Search results for: green computing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3109

Search results for: green computing

199 Preparation and Characterization of Poly(L-Lactic Acid)/Oligo(D-Lactic Acid) Grafted Cellulose Composites

Authors: Md. Hafezur Rahaman, Mohd. Maniruzzaman, Md. Shadiqul Islam, Md. Masud Rana

Abstract:

With the growth of environmental awareness, enormous researches are running to develop the next generation materials based on sustainability, eco-competence, and green chemistry to preserve and protect the environment. Due to biodegradability and biocompatibility, poly (L-lactic acid) (PLLA) has a great interest in ecological and medical applications. Also, cellulose is one of the most abundant biodegradable, renewable polymers found in nature. It has several advantages such as low cost, high mechanical strength, biodegradability and so on. Recently, an immense deal of attention has been paid for the scientific and technological development of α-cellulose based composite material. PLLA could be used for grafting of cellulose to improve the compatibility prior to the composite preparation. Here it is quite difficult to form a bond between lower hydrophilic molecules like PLLA and α-cellulose. Dimmers and oligomers can easily be grafted onto the surface of the cellulose by ring opening or polycondensation method due to their low molecular weight. In this research, α-cellulose extracted from jute fiber is grafted with oligo(D-lactic acid) (ODLA) via graft polycondensation reaction in presence of para-toluene sulphonic acid and potassium persulphate in toluene at 130°C for 9 hours under 380 mmHg. Here ODLA is synthesized by ring opening polymerization of D-lactides in the presence of stannous octoate (0.03 wt% of lactide) and D-lactic acids at 140°C for 10 hours. Composites of PLLA with ODLA grafted α-cellulose are prepared by solution mixing and film casting method. Confirmation of grafting was carried out through FTIR spectroscopy and SEM analysis. A strongest carbonyl peak of FTIR spectroscopy at 1728 cm⁻¹ of ODLA grafted α-cellulose confirms the grafting of ODLA onto α-cellulose which is absent in α-cellulose. It is also observed from SEM photographs that there are some white areas (spot) on ODLA grafted α-cellulose as compared to α-cellulose may indicate the grafting of ODLA and consistent with FTIR results. Analysis of the composites is carried out by FTIR, SEM, WAXD and thermal gravimetric analyzer. Most of the FTIR characteristic absorption peak of the composites shifted to higher wave number with increasing peak area may provide a confirmation that PLLA and grafted cellulose have better compatibility in composites via intermolecular hydrogen bonding and this supports previously published results. Grafted α-cellulose distributions in composites are uniform which is observed by SEM analysis. WAXD studied show that only homo-crystalline structures of PLLA present in the composites. Thermal stability of the composites is enhanced with increasing the percentages of ODLA grafted α-cellulose in composites. As a consequence, the resultant composites have a resistance toward the thermal degradation. The effects of length of the grafted chain and biodegradability of the composites will be studied in further research.

Keywords: α-cellulose, composite, graft polycondensation, oligo(D-lactic acid), poly(L-lactic acid)

Procedia PDF Downloads 117
198 Flow Visualization and Mixing Enhancement in Y-Junction Microchannel with 3D Acoustic Streaming Flow Patterns Induced by Trapezoidal Triangular Structure using High-Viscous Liquids

Authors: Ayalew Yimam Ali

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The Y-shaped microchannel system is used to mix up low or high viscosities of different fluids, and the laminar flow with high-viscous water-glycerol fluids makes the mixing at the entrance Y-junction region a challenging issue. Acoustic streaming (AS) is time-average, a steady second-order flow phenomenon that could produce rolling motion in the microchannel by oscillating low-frequency range acoustic transducer by inducing acoustic wave in the flow field is the promising strategy to enhance diffusion mass transfer and mixing performance in laminar flow phenomena. In this study, the 3D trapezoidal Structure has been manufactured with advanced CNC machine cutting tools to produce the molds of trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm spine sharp-edge tip depth from PMMA glass (Polymethylmethacrylate) and the microchannel has been fabricated using PDMS (Polydimethylsiloxane) which could be grown-up longitudinally in Y-junction microchannel mixing region top surface to visualized 3D rolling steady acoustic streaming and mixing performance evaluation using high-viscous miscible fluids. The 3D acoustic streaming flow patterns and mixing enhancement were investigated using the micro-particle image velocimetry (μPIV) technique with different spine depth lengths, channel widths, high volume flow rates, oscillation frequencies, and amplitude. The velocity and vorticity flow fields show that a pair of 3D counter-rotating streaming vortices were created around the trapezoidal spine structure and observing high vorticity maps up to 8 times more than the case without acoustic streaming in Y-junction with the high-viscosity water-glycerol mixture fluids. The mixing experiments were performed by using fluorescent green dye solution with de-ionized water on one inlet side, de-ionized water-glycerol with different mass-weight percentage ratios on the other inlet side of the Y-channel and evaluated its performance with the degree of mixing at different amplitudes, flow rates, frequencies, and spine sharp-tip edge angles using the grayscale value of pixel intensity with MATLAB Software. The degree of mixing (M) characterized was found to significantly improved to 0.96.8% with acoustic streaming from 67.42% without acoustic streaming, in the case of 0.0986 μl/min flow rate, 12kHz frequency and 40V oscillation amplitude at y = 2.26 mm. The results suggested the creation of a new 3D steady streaming rolling motion with a high volume flow rate around the entrance junction mixing region, which promotes the mixing of two similar high-viscosity fluids inside the microchannel, which is unable to mix by the laminar flow with low viscous conditions.

Keywords: nano fabrication, 3D acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement

Procedia PDF Downloads 33
197 Teaching Timber: The Role of the Architectural Student and Studio Course within an Interdisciplinary Research Project

Authors: Catherine Sunter, Marius Nygaard, Lars Hamran, Børre Skodvin, Ute Groba

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Globally, the construction and operation of buildings contribute up to 30% of annual green house gas emissions. In addition, the building sector is responsible for approximately a third of global waste. In this context, the utilization of renewable resources in buildings, especially materials that store carbon, will play a significant role in the growing city. These are two reasons for introducing wood as a building material with a growing relevance. A third is the potential economic value in countries with a forest industry that is not currently used to capacity. In 2013, a four-year interdisciplinary research project titled “Wood Be Better” was created, with the principle goal to produce and publicise knowledge that would facilitate increased use of wood in buildings in urban areas. The research team consisted of architects, engineers, wood technologists and mycologists, both from research institutions and industrial organisations. Five structured work packages were included in the initial research proposal. Work package 2 was titled “Design-based research” and proposed using architecture master courses as laboratories for systematic architectural exploration. The aim was twofold: to provide students with an interdisciplinary team of experts from consultancies and producers, as well as teachers and researchers, that could offer the latest information on wood technologies; whilst at the same time having the studio course test the effects of the use of wood on the functional, technical and tectonic quality within different architectural projects on an urban scale, providing results that could be fed back into the research material. The aim of this article is to examine the successes and failures of this pedagogical approach in an architecture school, as well as the opportunities for greater integration between academic research projects, industry experts and studio courses in the future. This will be done through a set of qualitative interviews with researchers, teaching staff and students of the studio courses held each semester since spring 2013. These will investigate the value of the various experts of the course; the different themes of each course; the response to the urban scale, architectural form and construction detail; the effect of working with the goals of a research project; and the value of the studio projects to the research. In addition, six sample projects will be presented as case studies. These will show how the projects related to the research and could be collected and further analysed, innovative solutions that were developed during the course, different architectural expressions that were enabled by timber, and how projects were used as an interdisciplinary testing ground for integrated architectural and engineering solutions between the participating institutions. The conclusion will reflect on the original intentions of the studio courses, the opportunities and challenges faced by students, researchers and teachers, the educational implications, and on the transparent and inclusive discourse between the architectural researcher, the architecture student and the interdisciplinary experts.

