes have been reported by a continuing increase in interest in bioinorganic chemistry. To our best of knowledge, the investigation of artificial enzyme mimics of vanadium complexes is very less explored. Recently, our group has reported synthetic vanadium schiff base complexes capable of mimicking peroxidases. Herein, we have synthesized monoidovanadium(IV) and dioxidovanadium(V) complexes of pyrazoleone derivateis ( extensively studied on account of their broad range of pharmacological appication). All these complexes are characterized by various spectroscopic techniques like FT-IR, UV-Visible, NMR (1H, 13C and 51V), Elemental analysis, thermal studies and single crystal analysis. The peroxidase mimic activity has been studied towards oxidation of pyrogallol to purpurogallin with hydrogen peroxide at pH 7 followed by measuring kinetic parameters. The Michaelis-Menten behavior shows an excellent catalytic activity over its natural counterparts, e.g. V-HPO and HRP. The obtained kinetic parameters (Vmax, Kcat) were also compared with peroxidase and haloperoxidase enzymes making it a promising mimic of peroxidase catalyst. Also, the catalytic activity has been studied towards the oxidation of 1-phenylethanol in presence of H2O2 as an oxidant. Various parameters such as amount of catalyst and oxidant, reaction time, reaction temperature and solvent have been taken into consideration to get maximum oxidative products of 1-phenylethanol.

Keywords: oxovanadium(IV)/dioxidovanadium(V) complexes, NMR spectroscopy, Crystal structure, peroxidase mimic activity towards oxidation of pyrogallol, Oxidation of 1-phenylethanol

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Authors: Caleb B. Sagwa, Tobias O. Okeno, Alexander K. Kahi

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Dairy cattle production plays an important role in the Kenyan economy. However, high incidences of mastitis is a major setback to the productivity in this industry. The current dairy cattle breeding objective in Kenya does not include mastitis resistance, mainly because the economic value of mastitis resistance has not been determined. Therefore this study aimed at estimating the economic value of mastitis resistance in dairy cattle in Kenya. Initial input parameters were obtained from literature on dairy cattle production systems in the tropics. Selection index methodology was used to derive the economic value of mastitis resistance. Somatic cell count (SCC) was used an indicator trait for mastitis resistance. The economic value was estimated relative to milk yield (MY). Economic values were assigned to SCC in a selection index such that the overall gain in the breeding goal trait was maximized. The option of estimating the economic value for SCC by equating the response in the trait of interest to its index response was considered. The economic value of mastitis resistance was US $23.64 while maximum response to selection for MY was US $66.01. The findings of this study provide vital information that is a pre-requisite for the inclusion of mastitis resistance in the current dairy cattle breeding goal in Kenya.

Keywords: somatic cell count, milk quality, payment system, breeding goal

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Authors: Ashagrie Getnet Flattie

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Line-of-sight (LOS) information, data rates, good quality, and flexible network service are limited by the fact that, for the duration of any given connection, they experience severe variation in signal strength due to fading and path loss. Wireless system faces major challenges in achieving wide coverage and capacity without affecting the system performance and to access data everywhere, all the time. In this paper, the cell coverage and edge rate of different Multiple-input multiple-output (MIMO) schemes in 20 MHz Long Term Evolution (LTE) system under Unmanned Air Vehicles (UAV) platform are investigated. After some background on the enormous potential of UAV, MIMO, and LTE in wireless links, the paper highlights the presented system model which attempts to realize the various benefits of MIMO being incorporated into UAV platform. The performances of the three MIMO LTE schemes are compared with the performance of 4x4 MIMO LTE in UAV scheme carried out to evaluate the improvement in cell radius, BER, and data throughput of the system in different morphology. The results show that significant performance gains such as bit error rate (BER), data rate, and coverage can be achieved by using the presented scenario.

Keywords: LTE, MIMO, path loss, UAV

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Authors: Md. Maksudur Rahman Khan, Chee Wai Woon, Huei Ruey Ong, Vignes Rasiah, Chin Kui Cheng, Kar Min Chan, E. Baranitharan

