Search results for: hybrid genetic algorithms

Authors: John K. Avor, Choong-Koo Chang

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The transfer of electrical loads at power generation stations from Standby Auxiliary Transformer (SAT) to Unit Auxiliary Transformer (UAT) and vice versa is through a fast bus transfer scheme. Fast bus transfer is a time-critical application where the transfer process depends on various parameters, thus transfer schemes apply advance algorithms to ensure power supply reliability and continuity. In a nuclear power generation station, supply continuity is essential, especially for critical class 1E electrical loads. Bus transfers must, therefore, be executed accurately within 4 to 10 cycles in order to achieve safety system requirements. However, the main problem is that there are instances where transfer schemes scrambled due to inaccurate interpretation of key parameters; and consequently, have failed to transfer several critical loads from UAT to the SAT during main generator trip event. Although several techniques have been adopted to develop robust transfer schemes, a combination of Artificial Neural Network and Fuzzy Systems (Neuro-Fuzzy) has not been extensively used. In this paper, we apply the concept of Neuro-Fuzzy to determine plant operating mode and dynamic prediction of the appropriate bus transfer algorithm to be selected based on the first cycle of voltage information. The performance of Sequential Fast Transfer and Residual Bus Transfer schemes was evaluated through simulation and integration of the Neuro-Fuzzy system. The objective for adopting Neuro-Fuzzy approach in the bus transfer scheme is to utilize the signal validation capabilities of artificial neural network, specifically the back-propagation algorithm which is very accurate in learning completely new systems. This research presents a combined effect of artificial neural network and fuzzy systems to accurately interpret key bus transfer parameters such as magnitude of the residual voltage, decay time, and the associated phase angle of the residual voltage in order to determine the possibility of high speed bus transfer for a particular bus and the corresponding transfer algorithm. This demonstrates potential for general applicability to improve reliability of the auxiliary power distribution system. The performance of the scheme is implemented on APR1400 nuclear power plant auxiliary system.

Keywords: auxiliary power system, bus transfer scheme, fuzzy logic, neural networks, reliability

Procedia PDF Downloads 152

Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

Procedia PDF Downloads 116

Authors: Paolino Di Felice

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The background and significance of this study come from papers already appeared in the literature which measured the impact of public services (e.g., hospitals, schools, ...) on the citizens’ needs satisfaction (one of the dimensions of QOL studies) by calculating the distance between the place where they live and the location on the territory of the services. Those studies assume that the citizens' dwelling coincides with the centroid of the polygon that expresses the boundary of the administrative district, within the city, they belong to. Such an assumption “introduces a maximum measurement error equal to the greatest distance between the centroid and the border of the administrative district.”. The case study, this abstract reports about, investigates the implications descending from the adoption of such an approach but at geographical scales greater than the urban one, namely at the three levels of nesting of the Italian administrative units: the (20) regions, the (110) provinces, and the 8,094 municipalities. To carry out this study, it needs to be decided: a) how to store the huge amount of (spatial and descriptive) input data and b) how to process them. The latter aspect involves: b.1) the design of algorithms to investigate the geometry of the boundary of the Italian administrative units; b.2) their coding in a programming language; b.3) their execution and, eventually, b.4) archiving the results in a permanent support. The IT solution we implemented is centered around a (PostgreSQL/PostGIS) Geo DataBase structured in terms of three tables that fit well to the hierarchy of nesting of the Italian administrative units: municipality(id, name, provinceId, istatCode, regionId, geometry) province(id, name, regionId, geometry) region(id, name, geometry). The adoption of the DBMS technology allows us to implement the steps "a)" and "b)" easily. In particular, step "b)" is simplified dramatically by calling spatial operators and spatial built-in User Defined Functions within SQL queries against the Geo DB. The major findings coming from our experiments can be summarized as follows. The approximation that, on the average, descends from assimilating the residence of the citizens with the centroid of the administrative unit of reference is of few kilometers (4.9) at the municipalities level, while it becomes conspicuous at the other two levels (28.9 and 36.1, respectively). Therefore, studies such as those mentioned above can be extended up to the municipal level without affecting the correctness of the interpretation of the results, but not further. The IT framework implemented to carry out the experiments can be replicated for studies referring to the territory of other countries all over the world.