Keywords: architecture, interdisciplinary, research, studio, students, wood

Procedia PDF Downloads 311
196 A Fermatean Fuzzy MAIRCA Approach for Maintenance Strategy Selection of Process Plant Gearbox Using Sustainability Criteria

Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

Procedia PDF Downloads 138
195 Control of Belts for Classification of Geometric Figures by Artificial Vision

Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

Procedia PDF Downloads 378
194 Gender Construction in Contemporary Dystopian Fiction in Young Adult Literature: A South African Example

Authors: Johan Anker

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The purpose of this paper is to discuss the nature of gender construction in modern dystopian fiction, the development of this genre in Young Adult Literature and reasons for the enormous appeal on the adolescent readers. A recent award winning South African text in this genre, The Mark by Edith Bullring (2014), will be used as example while also comparing this text to international bestsellers like Divergent (Roth:2011), The Hunger Games (Collins:2008) and others. Theoretical insights from critics and academics in the field of children’s literature, like Ames, Coats, Bradford, Booker, Basu, Green-Barteet, Hintz, McAlear, McCallum, Moylan, Ostry, Ryan, Stephens and Westerfield will be referred to and their insights used as part of the analysis of The Mark. The role of relevant and recurring themes in this genre, like global concerns, environmental destruction, liberty, self-determination, social and political critique, surveillance and repression by the state or other institutions will also be referred to. The paper will shortly refer to the history and emergence of dystopian literature as genre in adult and young adult literature as part of the long tradition since the publishing of Orwell’s 1984 and Huxley’s Brave New World. Different factors appeal to adolescent readers in the modern versions of this hybrid genre for young adults: teenage protagonists who are questioning the underlying values of a flawed society like an inhuman or tyrannical government, a growing understanding of the society around them, feelings of isolation and the dynamic of relationships. This unease leads to a growing sense of the potential to act against society (rebellion), and of their role as agents in a larger community and independent decision-making abilities. This awareness also leads to a growing sense of self (identity and agency) and the development of romantic relationships. The specific modern tendency of a female protagonist as leader in the rebellion against state and state apparatus, who gains in agency and independence in this rebellion, an important part of the identification with and construction of gender, while being part of the traditional coming-of-age young adult novel will be emphasized. A comparison between the traditional themes, structures and plots of young adult literature (YAL) with adult dystopian literature and those of recent dystopian YAL will be made while the hybrid nature of this genre and the 'sense of unease' but also of hope, as an essential part of youth literature, in the closure to these novels will be discussed. Important questions about the role of the didactic nature of these texts and the political issues and the importance of the formation of agency and identity for the young adult reader, as well as identification with the protagonists in this genre, are also part of this discussion of The Mark and other YAL novels.

Keywords: agency, dystopian literature, gender construction, young adult literature

Procedia PDF Downloads 190
193 The Role of Professional Teacher Development in Introducing Trilingual Education into the Secondary School Curriculum: Lessons from Kazakhstan, Central Asia

Authors: Kairat Kurakbayev, Dina Gungor, Adil Ashirbekov, Assel Kambatyrova

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Kazakhstan, a post-Soviet economy located in the Central Asia, is making great efforts to internationalize its national system of education. The country is very ambitious in making the national economy internationally competitive and education has become one of the main pillars of the nation’s strategic development plan for 2030. This paper discusses the role of professional teacher development in upgrading the secondary education curriculum with the introduction of English as a medium of instruction (EMI) in grades 10-11 grades. Having Kazakh as the state language and Russian as the official language, English bears a status of foreign language in the country. The development of trilingual education is very high on the agenda of the Ministry of Education and Science. It is planned that by 2019 STEM-related subjects – Biology, Chemistry, Computing and Physics – will be taught in EMI. Introducing English-medium education appears to be a very drastic reform and the teaching cadre is the key driver here. At the same time, after the collapse of the Soviet Union, the teaching profession is still struggling to become attractive in the eyes of the local youth. Moreover, the quality of Kazakhstan’s secondary education is put in question by OECD national review reports. The paper presents a case study of the nation-wide professional development programme arranged for 5 010 school teachers so that they could be able to teach their content subjects in English starting from 2019 onwards. The study is based on the mixed methods research involving the data derived from the surveys and semi-structured interviews held with the programme participants, i.e. school teachers. The findings of the study imply the significance of the school teachers’ attitudes towards the top-down reform of trilingual education. The qualitative research data reveal the teachers’ beliefs about advantages and disadvantages of having their content subjects (e.g. Biology or Chemistry) taught in EMI. The study highlights teachers’ concerns about their professional readiness to implement the top-down reform of English-medium education and discusses possible risks of academic underperforming on the part of students whose English language proficiency is not advanced. This paper argues that for the effective implementation of the English-medium education in secondary schools, the state should adopt a comprehensive approach to upgrading the national academic system where teachers’ attitudes and beliefs play the key role in making the trilingual education policy effective. The study presents lessons for other national academic systems considering to transfer its secondary education to English as a medium of instruction.

Keywords: teacher education, teachers' beliefs, trilingual education, case study

Procedia PDF Downloads 181
192 Application of Deep Learning Algorithms in Agriculture: Early Detection of Crop Diseases

Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 119
191 Landing Performance Improvement Using Genetic Algorithm for Electric Vertical Take Off and Landing Aircrafts

Authors: Willian C. De Brito, Hernan D. C. Munoz, Erlan V. C. Carvalho, Helder L. C. De Oliveira

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In order to improve commute time for small distance trips and relieve large cities traffic, a new transport category has been the subject of research and new designs worldwide. The air taxi travel market promises to change the way people live and commute by using the concept of vehicles with the ability to take-off and land vertically and to provide passenger’s transport equivalent to a car, with mobility within large cities and between cities. Today’s civil air transport remains costly and accounts for 2% of the man-made CO₂ emissions. Taking advantage of this scenario, many companies have developed their own Vertical Take Off and Landing (VTOL) design, seeking to meet comfort, safety, low cost and flight time requirements in a sustainable way. Thus, the use of green power supplies, especially batteries, and fully electric power plants is the most common choice for these arising aircrafts. However, it is still a challenge finding a feasible way to handle with the use of batteries rather than conventional petroleum-based fuels. The batteries are heavy and have an energy density still below from those of gasoline, diesel or kerosene. Therefore, despite all the clear advantages, all electric aircrafts (AEA) still have low flight autonomy and high operational cost, since the batteries must be recharged or replaced. In this sense, this paper addresses a way to optimize the energy consumption in a typical mission of an aerial taxi aircraft. The approach and landing procedure was chosen to be the subject of an optimization genetic algorithm, while final programming can be adapted for take-off and flight level changes as well. A real tilt rotor aircraft with fully electric power plant data was used to fit the derived dynamic equations of motion. Although a tilt rotor design is used as a proof of concept, it is possible to change the optimization to be applied for other design concepts, even those with independent motors for hover and cruise flight phases. For a given trajectory, the best set of control variables are calculated to provide the time history response for aircraft´s attitude, rotors RPM and thrust direction (or vertical and horizontal thrust, for independent motors designs) that, if followed, results in the minimum electric power consumption through that landing path. Safety, comfort and design constraints are assumed to give representativeness to the solution. Results are highly dependent on these constraints. For the tested cases, performance improvement ranged from 5 to 10% changing initial airspeed, altitude, flight path angle, and attitude.