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The present work represents a preparation of non-precious iron-based electrocatalyst (FeN) for ORR in air-cathode microbial fuel cell by pyrolysis treatment. Iron oxalate which recovered from the industrial wastewater and Phenanthroline (Phen) were used as the iron and nitrogen precursors, respectively in preparing FeN catalyst. The performance of as prepared catalyst (FeN) was investigated in a single chambered air cathode MFC in which anaerobic sludge was used as inoculum and palm oil mill effluent as substrate. The maximum open circuit potential (OCV) and the highest power density recorded were 0.543 V and 4.9 mW/m2, respectively. Physical characterization of FeN was elucidated by using Brunauner Emmett Teller (BET), X-Ray Diffraction (XRD) analysis and Field Emission Scanning Electron Microscopy (FESEM) while the electrochemical properties were characterized by cyclic voltammetry (CV) analysis. The presence of biofilm on anode surface was examined using FESEM and confirmed using Infrared Spectroscopy and Thermogravimetric Analysis. The findings of this study demonstrated that FeN is electrochemically active and further modification is needed to increase the ORR catalytic activity.

Keywords: iron based catalyst, microbial fuel cells, oxygen reduction reaction, palm oil mill effluent

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis

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Authors: Nonita Sarin, K.J.Singh, Anuj Kumar, Davinder Singh

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Polymeric 3D hydrogels have pivotal role in bone tissue regeneration applications. Hydrogels behave similar to the living tissues because they have large water imbibing capacity in swollen state and adjust their shape according to the tissues during tissue formation after implantation. On the other hand, hydrogels are very soft, fragile and lack mechanical strength. Incorporation of bioceramics can improve mechanical strength. Furthermore, bioceramics synthesized by sol gel technique may enhance the apatite formation and degradation rates which can lead to the increase in faster rates for new bone and tissue regeneration. Simulated body fluid (SBF) induces the poly-condensation of silanol groups which leads to formation of silica matrix and provide active sites for the precipitation of Ca2+ and PO43- ions to form apatite layer which is similar to mineral form of bone. Therefore, authors have synthesized bioceramic incorporated Polyacrylamide-carboxymethylcellulose hydrogels by free radical polymerization and bioceramic compositions of xSrO-(36-x)CaO-45SiO2-ySeO3-(12-y)P2O5-7MgO (where x=0,4 and y=0,2 mol%) were synthesized by sol gel technique. Bioceramics incorporated in polymer matrix induces quicker apatite formation during immersion in SBF by raising the pH with the release of alkaline ions during ion exchange process and the apatite formation takes place in alkaline medium. The behavior of samples PABC-0 (without bioceramics) and PABC-20 (with 20 wt% bioceramics) were evaluated by X-Ray Diffraction and FTIR. In term of bioactivity, it was observed that PABC-20 has shown hydroxyapatite (HA) formation on 1st day of immersion whereas, PABC-0 was shown apatite formation on 7th day of immersion in SBF. The rapid rate of HA growth on 1st day of immersion in SBF signifies easy regeneration of damaged bone tissues. Degradation studies have been undertaken in Phosphate Buffer Saline and PABC-20 exhibited slower degradation rate up to 9%as compared to PABC-0 up to 18%. Slower degradation rate is suitable for new tissue regeneration and cell attachment. Also, Zeta potential studies have been employed to check the surface charge and it has been observed that samples carry negative charge when immersed in SBF. In addition, the swelling test of the samples have been performed and relative swelling ratio % observed for PABC-0 is 607% and PABC-20 is 305%. This indicates that the incorporation of bioceramics leads to the filling up of the voids in between the polymer matrix which in result reduces porosity and increase the mechanical strength by filling the voids. The porosity of PABC-0 is 84% and PABC-20 is 72%. PABC-20 sample demonstrates that bioceramics incorporation reduce the porosity and improves mechanical strength. Also, maximum in vitro cell viability up to 98% with MG63 cell line has been observed which indicate that the bioceramic incorporated hydrogel(PABC-20) provide the alkaline medium which is suitable environment for cell growth.

Keywords: hydrogels, hydroxyapatite, MG63 cell line, zeta potential

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Authors: G. Eom, H. Kim, A. Hwang, T. Kang, B. Kim

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Telomerase activity is overexpressed in over 85% of human cancers while suppressed in normal somatic cells. Telomerase has been attracted as a universal cancer biomarker. Therefore, the development of effective telomerase activity detection methods is urgently demanded in cancer diagnosis and therapy. Herein, we report a nanogap-rich Au nanowire (NW) surface-enhanced Raman scattering (SERS) sensor for detection of human telomerase activity. The nanogap-rich Au NW SERS sensors were prepared simply by uniformly depositing nanoparticles (NPs) on single-crystalline Au NWs. We measured SERS spectra of methylene blue (MB) from 60 different nanogap-rich Au NWs and obtained the relative standard deviation (RSD) of 4.80%, confirming the superb reproducibility of nanogap-rich Au NW SERS sensors. The nanogap-rich Au NW SERS sensors enable us to detect telomerase activity in 0.2 cancer cells/mL. Furthermore, telomerase activity is detectable in 7 different cancer cell lines whereas undetectable in normal cell lines, which suggest the potential applicability of nanogap-rich Au NW SERS sensor in cancer diagnosis. We expect that the present nanogap-rich Au NW SERS sensor can be useful in biomedical applications including a diverse biomarker sensing.