Keywords: quality of life, distance measurement error, Italian administrative units, spatial database

Procedia PDF Downloads 350

Authors: W. Kritsarikan, T. Patcharawit, T. Yingnakorn, S. Khumkoa

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Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as electrical and medical devices and account for 13.5 % of the permanent magnet’s market. Since its typical composition of 29 - 32 % Nd, 64.2 – 68.5 % Fe and 1 – 1.2 % B contains a significant amount of rare earth metals and will be subjected to shortages in the future. Domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social, environmental impacts toward a circular economy. Most research works focus on recycling the magnet wastes, both from the manufacturing process and end of life. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as the types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd₂O₃) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550 - 800 °C to enable selective leaching of neodymium in the subsequent leaching step using H₂SO₄ at 2.5 M over 24 h. The leachate was then subjected to drying and roasting at 700 – 800 °C prior to precipitation by oxalic acid and calcination to obtain neodymium oxide as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to an increasing amount of hematite (Fe₂O₃) as the main composition with a smaller amount of magnetite (Fe₃O₄) found. Peaks of neodymium oxide (Nd₂O₃) were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO₃) was present and its XRD peaks were pronounced at higher oxidative roasting temperatures. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form hematite as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of magnetite was still detected by XRD. The higher roasting temperature at 800 °C resulted in a greater Fe₂O₃ to Nd₂(SO₄)₃ ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 °C followed by acid leaching and roasting at 800 °C gave the optimum condition for further steps of precipitation and calcination to finally achieve neodymium oxide.

Keywords: NdFeB magnet waste, oxidative roasting, recycling, selective leaching

Procedia PDF Downloads 169

Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

Procedia PDF Downloads 51

Authors: Sulalit Bandyopadhyay, Muhammad Awais Ashfaq Alvi, Anuvansh Sharma, Wilhelm R. Glomm

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Release of drugs from nanogels and nanogel-based systems can occur under the influence of external stimuli like temperature, pH, magnetic fields and so on. pNIPAm-AAc nanogels respond to the combined action of both temperature and pH, the former being mostly determined by hydrophilic-to-hydrophobic transitions above the volume phase transition temperature (VPTT), while the latter is controlled by the degree of protonation of the carboxylic acid groups. These nanogels based systems are promising candidates in the field of drug delivery. Combining nanogels with magneto-plasmonic nanoparticles (NPs) introduce imaging and targeting modalities along with stimuli-response in one hybrid system, thereby incorporating multifunctionality. Fe@Au core-shell NPs possess optical signature in the visible spectrum owing to localized surface plasmon resonance (LSPR) of the Au shell, and superparamagnetic properties stemming from the Fe core. Although there exist several synthesis methods to control the size and physico-chemical properties of pNIPAm-AAc nanogels, yet, there is no comprehensive study that highlights the dependence of incorporation of one or more layers of NPs to these nanogels. In addition, effective determination of volume phase transition temperature (VPTT) of the nanogels is a challenge which complicates their uses in biological applications. Here, we have modified the swelling-collapse properties of pNIPAm-AAc nanogels, by combining with Fe@Au NPs using different solution based methods. The hydrophilic-hydrophobic transition of the nanogels above the VPTT has been confirmed to be reversible. Further, an analytical method has been developed to deduce the average VPTT which is found to be 37.3°C for the nanogels and 39.3°C for nanogel coated Fe@Au NPs. An opposite swelling –collapse behaviour is observed for the latter where the Fe@Au NPs act as bridge molecules pulling together the gelling units. Thereafter, Cyt C, a model protein drug and L-Dopa, a drug used in the clinical treatment of Parkinson’s disease were loaded separately into the nanogels and nanogel coated Fe@Au NPs, using a modified breathing-in mechanism. This gave high loading and encapsulation efficiencies (L Dopa: ~9% and 70µg/mg of nanogels, Cyt C: ~30% and 10µg/mg of nanogels respectively for both the drugs. The release kinetics of L-Dopa, monitored using UV-vis spectrophotometry was observed to be rather slow (over several hours) with highest release happening under a combination of high temperature (above VPTT) and acidic conditions. However, the release of L-Dopa from nanogel coated Fe@Au NPs was the fastest, accounting for release of almost 87% of the initially loaded drug in ~30 hours. The chemical structure of the drug, drug incorporation method, location of the drug and presence of Fe@Au NPs largely alter the drug release mechanism and the kinetics of these nanogels and Fe@Au NPs coated with nanogels.

Keywords: controlled release, nanogels, volume phase transition temperature, l-dopa

Procedia PDF Downloads 309

Authors: Kristina Amaleviciute, Ieva Jokubauskaite, Alvyra Slepetiene, Jonas Volungevicius, Inga Liaudanskiene