Keywords: air taxi travel, all electric aircraft, batteries, energy consumption, genetic algorithm, landing performance, optimization, performance improvement, tilt rotor, VTOL design

Procedia PDF Downloads 115
190 Sustainable Solid Waste Management Solutions for Asian Countries Using the Potential in Municipal Solid Waste of Indian Cities

Authors: S. H. Babu Gurucharan, Priyanka Kaushal

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Majority of the world's population is expected to live in the Asia and Pacific region by 2050 and thus their cities will generate the maximum waste. India, being the second populous country in the world, is an ideal case study to identify a solution for Asian countries. Waste minimisation and utilisation have always been part of the Indian culture. During rapid urbanisation, our society lost the art of waste minimisation and utilisation habits. Presently, Waste is not considered as a resource, thus wasting an opportunity to tap resources. The technologies in vogue are not suited for effective treatment of large quantities of generated solid waste, without impacting the environment and the population. If not treated efficiently, Waste can become a silent killer. The article is trying to highlight the Indian municipal solid waste scenario as a key indicator of Asian waste management and recommend sustainable waste management and suggest effective solutions to treat the Solid Waste. The methods followed during the research were to analyse the solid waste data on characteristics of solid waste generated in Indian cities, then evaluate the current technologies to identify the most suitable technology in Indian conditions with minimal environmental impact, interact with the technology technical teams, then generate a technical process specific to Indian conditions and further examining the environmental impact and advantages/ disadvantages of the suggested process. The most important finding from the study was the recognition that most of the current municipal waste treatment technologies being employed, operate sub-optimally in Indian conditions. Therefore, the study using the available data, generated heat and mass balance of processes to arrive at the final technical process, which was broadly divided into Waste processing, Waste Treatment, Power Generation, through various permutations and combinations at each stage to ensure that the process is techno-commercially viable in Indian conditions. Then environmental impact was arrived through secondary sources and a comparison of environmental impact of different technologies was tabulated. The major advantages of the suggested process are the effective use of waste for resource generation both in terms of maximised power output or conversion to eco-friendly products like biofuels or chemicals using advanced technologies, minimum environmental impact and the least landfill requirement. The major drawbacks are the capital, operations and maintenance costs. The existing technologies in use in Indian municipalities have their own limitations and the shortlisted technology is far superior to other technologies in vogue. Treatment of Municipal Solid Waste with an efficient green power generation is possible through a combination of suitable environment-friendly technologies. A combination of bio-reactors and plasma-based gasification technology is most suitable for Indian Waste and in turn for Asian waste conditions.

Keywords: calorific value, gas fermentation, landfill, municipal solid waste, plasma gasification, syngas

Procedia PDF Downloads 184
189 Investigating Seasonal Changes of Urban Land Cover with High Spatio-Temporal Resolution Satellite Data via Image Fusion

Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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188 MOF [(4,4-Bipyridine)₂(O₂CCH₃)₂Zn]N as Heterogeneous Acid Catalysts for the Transesterification of Canola Oil

Authors: H. Arceo, S. Rincon, C. Ben-Youssef, J. Rivera, A. Zepeda

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Biodiesel has emerged as a material with great potential as a renewable energy replacement to current petroleum-based diesel. Recently, biodiesel production is focused on the development of more efficient, sustainable process with lower costs of production. In this sense, a “green” approach to biodiesel production has stimulated the use of sustainable heterogeneous acid catalysts, that are better alternatives to conventional processes because of their simplicity and the simultaneous promotion of esterification and transesterification reactions from low-grade, highly-acidic and water containing oils without the formation of soap. The focus of this methodology is the development of new heterogeneous catalysts that under ordinary reaction conditions could reach yields similar to homogeneous catalysis. In recent years, metal organic frameworks (MOF) have attracted much interest for their potential as heterogeneous acid catalysts. They are crystalline porous solids formed by association of transition metal ions or metal–oxo clusters and polydentate organic ligands. This hybridization confers MOFs unique features such as high thermal stability, larger pore size, high specific area, high selectivity and recycling potential. Thus, MOF application could be a way to improve the biodiesel production processes. In this work, we evaluated the catalytic activity of MOF [(4,4-bipyridine)2(O₂CCH₃)2Zn]n (MOF Zn-I) for the synthesis of biodiesel from canola oil. The reaction conditions were optimized using the response surface methodology with a compound design central with 24. The variables studied were: Reaction temperature, amount of catalyst, molar ratio oil: MetOH and reaction time. The preparation MOF Zn-I was performed by mixing 5 mmol 4´4 dipyridine dissolved in 25 mL methanol with 10 mmol Zn(O₂CCH₃)₂ ∙ 2H₂O in 25 mL water. The crystals were obtained by slow evaporation of the solvents at 60°C for 18 h. The prepared catalyst was characterized using X-ray diffraction (XRD) and Fourier transform infrared spectrometer (FT-IR). The prepared catalyst was characterized using X-ray diffraction (XRD) and Fourier transform infrared spectrometer (FT-IR). Experiments were performed using commercially available canola oil in ace pressure tube under continuous stirring. The reaction was filtered and vacuum distilled to remove the catalyst and excess alcohol, after which it was centrifuged to separate the obtained biodiesel and glycerol. 1H NMR was used to calculate the process yield. GC-MS was used to quantify the fatty acid methyl ester (FAME). The results of this study show that the acid catalyst MOF Zn-I could be used as catalyst for biodiesel production through heterogeneous transesterification of canola oil with FAME yield 82 %. The optimum operating condition for the catalytic reaction were of 142°C, 0.5% catalyst/oil weight ratio, 1:30 oil:MeOH molar ratio and 5 h reaction time.