Keywords: cancer biomarker, nanowires, surface-enhanced Raman scattering, telomerase

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Authors: Ji-Young Choi, Jungjin Kim, Sang-Sun Yun, Sangmee Ahn Jo

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Intracellular adhesion molecule1 (ICAM1) is a mediator of inflammation and involved in adhesion and transmigration of leukocytes to endothelial cells, resulting in enhancement of brain inflammation. We hypothesized that increase of ICAM1 expression in endothelial cells is an early step in the pathogenesis of brain diseases such as Alzheimer’s disease. Here, we report that ICAM1 expression is regulated by pro-inflammatory cytokine TNFa in human microvascular endothelial cell (HBMVEC). TNFa significantly increased ICAM1 mRNA and protein levels at the concentrations showing no cell toxicity. This increase was also shown in micro vessels of mouse brain 24 hours after treatment with TNFa (8 mg/kg, i.v). We then investigated the epigenetic mechanism involved in the induction of ICAM1 expression. Chromatin immunoprecipitation assay revealed that TNFa reduced methylation of histone3K9 (H3K9-2me) and histone3K27 (H3K27-3me), well-known modification as gene suppression, with in the ICAM1 promoter region. However, acetylation of H3K9 and H3K14, well-known modification as gene activation, was not changed by TNFa. Treatment of BIX01294, a specific inhibitor of histone methyltransferase G9a responsible for H3K9-2me, dramatically increased in ICAM1 mRNA and protein levels and overexpression of G9a gene suppressed TNFa-induced ICAM1 expression. In contrast, GSK126, an inhibitor of histone methyltransferase EZH2 responsible for H3K27-3me and valproic acid, an inhibitor of histone deacetylase (HDAC) did not affect ICAM1 expression. These results suggested that histone3 methylation is involved in ICAM1 repression. Moreover, TNFa or BIX01294-induced ICAM induction resulted in both enhancements in adhesion and transmigration of leukocyte on endothelial cell. This study demonstrates that TNFa upregulates ICAM1 expression through H3K9-2me and H3K27-3me within the ICAM1 promoter region, in which G9a is likely to play a pivotal role in ICAM1 transcription. Our study provides a novel mechanism for ICAM1 transcription regulation in HBMVEC.

Keywords: ICAM1, TNFa, HBMVEC, H3K9-2me

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Authors: Monica Anumula

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Nowadays human beings attain comfort zone artificially for heating, cooling and lighting the spaces they live, and their main importance is given to aesthetics of building and they are not designed to protect themselves from climate. They depend on artificial sources of energy resulting in energy wastage. In order to reduce the amount of energy being spent in the construction industry and Energy Package goals by 2020, new ways of constructing houses is required. The larger part of energy consumption of a building is directly related to architectural aspects hence nature has to be integrated into the building design to attain comfort zone and reduce the dependency on artificial source of energy. The research is to develop bioclimatic design strategies and techniques for the walls and roofs of Vijayawada houses. Study and analysis of design strategies and techniques of various cases like Kerala, Mangalore etc. for similar kind of climate is examined in this paper. Understanding the vernacular architecture and modern techniques of that various cases and implementing in the housing of Vijayawada not only decreases energy consumption but also enhances socio cultural values of Vijayawada. This study focuses on the comparison of vernacular techniques and modern building bio climatic strategies to attain thermal comfort and energy reduction in hot and humid climate. This research provides further thinking of new strategies which include both vernacular and modern bioclimatic techniques.