Keywords: fatty acid methyl ester, heterogeneous acid catalyst, metal organic framework, transesterification

Procedia PDF Downloads 279
187 Design Approach to Incorporate Unique Performance Characteristics of Special Concrete

Authors: Devendra Kumar Pandey, Debabrata Chakraborty

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The advancement in various concrete ingredients like plasticizers, additives and fibers, etc. has enabled concrete technologists to develop many viable varieties of special concretes in recent decades. Such various varieties of concrete have significant enhancement in green as well as hardened properties of concrete. A prudent selection of appropriate type of concrete can resolve many design and application issues in construction projects. This paper focuses on usage of self-compacting concrete, high early strength concrete, structural lightweight concrete, fiber reinforced concrete, high performance concrete and ultra-high strength concrete in the structures. The modified properties of strength at various ages, flowability, porosity, equilibrium density, flexural strength, elasticity, permeability etc. need to be carefully studied and incorporated into the design of the structures. The paper demonstrates various mixture combinations and the concrete properties that can be leveraged. The selection of such products based on the end use of structures has been proposed in order to efficiently utilize the modified characteristics of these concrete varieties. The study involves mapping the characteristics with benefits and savings for the structure from design perspective. Self-compacting concrete in the structure is characterized by high shuttering loads, better finish, and feasibility of closer reinforcement spacing. The structural design procedures can be modified to specify higher formwork strength, height of vertical members, cover reduction and increased ductility. The transverse reinforcement can be spaced at closer intervals compared to regular structural concrete. It allows structural lightweight concrete structures to be designed for reduced dead load, increased insulation properties. Member dimensions and steel requirement can be reduced proportionate to about 25 to 35 percent reduction in the dead load due to self-weight of concrete. Steel fiber reinforced concrete can be used to design grade slabs without primary reinforcement because of 70 to 100 percent higher tensile strength. The design procedures incorporate reduction in thickness and joint spacing. High performance concrete employs increase in the life of the structures by improvement in paste characteristics and durability by incorporating supplementary cementitious materials. Often, these are also designed for slower heat generation in the initial phase of hydration. The structural designer can incorporate the slow development of strength in the design and specify 56 or 90 days strength requirement. For designing high rise building structures, creep and elasticity properties of such concrete also need to be considered. Lastly, certain structures require a performance under loading conditions much earlier than final maturity of concrete. High early strength concrete has been designed to cater to a variety of usages at various ages as early as 8 to 12 hours. Therefore, an understanding of concrete performance specifications for special concrete is a definite door towards a superior structural design approach.

Keywords: high performance concrete, special concrete, structural design, structural lightweight concrete

Procedia PDF Downloads 305
186 Neoliberalism and Environmental Justice: A Critical Examination of Corporate Greenwashing

Authors: Arnav M. Raval

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This paper critically examines the neoliberal economic model and its role in enabling corporate greenwashing, a practice where corporations deceptively market themselves as environmentally responsible while continuing harmful environmental practices. Through a rigorous focus on the neoliberal emphasis of free markets, deregulation, and minimal government intervention, this paper explores how these policies have set the stage for corporations to externalize environmental costs and engage in superficial sustainability initiatives. Within this framework, companies often bypass meaningful environmental reform, opting for strategies that enhance their public image without addressing their actual environmental impacts. The paper also draws on the works of critical theorists Theodor Adorno, Max Horkheimer, and Herbert Marcuse, particularly their critiques of capitalist society and its tendency to commodify social values. This paper argues that neoliberal capitalism has commodified environmentalism, transforming genuine ecological responsibility into a marketable product. Through corporate social responsibility initiatives, corporations have created the illusion of sustainability while masking deeper environmental harm. Under neoliberalism, these initiatives often serve as public relations tools rather than genuine commitments to environmental justice and sustainability. This commodification has become particularly dangerous because as it manipulates consumer perceptions and diverts attention away from the structural causes of environmental degradation. The analysis also examines how greenwashing practices have disproportionately affected marginalized communities, particularly in the global South, where environmental costs are often externalized. As these corporations promote their “sustainability” in wealthier markets, these marginalized communities bear the brunt of their pollution, resource depletion, and other forms of environmental degradation. This dynamic underscores the inherent injustice within neoliberal environmental policies, as those most vulnerable to environmental risks are often neglected, as companies reap the benefits of corporate sustainability efforts at their expense. Finally, this paper calls for a fundamental transition away from neoliberal market-driven solutions, which prioritize corporate profit over genuine ecological reform. It advocates for stronger regulatory frameworks, transparent third-party certifications, and a more collective approach to environmental governance. In order to ensure genuine corporate accountability, governments and institutions must move beyond superficial green initiatives and market-based solutions, shifting toward policies that enforce real environmental responsibility and prioritize environmental justice for all communities. Through the critique of the neoliberal system and its commodification of environmentalism, this paper has highlighted the urgent need to rethink how environmental responsibility is defined and enacted in the corporate world. Without systemic change, greenwashing will continue to undermine both ecological sustainability and social justice, leaving the most vulnerable populations to suffer the consequences.

Keywords: critical theory, environmental justice, greenwashing, neoliberalism

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185 Municipal Action Against Urbanisation-Induced Warming: Case Studies from Jordan, Zambia, and Germany

Authors: Muna Shalan

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Climate change is a systemic challenge for cities, with its impacts not happening in isolation but rather intertwined, thus increasing hazards and the vulnerability of the exposed population. The increase in the frequency and intensity of heat waves, for example, is associated with multiple repercussions on the quality of life of city inhabitants, including health discomfort, a rise in mortality and morbidity, increasing energy demand for cooling, and shrinking of green areas due to drought. To address the multi-faceted impact of urbanisation-induced warming, municipalities and local governments are challenged with devising strategies and implementing effective response measures. Municipalities are recognising the importance of guiding urban concepts to drive climate action in the urban environment. An example is climate proofing, which refers to a process of mainstreaming climate change into development strategies and programs, i.e., urban planning is viewed through a climate change lens. There is a multitude of interconnected aspects that are critical to paving the path toward climate-proofing of urban areas and avoiding poor planning of layouts and spatial arrangements. Navigating these aspects through an analysis of the overarching practices governing municipal planning processes, which is the focus of this research, will highlight entry points to improve procedures, methods, and data availability for optimising planning processes and municipal actions. By employing a case study approach, the research investigates how municipalities in different contexts, namely in the city of Sahab in Jordan, Chililabombwe in Zambia, and the city of Dortmund in Germany, are integrating guiding urban concepts to shrink the deficit in adaptation and mitigation and achieve climate proofing goals in their respective local contexts. The analysis revealed municipal strategies and measures undertaken to optimize existing building and urban design regulations by introducing key performance indicators and improving in-house capacity. Furthermore, the analysis revealed that establishing or optimising interdepartmental communication frameworks or platforms is key to strengthening the steering structures governing local climate action. The most common challenge faced by municipalities is related to their role as a regulator and implementers, particularly in budget analysis and instruments for cost recovery of climate action measures. By leading organisational changes related to improving procedures and methods, municipalities can mitigate the various challenges that may emanate from uncoordinated planning and thus promote action against urbanisation-induced warming.

Keywords: urbanisation-induced warming, response measures, municipal planning processes, key performance indicators, interdepartmental communication frameworks, cost recovery

Procedia PDF Downloads 69
184 Quantitative, Preservative Methodology for Review of Interview Transcripts Using Natural Language Processing

Authors: Rowan P. Martnishn

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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.

Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding

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183 Devotional Informant and Diagenetic Alterations, Influences of Facies and Fine Kaolinite Formation Migration on Sandstone’ Reservoir Quality, Sarir Formation, Sirt

Authors: Faraj M. Elkhatri, Hana Ellafi

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In recent years, there has been a growing recognition of the potential of marine-based functional foods and combination therapies in promoting a healthy lifestyle and exploring their effectiveness in preventing or treating diseases. The combination of marine bioactive compounds or extracts offers synergistic or enhancement effects through various mechanisms, including multi-target actions, improved bioavailability, enhanced bioactivity, and mitigation of potential adverse effects. Both the green-lipped mussel (GLM) and fucoidan derived from brown seaweed are rich in bioactivities. These two, mussel and fucoidan, have not been previously formulated together. This study aims to combine GLM oil from Perna canaliculus with low molecular weight fucoidan (LMWF) extracted from Undaria pinnatifida to investigate the unique mixture’s anti-inflammatory and antioxidant properties. The cytotoxicity of individual compounds and combinations was assessed using the MTT assay in (THP-1 and RAW264.7) cell lines. The anti-inflammatory activity of mussel-fucoidan was evaluated by treating LPS-stimulated human monocyte and macrophage (THP1-1) cells. Subsequently, the inflammatory cytokines released into the supernatant of these cell lines were quantified via ELISA. Antioxidant activity was determined by using the free radical scavenging assay (DPPH). DPPH assay demonstrated that the radical scavenging activity of the combinations, particularly at concentrations exceeding 1 mg/ml, showed a significantly higher percentage of inhibition when compared to the individual component. This suggests an enhancement effect when the two compounds are combined, leading to increased antioxidant activity. In terms of immunomodulatory activity, the individual compounds exhibited distinct behaviors. GLM oil displayed a higher ability to suppress the cytokine TNF- compared to LMWF. Interestingly, the LMWF fraction, when used individually, did not demonstrate TNF- suppression. However, when combined with GLM, the TNF- suppression (anti-inflammatory) activity of the combination was better than GLM or LWMF alone. This observation underscores the potential for enhancement interactions between the two components in terms of anti-inflammatory properties. This study revealed that each individual compound, LMWF, and GLM, possesses unique and notable bioactivity. The combination of these two individual compounds results in an enhancement effect, where the bioactivity of each is enhanced, creating a superior combination. This suggests that the combination of LMWF and GLM has the potential to offer a more potent and multifaceted therapeutic effect, particularly in the context of antioxidant and anti-inflammatory activities. These findings hold promise for the development of novel therapeutic interventions or supplements that harness the enhancement effects.

Keywords: formation damage, porosity loses, pore throat, quartz cement

Procedia PDF Downloads 57
182 Optimization of Biomass Production and Lipid Formation from Chlorococcum sp. Cultivation on Dairy and Paper-Pulp Wastewater

Authors: Emmanuel C. Ngerem

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The ever-increasing depletion of the dominant global form of energy (fossil fuels) calls for the development of sustainable and green alternative energy sources such as bioethanol, biohydrogen, and biodiesel. The production of the major biofuels relies on biomass feedstocks that are mainly derived from edible food crops and some inedible plants. One suitable feedstock with great potential as raw material for biofuel production is microalgal biomass. Despite the tremendous attributes of microalgae as a source of biofuel, their cultivation requires huge volumes of freshwater, thus posing a serious threat to commercial-scale production and utilization of algal biomass. In this study, a multi-media wastewater mixture for microalgae growth was formulated and optimized. Moreover, the obtained microalgae biomass was pre-treated to reduce sugar recovery and was compared with previous studies on microalgae biomass pre-treatment. The formulated and optimized mixed wastewater media for biomass and lipid accumulation was established using the simplex lattice mixture design. Based on the superposition approach of the potential results, numerical optimization was conducted, followed by the analysis of biomass concentration and lipid accumulation. The coefficients of regression (R²) of 0.91 and 0.98 were obtained for biomass concentration and lipid accumulation models, respectively. The developed optimization model predicted optimal biomass concentration and lipid accumulation of 1.17 g/L and 0.39 g/g, respectively. It suggested 64.69% dairy wastewater (DWW) and 35.31% paper and pulp wastewater (PWW) mixture for biomass concentration, 34.21% DWW, and 65.79% PWW for lipid accumulation. Experimental validation generated 0.94 g/L and 0.39 g/g of biomass concentration and lipid accumulation, respectively. The obtained microalgae biomass was pre-treated, enzymatically hydrolysed, and subsequently assessed for reducing sugars. The optimization of microwave pre-treatment of Chlorococcum sp. was achieved using response surface methodology (RSM). Microwave power (100 – 700 W), pre-treatment time (1 – 7 min), and acid-liquid ratio (1 – 5%) were selected as independent variables for RSM optimization. The optimum conditions were achieved at microwave power, pre-treatment time, and acid-liquid ratio of 700 W, 7 min, and 32.33:1, respectively. These conditions provided the highest amount of reducing sugars at 10.73 g/L. Process optimization predicted reducing sugar yields of 11.14 g/L on microwave-assisted pre-treatment of 2.52% HCl for 4.06 min at 700 watts. Experimental validation yielded reducing sugars of 15.67 g/L. These findings demonstrate that dairy wastewater and paper and pulp wastewater that could pose a serious environmental nuisance. They could be blended to form a suitable microalgae growth media, consolidating the potency of microalgae as a viable feedstock for fermentable sugars. Also, the outcome of this study supports the microalgal wastewater biorefinery concept, where wastewater remediation is coupled with bioenergy production.

Keywords: wastewater cultivation, mixture design, lipid, biomass, nutrient removal, microwave, Chlorococcum, raceway pond, fermentable sugar, modelling, optimization

Procedia PDF Downloads 41
181 A Web and Cloud-Based Measurement System Analysis Tool for the Automotive Industry

Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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180 Devulcanization of Waste Rubber Using Thermomechanical Method Combined with Supercritical CO₂