Keywords: bioclimatic design, energy consumption, hot and humid climates, thermal comfort

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yaokai Liu, Xinhong Wang, Yongsheng Zhou

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Performances analysis of remote sensing sensor is required to pursue a range of scientific research and application objectives. Laboratory analysis of any remote sensing instrument is essential, but not sufficient to establish a valid inflight one. In this study, with the aid of the in situ measurements and corresponding image of three-gray scale permanent artificial target, the in-flight radiometric performances analyses (in-flight radiometric calibration, dynamic range and response linearity, signal-noise-ratio (SNR), radiometric resolution) of self-developed short-wave infrared (SWIR) camera are performed. To acquire the inflight calibration coefficients of the SWIR camera, the at-sensor radiances (L_i) for the artificial targets are firstly simulated with in situ measurements (atmosphere parameter and spectral reflectance of the target) and viewing geometries using MODTRAN model. With these radiances and the corresponding digital numbers (DN) in the image, a straight line with a formulation of L = G × DN + B is fitted by a minimization regression method, and the fitted coefficients, G and B, are inflight calibration coefficients. And then the high point (L_H) and the low point (L_L) of dynamic range can be described as L_H= (G × DN_H + B) and L_L= B, respectively, where DN_H is equal to 2ⁿ − 1 (n is the quantization number of the payload). Meanwhile, the sensor’s response linearity (δ) is described as the correlation coefficient of the regressed line. The results show that the calibration coefficients (G and B) are 0.0083 W·sr⁻¹m⁻²µm⁻¹ and −3.5 W·sr⁻¹m⁻²µm⁻¹; the low point of dynamic range is −3.5 W·sr⁻¹m⁻²µm⁻¹ and the high point is 30.5 W·sr⁻¹m⁻²µm⁻¹; the response linearity is approximately 99%. Furthermore, a SNR normalization method is used to assess the sensor’s SNR, and the normalized SNR is about 59.6 when the mean value of radiance is equal to 11.0 W·sr⁻¹m⁻²µm⁻¹; subsequently, the radiometric resolution is calculated about 0.1845 W•sr^-1m^-2μm^-1. Moreover, in order to validate the result, a comparison of the measured radiance with a radiative-transfer-code-predicted over four portable artificial targets with reflectance of 20%, 30%, 40%, 50% respectively, is performed. It is noted that relative error for the calibration is within 6.6%.

Keywords: calibration and validation site, SWIR camera, in-flight radiometric calibration, dynamic range, response linearity

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Stephen M. Simmons, Stuart W. Baur, William L. Gillis

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In recent years, increasing concern has been shown towards the issue of light pollution, especially with the spread of brighter, more blue-rich LED bulbs. Much research has been conducted in order to study the effects of artificial light at night, and many adverse impacts have been discovered, such as circadian disruption, degradation of the night sky, and interference oftheprocesses and behaviors of plants and animals. Despite a plethora of informationin the literature regarding the numerous illeffects of this type of pollution, there does not appear to be a complete summary of these impacts, including their magnitudes, which would facilitate the balancing of risks and benefits in the design of an exterior lighting system. This paperprovides a comprehensive review of the known impacts of light pollution, divided into four categories - human health, night sky, plants, and animals; additionally, it includes a synopsis of what likely remains unknown at this point in time. This review will attempt to showcase the relative significance of differentimpacts within each category, as well as their sensitivity to changes in lighting specifications (brightness, color temperature, shielding, and mounting height). Methods to be employed in this research include an extensive literature review and the gathering of expert knowledge and opinions. The findings of this review will be used to inform the creation of an optimized lighting design for the Missouri University of Science and Technology campus. It is hoped that future research willexplore the known impacts of light pollution further, as well as search for what still remains to be found regarding the consequencesof artificial light at night.

Keywords: comprehensive review, impacts, light pollution, lighting design, literature review

Procedia PDF Downloads 140

Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

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As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

Procedia PDF Downloads 153

Authors: Zeyu Zhou, Ziyu Zhao, Xiaochen Yang, Ling AI, Heng Zhai, Stuart Holmes

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As a promising sustainable alternative to traditional fossil fuels, fuel cell technology is highly favoured due to its enhanced working efficiency and reduced emissions. In the context of high-temperature fuel cells (operating above 100 °C), the most commonly used proton exchange membrane (PEM) is the Polybenzimidazole (PBI) doped phosphoric acid (PA) membrane. Grafting is a promising strategy to advance PA-doped PBI PEM technology. The existing grafting modification on PBI PEMs mainly focuses on grafting phosphate-containing or alkaline groups onto the PBI molecular chains. However, quaternary ammonium-based grafting approaches face a common challenge. To initiate the N-alkylation reaction, deacidifying agents such as NaH, NaOH, KOH, K2CO3, etc., can lead to ionic crosslinking between the quaternary ammonium group and PBI. Polyvinylpyrrolidone (PVP) is another widely used polymer, the N-heterocycle groups within PVP endow it with a significant ability to absorb PA. Recently, PVP has attracted substantial attention in the field of fuel cells due to its reduced environmental impact and impressive fuel cell performance. However, due to the the poor compatibility of PVP in PBI, few research apply PVP in PA-doped PBI PEMs. This work introduces an innovative strategy to graft PVP onto PBI to form a network-like polymer. Due to the absence of quaternary ammonium groups, PVP does not pose issues related to crosslinking with PBI. Moreover, the nitrogen-containing functional groups on PVP provide PBI with a robust phosphoric acid retention ability. The nuclear magnetic resonance (NMR) hydrogen spectrum analysis results indicate the successful completion of the grafting reaction where N-alkylation reactions happen on both sides of the grafting agent 1,4-bis(chloromethyl)benzene. On one side, the reaction takes place with the hydrogen atoms on the imidazole groups of PBI, while on the other side, it reacts with the terminal amino group of PVP. The XPS results provide additional evidence from the perspective of the element. On synthesized PBI-g-PVP surfaces, there is an absence of chlorine (chlorine in grafting agent 1,4-bis(chloromethyl)benzene is substituted) element but a presence of sulfur element (sulfur element in terminal amino PVP appears in PBI), which demonstrates the occurrence of the grafting reaction and PVP is successfully grafted onto PBI. Prepare these modified membranes into MEA. It was found that during the fuel cell operation, all the grafted membranes showed substantial improvement in maximum current density and peak power density compared to unmodified one. For PBI-g-PVP 30, with a grafting degree of 22.4%, the peak power density reaches 1312 mW cm⁻², marking a 59.6% enhancement compared to the pristine PBI membrane. The improvement is caused by the improved PA binding ability of the membrane after grafting. The AST test result shows that the grafting membranes have better long-term durability and performance than unmodified membranes attributed to the presence of added PA binding sites, which can effectively prevent the PA leaching caused by proton migration. In conclusion, the test results indicate that grafting PVP onto PBI is a promising strategy which can effectively improve the fuel cell performance.

Keywords: fuel cell, grafting modification, PA doping ability, PVP

Procedia PDF Downloads 81

Authors: T. S. Olugbemi, T. S. Friday, O. O. Olusola

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This experiment was carried out to assess the effect of different stocking densities and vitamin C supplementation on the performance of Japanese quails. Five hundred and twenty (520) unsexed quail birds of two (2) weeks of age were allotted randomly into nine (9) groups with 3 replicates each in a 3x3 factorial arrangement (3 stocking density levels and 3 graded vitamin C levels) with densities of 150, 120, 90 cm2/bird(11, 16, 21 birds). During the five weeks growing trial (2- 6 weeks), results showed that stocking density had significant effects on final weight (131.59g compared to 111.10g for the lowest), total and daily weight gain. No significance difference was observed for feed conversion ratio, age at first lay and first egg weight. Observations on haematological parameters (packed cell volume (PCV), total protein (TP), haemoglobin, red blood cell (RBC), lymphocyte, heterophil) on stocking density showed no significant differences. Vitamin C supplementation at 50mg/kg and 100mg/kg did not have any significant effect on the growth performance parameters of growing quails. Stocking density at 150cm2/bird had a better performance with or without vitamin C supplementation hence it is recommended that stocking rates of quails between the ages of 2 – 6 weeks should not be below 150cm2/bird.