Authors: L. Asaro, M. Gratton, S. Seghar, N. Poirot, N. Ait Hocine

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Rubber waste disposal is an environmental problem. Particularly, many researches are centered in the management of discarded tires. In spite of all different ways of handling used tires, the most common is to deposit them in a landfill, creating a stock of tires. These stocks can cause fire danger and provide ambient for rodents, mosquitoes and other pests, causing health hazards and environmental problems. Because of the three-dimensional structure of the rubbers and their specific composition that include several additives, their recycling is a current technological challenge. The technique which can break down the crosslink bonds in the rubber is called devulcanization. Strictly, devulcanization can be defined as a process where poly-, di-, and mono-sulfidic bonds, formed during vulcanization, are totally or partially broken. In the recent years, super critical carbon dioxide (scCO₂) was proposed as a green devulcanization atmosphere. This is because it is chemically inactive, nontoxic, nonflammable and inexpensive. Its critical point can be easily reached (31.1 °C and 7.38 MPa), and residual scCO₂ in the devulcanized rubber can be easily and rapidly removed by releasing pressure. In this study thermomechanical devulcanization of ground tire rubber (GTR) was performed in a twin screw extruder under diverse operation conditions. Supercritical CO₂ was added in different quantities to promote the devulcanization. Temperature, screw speed and quantity of CO₂ were the parameters that were varied during the process. The devulcanized rubber was characterized by its devulcanization percent and crosslink density by swelling in toluene. Infrared spectroscopy (FTIR) and Gel permeation chromatography (GPC) were also done, and the results were related with the Mooney viscosity. The results showed that the crosslink density decreases as the extruder temperature and speed increases, and, as expected, the soluble fraction increase with both parameters. The Mooney viscosity of the devulcanized rubber decreases as the extruder temperature increases. The reached values were in good correlation (R= 0.96) with de the soluble fraction. In order to analyze if the devulcanization was caused by main chains or crosslink scission, the Horikx's theory was used. Results showed that all tests fall in the curve that corresponds to the sulfur bond scission, which indicates that the devulcanization has successfully happened without degradation of the rubber. In the spectra obtained by FTIR, it was observed that none of the characteristic peaks of the GTR were modified by the different devulcanization conditions. This was expected, because due to the low sulfur content (~1.4 phr) and the multiphasic composition of the GTR, it is very difficult to evaluate the devulcanization by this technique. The lowest crosslink density was reached with 1 cm³/min of CO₂, and the power consumed in that process was also near to the minimum. These results encourage us to do further analyses to better understand the effect of the different conditions on the devulcanization process. The analysis is currently extended to monophasic rubbers as ethylene propylene diene monomer rubber (EPDM) and natural rubber (NR).

Keywords: devulcanization, recycling, rubber, waste

Procedia PDF Downloads 385
179 Petrology, Geochemistry and Formation Conditions of Metaophiolites of the Loki Crystalline Massif (the Caucasus)

Authors: Irakli Gamkrelidze, David Shengelia, Tamara Tsutsunava, Giorgi Chichinadze, Giorgi Beridze, Ketevan Tedliashvili, Tamara Tsamalashvili

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The Loki crystalline massif crops out in the Caucasian region and the geological retrospective represent the northern marginal part of the Baiburt-Sevanian terrain (island arc), bordering with the Paleotethys oceanic basin in the north. The pre-Alpine basement of the massif is built up of Lower-Middle Paleozoic metamorphic complex (metasedimentary and metabasite rocks), Upper Devonian quartz-diorites and Late Variscan granites. Earlier metamorphic complex was considered as an indivisible set including suites with different degree of metamorphism. Systematic geologic, petrologic and geochemical investigations of the massif’s rocks suggest the different conception on composition, structure and formation conditions of the massif. In particular, there are two main rock types in the Loki massif: the oldest autochthonous series of gneissic quartz-diorites and cutting them granites. The massif is flanked on its western side by a volcano-sedimentary sequence, metamorphosed to low-T facies. Petrologic, metamorphic and structural differences in this sequence prove the existence of a number of discrete units (overthrust sheets). One of them, the metabasic sheet represents the fragment of ophiolite complex. It comprises transition types of the second and third layers of the Paleooceanic crust: the upper noncumulated part of the third layer gabbro component and the following lowest part of the parallel diabase dykes of the second layer. The ophiolites are represented by metagabbros, metagabbro-diabases, metadiabases and amphibolite schists. According to the content of petrogenic components and additive elements in metabasites is stated that the protolith of metabasites belongs to petrochemical type of tholeiitic series of basalts. The parental magma of metaophiolites is of E-MORB composition, and by petrochemical parameters, it is very close to the composition of intraplate basalts. The dykes of hypabissal leucocratic siliceous and medium magmatic rocks associated with the metaophiolite sheet form the separate complex. They are granitoids with the extremely low content of CaO and quartz-diorite porphyries. According to various petrochemical parameters, these rocks have mixed characteristics. Their formation took place in spreading conditions or in the areas of manifestation of plumes most likely of island arc type. The metamorphism degree of the metaophiolites corresponds to a very low stage of green schist facies. The rocks of the metaophiolite complex are obducted from the Paleotethys Ocean. Geological and paleomagnetic data show that the primary location of the ocean is supposed to be to the north of the Loki crystalline massif.

Keywords: the Caucasus, crystalline massif, ophiolites, tectonic sheet

Procedia PDF Downloads 274
178 Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

Procedia PDF Downloads 100
177 Business Intelligent to a Decision Support Tool for Green Entrepreneurship: Meso and Macro Regions

Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

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The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

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176 Exploring Drivers and Barriers to Environmental Supply Chain Management in the Pharmaceutical Industry of Ghana

Authors: Gifty Kumadey, Albert Tchey Agbenyegah

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(i) Overview and research goal(s): This study aims to address research gaps in the Ghanaian pharmaceutical industry by examining the impact of environmental supply chain management (ESCM) practices on environmental and operational performance. Previous studies have provided inconclusive evidence on the relationship between ESCM practices and environmental and operational performance. The research aims to provide a clearer understanding of the impact of ESCM practices on environmental and operational performance in the context of the Ghanaian pharmaceutical industry. Limited research has been conducted on ESCM practices in developing countries, particularly in Africa. The study aims to bridge this gap by examining the drivers and barriers specific to the pharmaceutical industry in Ghana. The research aims to analyze the impact of ESCM practices on the achievement of Sustainable Development Goals (SDGs) in the Ghanaian pharmaceutical industry, focusing on SDGs 3, 12, 13, and 17. It also explores the potential for partnerships and collaborations to advance ESCM practices in the pharmaceutical industry. The research hypotheses suggest that pressure from stakeholder positively influences the adoption of ESCM practices in the Ghanaian pharmaceutical industry. By addressing these goals, the study aims to contribute to sustainable development initiatives and offer practical recommendations to enhance ESCM A practices in the industry. (ii) Research methods and data: This study uses a quantitative research design to examine the drivers and barriers to environmental supply chain management in the pharmaceutical industry in Accra.The sample size is approximately 150 employees, with senior and middle-level managers from pharmaceutical industry of Ghana. A purposive sampling technique is used to select participants with relevant knowledge and experience in environmental supply chain management. Data will be collected using a structured questionnaire using Likert scale responses. Descriptive statistics will be used to analyze the data and provide insights into current practices and their impact on environmental and operational performance. (iii) Preliminary results and conclusions: Main contributions: Identifying drivers/barriers to ESCM in Ghana's pharmaceutical industry, evaluating current ESCM practices, examining impact on performance, providing practical insights, contributing to knowledge on ESCM in Ghanaian context. The research contributes to SDGs 3, 9, and 12 by promoting sustainable practices and responsible consumption in the industry. The study found that government rules and regulations are the most critical drivers for ESCM adoption, with senior managers playing a significant role. However, employee and competitor pressures have a lesser impact. The industry has made progress in implementing certain ESCM practices, but there is room for improvement in areas like green distribution and reverse logistics. The study emphasizes the importance of government support, management engagement, and comprehensive implementation of ESCM practices in the industry. Future research should focus on overcoming barriers and challenges to effective ESCM implementation.

Keywords: environmental supply chain, sustainable development goal, ghana pharmaceutical industry, government regulations

Procedia PDF Downloads 94
175 Ammonia Bunkering Spill Scenarios: Modelling Plume’s Behaviour and Potential to Trigger Harmful Algal Blooms in the Singapore Straits

Authors: Bryan Low

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In the coming decades, the global maritime industry will face a most formidable environmental challenge -achieving net zero carbon emissions by 2050. To meet this target, the Maritime Port Authority of Singapore (MPA) has worked to establish green shipping and digital corridors with ports of several other countries around the world where ships will use low-carbon alternative fuels such as ammonia for power generation. While this paradigm shift to the bunkering of greener fuels is encouraging, fuels like ammonia will also introduce a new and unique type of environmental risk in the unlikely scenario of a spill. While numerous modelling studies have been conducted for oil spills and their associated environmental impact on coastal and marine ecosystems, ammonia spills are comparatively less well understood. For example, there is a knowledge gap regarding how the complex hydrodynamic conditions of the Singapore Straits may influence the dispersion of a hypothetical ammonia plume, which has different physical and chemical properties compared to an oil slick. Chemically, ammonia can be absorbed by phytoplankton, thus altering the balance of the marine nitrogen cycle. Biologically, ammonia generally serves the role of a nutrient in coastal ecosystems at lower concentrations. However, at higher concentrations, it has been found to be toxic to many local species. It may also have the potential to trigger eutrophication and harmful algal blooms (HABs) in coastal waters, depending on local hydrodynamic conditions. Thus, the key objective of this research paper is to support the development of a model-based forecasting system that can predict ammonia plume behaviour in coastal waters, given prevailing hydrodynamic conditions and their environmental impact. This will be essential as ammonia bunkering becomes more commonplace in Singapore’s ports and around the world. Specifically, this system must be able to assess the HAB-triggering potential of an ammonia plume, as well as its lethal and sub-lethal toxic effects on local species. This will allow the relevant authorities to better plan risk mitigation measures or choose a time window with the ideal hydrodynamic conditions to conduct ammonia bunkering operations with minimal risk. In this paper, we present the first part of such a forecasting system: a jointly coupled hydrodynamic-water quality model that can capture how advection-diffusion processes driven by ocean currents influence plume behaviour and how the plume interacts with the marine nitrogen cycle. The model is then applied to various ammonia spill scenarios where the results are discussed in the context of current ammonia toxicity guidelines, impact on local ecosystems, and mitigation measures for future bunkering operations conducted in the Singapore Straits.

Keywords: ammonia bunkering, forecasting, harmful algal blooms, hydrodynamics, marine nitrogen cycle, oceanography, water quality modeling

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174 Fabrication of Electrospun Green Fluorescent Protein Nano-Fibers for Biomedical Applications

Authors: Yakup Ulusu, Faruk Ozel, Numan Eczacioglu, Abdurrahman Ozen, Sabriye Acikgoz

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GFP discovered in the mid-1970s, has been used as a marker after replicated genetic study by scientists. In biotechnology, cell, molecular biology, the GFP gene is frequently used as a reporter of expression. In modified forms, it has been used to make biosensors. Many animals have been created that express GFP as an evidence that a gene can be expressed throughout a given organism. Proteins labeled with GFP identified locations are determined. And so, cell connections can be monitored, gene expression can be reported, protein-protein interactions can be observed and signals that create events can be detected. Additionally, monitoring GFP is noninvasive; it can be detected by under UV-light because of simply generating fluorescence. Moreover, GFP is a relatively small and inert molecule, that does not seem to treat any biological processes of interest. The synthesis of GFP has some steps like, to construct the plasmid system, transformation in E. coli, production and purification of protein. GFP carrying plasmid vector pBAD–GFPuv was digested using two different restriction endonuclease enzymes (NheI and Eco RI) and DNA fragment of GFP was gel purified before cloning. The GFP-encoding DNA fragment was ligated into pET28a plasmid using NheI and Eco RI restriction sites. The final plasmid was named pETGFP and DNA sequencing of this plasmid indicated that the hexa histidine-tagged GFP was correctly inserted. Histidine-tagged GFP was expressed in an Escherichia coli BL21 DE3 (pLysE) strain. The strain was transformed with pETGFP plasmid and grown on LuiraBertoni (LB) plates with kanamycin and chloramphenicol selection. E. coli cells were grown up to an optical density (OD 600) of 0.8 and induced by the addition of a final concentration of 1mM isopropyl-thiogalactopyranoside (IPTG) and then grown for additional 4 h. The amino-terminal hexa-histidine-tag facilitated purification of the GFP by using a His Bind affinity chromatography resin (Novagen). Purity of GFP protein was analyzed by a 12 % sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). The concentration of protein was determined by UV absorption at 280 nm (Varian Cary 50 Scan UV/VIS spectrophotometer). Synthesis of GFP-Polymer composite nanofibers was produced by using GFP solution (10mg/mL) and polymer precursor Polyvinylpyrrolidone, (PVP, Mw=1300000) as starting materials and template, respectively. For the fabrication of nanofibers with the different fiber diameter; a sol–gel solution comprising of 0.40, 0.60 and 0.80 g PVP (depending upon the desired fiber diameter) and 100 mg GFP in 10 mL water: ethanol (3:2) mixtures were prepared and then the solution was covered on collecting plate via electro spinning at 10 kV with a feed-rate of 0.25 mL h-1 using Spellman electro spinning system. Results show that GFP-based nano-fiber can be used plenty of biomedical applications such as bio-imaging, bio-mechanic, bio-material and tissue engineering.

Keywords: biomaterial, GFP, nano-fibers, protein expression

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173 Associated Problems with the Open Dump Site and Its Possible Solutions

Authors: Pangkaj Kumar Mahanta, Md. Rafizul Islam

Abstract:

The rapid growth of the population causes a substantial amount of increase in household waste all over the world. Waste management is becoming one of the most challenging phenomena in the present day. The most environmentally friendly final disposal process of waste is sanitary landfilling, which is practiced in most developing countries. However, in Southeast Asia, most of the final disposal point is an open dump site. Due to the ignominy of proper management of waste and monitoring, the surrounding environment gets polluted more by the open dump site in comparison with a sanitary landfill. Khulna is 3rd largest metropolitan city in Bangladesh, having a population of around 1.5 million and producing approximately 450 tons per day of Municipal Solid Waste. The Municipal solid waste of Khulna city is disposed of in Rajbandh open dump site. The surrounding air is being polluted by the gas produced in the open dump site. Also, the open dump site produces leachate, which contains various heavy metals like Cadmium (Cd), Chromium (Cr), Lead (Pb), Manganese (Mn), Mercury (Hg), Strontium (Sr), etc. Leachate pollutes the soil as well as the groundwater of the open dump site and also the surrounding area through seepage. Moreover, during the rainy season, the surface water is polluted by leachate runoff. Also, the plastic waste flowing out from the open dump site through various drivers pollutes the nearby environment. The health risk assessment associated with heavy metals was carried out by computing the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) via different exposure pathways following the USEPA guidelines. For ecological risk, potential contamination index (Cp), Contamination factor (CF), contamination load index (PLI), numerical integrated contamination factor (NICF), enrichment factor (EF), ecological risk index (ER), and potential ecological risk index (PERI) were computed. The health risk and ecological risk assessment results reveal that some heavy metals possess strong health and ecological risk. In addition, the child faces higher harmful health risks from several heavy metals than the adult for all the exposure pathways and media. The conversion of an open dump site into a sanitary landfill and a proper management system can reduce the problems associated with an open dump site. In the sanitary landfill, the produced gas will be managed properly to save the surrounding atmosphere from being polluted. The seepage of leachate can be minimized by installing a compacted clay layer (CCL) as a baseline and leachate collection in a sanitary landfill to save the underlying soil layer and surrounding water bodies from leachate. Another important component of a sanitary landfill is the conversion of plastic waste to energy will minimize the plastic pollution in the landfill area and also the surrounding soil and water bodies. Also, in the sanitary landfill, the bio-waste can be used to make compost to reduce the volume of bio-waste and proper utilization of the landfill area.