Keywords: anti-oxidants, performance, stress, stocking density

Procedia PDF Downloads 649

Authors: Chih-Hsin Lin, Shyh-Yuan Lee, Yuan-Min Lin

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For many tissue engineering applications, an important goal is to create functional tissues in-vitro, and such tissues to be viable, they have to be vascularized. Endothelial cells (EC) and endothelial progenitor cells (EPC) are promising candidates for vascularization. However, both of them have limited expansion capacity and autologous cells currently do not exist for either ECs or EPCs. Therefore, we use bone marrow mesenchymal stem cells (MSC) as a source material for ECs. Growth supplements are commonly used to induce MSC differentiation, and further improvements in differentiation conditions can be made by modifying the cell's growth environment. An example is pre-treatment of the growth dish with gas plasma, in order to modify the surface functional groups of the material that the cells are seeded on. In this work, we compare the effects of different gas plasmas on the growth and differentiation of MSCs. We treat the dish with different plasmas (CO2, N2, and O2) and then induce MSC differentiation with endothelial growth medium-2 (EGM-2). We find that EGM-2 by itself upregulates EC marker CD31 mRNA expression, but not VEGFR2, CD34, or vWF. However, these additional EC marker expressions were increased for cells seeded on plasma treated substrates. Specifically, for EC markers, we found that N2 plasma treatment upregulated CD31 and VEGFR-2 mRNA expressions; CO2 plasma treatment upregulated CD34 and vWF mRNA expressions. The osteogenic markers ALP and osteopontin mRNA expressions were markedly enhanced on all plasma-treated dishes. We also found that plasma treatment in conjunction with EGM-2 growth medium can enhance MSCs differentiation into endothelial-like cells and osteogenic-like cells. Our work shows that the effect of the growth medium (EGM-2) on MSCs differentiation is influenced by the plasma modified surface chemistry of the substrate. In conclusion, plasma surface modification can enhance EGM-2 effectiveness and induced both endothelial and osteogenic differentiation. Our findings provide a method to enhance EGM-2 based cell differentiation, with consequences for tissue engineering and stem cell biology applications.

Keywords: endothelial differentiation, EGM-2, osteogenesis, plasma treatment, surface modification

Procedia PDF Downloads 336

Authors: T. H. Huang, C. Y. Gao, C. H. Lin, J. L. Kwo, Y. K. Tseng

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The design and reliability of solar photovoltaic modules are crucial to the development of solar energy, and efforts are still being made to extend the life of photovoltaic modules to improve their efficiency because natural aging is time-consuming and does not provide manufacturers and investors with timely information, accelerated aging is currently the best way to estimate the life of photovoltaic modules. In this study, the accelerated aging of different light sources was combined with spectral response measurements to understand the effect of light sources on aging tests. In this study, there are two types of experimental samples: packaged and unpackaged and then irradiated with full-spectrum and UVC light sources for accelerated aging, as well as a control group without aging. The full-spectrum aging was performed by irradiating the solar cell with a xenon lamp like the solar spectrum for two weeks, while the accelerated aging was performed by irradiating the solar cell with a UVC lamp for two weeks. The samples were first visually observed, and infrared thermal images were taken, and then the electrical (IV) and Spectral Responsivity (SR) data were obtained by measuring the spectral response of the samples, followed by Scanning Electron Microscopy (SEM), Raman spectroscopy (Raman), and X-ray Diffraction (XRD) analysis. The results of electrical (IV) and Spectral Responsivity (SR) and material analyses were used to compare the differences between packaged and unpackaged solar cells with full spectral aging, accelerated UVC aging, and unaged solar cells. The main objective of this study is to compare the difference in the aging of packaged and unpackaged solar cells by irradiating different light sources. We determined by infrared thermal imaging that both full-spectrum aging and UVC accelerated aging increase the defects of solar cells, and IV measurements demonstrated that the conversion efficiency of solar cells decreases after full-spectrum aging and UVC accelerated aging. SEM observed some scorch marks on both unpackaged UVC accelerated aging solar cells and unpackaged full-spectrum aging solar cells. Raman spectroscopy examines the Si intensity of solar cells, and XRD confirms the crystallinity of solar cells by the intensity of Si and Ag winding peaks.

Keywords: solar cell, aging, spectral response measurement

Procedia PDF Downloads 105

Authors: Marasri Junsi, Sunisa Siripongvutikorn, Chutha Takahashi Yupanqui, Worrapong Usawakesmanee

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Thunbergia laurifolia has been used for folklore medicine purposes and consumed in the form of herbal tea in Thailand since ancient times. To evaluate the bioactive compounds of aqueous leave extract possessed antioxidant and anti-inflammatory activities. The antioxidant activities were examined by total extractable phenolic content (TPC), total extractable flavonoid content (TFC), ABTS radical scavenging, DPPH radical scavenging, FRAP reducing antioxidant power expressed as mg of gallic acid trolox and caffeic acid for the equivalents. Results indicated that the extract had high TPC and antioxidant activities. In addition, the HPLC-DAD analysis of phenolics and flavonoids indicated the presence of caffeic acid and rutin as bioactive compounds. Exposure of cells with the extract using nitric oxide (NO) production in RAW 264.7 murine macrophage cell line induced by lipopolysaccharide (LPS) was significantly reduced NO production and increased cell proliferation. The obtained results demonstrated that the extract contains a high potential to be used as anti-inflammatory and antioxidant substances.

Keywords: Thunbergia laurifolia, anti-inflammatory, antioxidant activities, RAW264.7

Procedia PDF Downloads 314