Keywords: ecological risk, health risk, open dump site, sanitary landfill

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172 Brazilian Brown Propolis as a Natural Source against Leishmania amazonensis

Authors: Victor Pena Ribeiro, Caroline Arruda, Jennyfer Andrea Aldana Mejia, Jairo Kenupp Bastos

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Leishmaniasis is a serious health problem around the world. The treatment of infected individuals with pentavalent antimonial drugs is the main therapeutic strategy. However, they present high toxicity and persistence side effects. Therefore, the discovery of new and safe natural-derived therapeutic agents against leishmaniasis is important. Propolis is a resin of viscous consistency produced by Apis mellifera bees from parts of plants. The main types of Brazilian propolis are green, red, yellow and brown. Thus, the aim of this work was to investigate the chemical composition and leishmanicidal properties of a brown propolis (BP). For this purpose, the hydroalcoholic crude extract of BP was obtained and was fractionated by liquid-liquid chromatography. The chemical profile of the extract and its fractions were obtained by HPLC-UV-DAD. The fractions were submitted to preparative HPLC chromatography for isolation of the major compounds of each fraction. They were analyzed by NMR for structural determination. The volatile compounds were obtained by hydrodistillation and identified by GC/MS. Promastigote forms of Leishmania amazonensis were cultivated in M199 medium and then 2×106 parasites.mL-1 were incubated in 96-well microtiter plates with the samples. The BP was dissolved in dimethyl sulfoxide (DMSO) and diluted into the medium, to give final concentrations of 1.56, 3.12, 6.25, 12.5, 25 and 50 µg.mL⁻¹. The plates were incubated at 25ºC for 24 h, and the lysis percentage was determined by using a Neubauer chamber. The bioassays were performed in triplicate, using a medium with 0.5% DMSO as a negative control and amphotericin B as a positive control. The leishimnicidal effect against promastigote forms was also evaluated at the same concentrations. Cytotoxicity experiments also were performed in 96-well plates against normal (CHO-k1) and tumor cell lines (AGP01 and HeLa) using XTT colorimetric method. Phenolic compounds, flavonoids, and terpenoids were identified in brown propolis. The major compounds were identified as follows: p-coumaric acid (24.6%) for a methanolic fraction, Artepelin-C (29.2%) for ethyl acetate fraction and the compounds of hexane fraction are in the process of structural elucidation. The major volatile compounds identified were β-caryophyllene (10.9%), germacrene D (9.7%), nerolidol (10.8%) and spathulenol (8.5%). The propolis did not show cytotoxicity against normal cell lines (CHO) with IC₅₀ > 100 μg.mL⁻¹, whereas the IC₅₀ < 10 μg.mL⁻¹ showed a potential against the AGP01 cell line, propolis did not demonstrate cytotoxicity against HeLa cell lines IC₅₀ > 100 μg.mL⁻¹. In the determination of the leishmanicidal activity, the highest (50 μg.mL⁻¹) and lowest (1.56 μg.mL⁻¹) concentrations of the crude extract caused the lysis of 76% and 45% of promastigote forms of L. amazonensis, respectively. To the amastigote form, the highest (50 μg.mL⁻¹) and lowest (1.56 μg.mL⁻¹) concentrations caused the mortality of 89% and 75% of L. amazonensis, respectively. The IC₅₀ was 2.8 μg.mL⁻¹ to amastigote form and 3.9 μg.mL⁻¹ to promastigote form, showing a promising activity against Leishmania amazonensis.

Keywords: amastigote, brown propolis, cytotoxicity, promastigote

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171 Artificial Neural Network and Satellite Derived Chlorophyll Indices for Estimation of Wheat Chlorophyll Content under Rainfed Condition

Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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170 Strategies for Conserving Ecosystem Functions of the Aravalli Range to Combat Land Degradation: Case of Kishangarh and Tijara Tehsil in Rajasthan, India

Authors: Saloni Khandelwal

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The Aravalli hills are one of the oldest and most distinctive mountain chains of peninsular India spanning in around 692 Km. More than 60% of it falls in the state of Rajasthan and influences ecological equilibrium in about 30% of the state. Because of natural and human-induced activities, physical gaps in the Aravallis are increasing, new gaps are coming up, and its physical structure is changing. There are no strict regulations to protect and monitor the Aravallis and no comprehensive research and study has been done for the enhancement of ecosystem functions of these ranges. Through this study, various factors leading to Aravalli’s degradation are identified and its impacts on selected areas are analyzed. A literature study is done to identify factors responsible for the degradation. To understand the severity of the problem at the lowest level, two tehsils from different districts in Rajasthan, which are the most affected due to illegal mining and increasing physical gaps are selected for the study. Case-1 of three-gram panchayats in Kishangarh Tehsil of Ajmer district focuses on the expanding physical gaps in the Aravalli range, and case-2 of three-gram panchayats in Tijara Tehsil of Alwar district focuses on increasing illegal mining in the Aravalli range. For measuring the degradation, physical, biological and social indicators are identified through literature review and for both the cases analysis is done on the basis of these indicators. Primary survey and focus group discussions are done with villagers, mining owners, illegal miners, and various government officials to understand dependency of people on the Aravalli and its importance to them along with the impact of degradation on their livelihood and environment. From the analysis, it has been found that green cover is continuously decreasing in both cases, dense forest areas do not exist now, the groundwater table is depleting at a very fast rate, soil is losing its moisture resulting in low yield and shift in agriculture. Wild animals which were easily seen earlier are now extinct. Cattles of villagers are dependent on the forest area in the Aravalli range for food, but with a decrease in fodder, their cattle numbers are decreasing. There is a decrease in agricultural land and an increase in scrub and salt-affected land. Analysis of various national and state programmes, acts which were passed to conserve biodiversity has been done showing that none of them is helping much to protect the Aravalli. For conserving the Aravalli and its forest areas, regional level and local level initiatives are required and are proposed in this study. This study is an attempt to formulate conservation and management strategies for the Aravalli range. These strategies will help in improving biodiversity which can lead to the revival of its ecosystem functions. It will also help in curbing the pollution at the regional and local level. All this will lead to the sustainable development of the region.

Keywords: Aravalli, ecosystem, LULC, Rajasthan

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