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The main task of this research was to investigate the chemical composition of the differently used soil in profiles. To identify the differences in the soil were investigated organic carbon (SOC) and its fractional composition: dissolved organic carbon (DOC), mobile humic acids (MHA) and C to N ratio of natural and anthropogenically affected Luvisols. Research object: natural and anthropogenically affected Luvisol, Akademija, Kedainiai, distr. Lithuania. Chemical analyses were carried out at the Chemical Research Laboratory of Institute of Agriculture, LAMMC. Soil samples for chemical analyses were taken from the genetics soil horizons. SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) in 590 nm wavelength using glucose standards. For mobile humic acids (MHA) determination the extraction procedure was carried out using 0.1 M NaOH solution. Dissolved organic carbon (DOC) was analyzed using an ion chromatograph SKALAR. pH was measured in 1M H2O. N total was determined by Kjeldahl method. Results: Based on the obtained results, it can be stated that transformation of chemical composition is going through the genetic soil horizons. Morphology of the upper layers of soil profile which is formed under natural conditions was changed by anthropomorphic (agrogenic, urbogenic, technogenic and others) structure. Anthropogenic activities, mechanical and biochemical disturbances destroy the natural characteristics of soil formation and complicates the interpretation of soil development. Due to the intensive cultivation, the pH values of the curve equals (disappears acidification characteristic for E horizon) with natural Luvisol. Luvisols affected by agricultural activities was characterized by a decrease in the absolute amount of humic substances in separate horizons. But there was observed more sustainable, higher carbon sequestration and thicker storage of humic horizon compared with forest Luvisol. However, the average content of humic substances in the soil profile was lower. Soil organic carbon content in anthropogenic Luvisols was lower compared with the natural forest soil, but there was more evenly spread over in the wider thickness of accumulative horizon. These data suggest that the organization of geo-ecological declines and agroecological increases in Luvisols. Acknowledgement: This work was supported by the National Science Program ‘The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems’ [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: agrogenization, dissolved organic carbon, luvisol, mobile humic acids, soil organic carbon

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Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: Woranittha Kritsarikan

Abstract:

Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as electrical and medical devices and account for 13.5 % of the permanent magnet’s market. Since its typical composition of 29 - 32 % Nd, 64.2 – 68.5 % Fe and 1 – 1.2 % B contains a significant amount of rare earth metals and will be subjected to shortages in the future. Domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social, environmental impacts toward the circular economy. Most research works focus on recycling the magnet wastes, both from the manufacturing process and end of life. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as the types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd₂O₃) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550 - 800 ᵒC to enable selective leaching of neodymium in the subsequent leaching step using H₂SO₄ at 2.5 M over 24 hours. The leachate was then subjected to drying and roasting at 700 – 800 ᵒC prior to precipitation by oxalic acid and calcination to obtain neodymium oxide as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to the increasing amount of hematite (Fe₂O₃) as the main composition with a smaller amount of magnetite (Fe3O4) found. Peaks of neodymium oxide (Nd₂O₃) were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO₃) was present and its XRD peaks were pronounced at higher oxidative roasting temperature. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form hematite as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of magnetite was still detected by XRD. The higher roasting temperature at 800 ᵒC resulted in a greater Fe2O3 to Nd2(SO4)3 ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 ᵒC followed by acid leaching and roasting at 800 ᵒC gave the optimum condition for further steps of precipitation and calcination to finally achieve neodymium oxide.

Keywords: NdFeB magnet waste, oxidative roasting, recycling, selective leaching

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Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

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Authors: Mahnaz Khalafehnilsaz, Rozina Rahnama

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

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

Procedia PDF Downloads 43

Authors: Igor Pejic

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The main focus of this research will be on analyzing correlative links between terrorism as an asymmetrical threat and the consequences it leaves on conventional security forces. The methodology behind the research will include qualitative research methods focusing on comparative analysis of books, scientific papers, documents and other sources, in order to deduce, explore and formulate the results of the research. With the coming of the 21^st century and the rising multi-polar, new world threats quickly emerged. The realistic approach in international relations deems that relations among nations are in a constant state of anarchy since there are no definitive rules and the distribution of power varies widely. International relations are further characterized by egoistic and self-orientated human nature, anarchy or absence of a higher government, security and lack of morality. The asymmetry of power is also reflected on countries' security capabilities and its abilities to project power. With the coming of the new millennia and the rising multi-polar world order, the asymmetry of power can be also added as an important trait of the global society which consequently brought new threats. Among various others, terrorism is probably the most well-known, well-based and well-spread asymmetric threat. In today's global political arena, terrorism is used by state and non-state actors to fulfill their political agendas. Terrorism is used as an all-inclusive tool for regime change, subversion or a revolution. Although the nature of terrorist groups is somewhat inconsistent, terrorism as a security and social phenomenon has a one constant which is reflected in its political dimension. The state's security apparatus, which was embodied in the form of conventional armed forces, is now becoming fragile, unable to tackle new threats and to a certain extent outdated. Conventional security forces were designed to defend or engage an exterior threat which is more or less symmetric and visible. On the other hand, terrorism as an asymmetrical threat is a part of hybrid, special or asymmetric warfare in which specialized units, institutions or facilities represent the primary pillars of security. In today's global society, terrorism is probably the most acute problem which can paralyze entire countries and their political systems. This problem, however, cannot be engaged on an open field of battle, but rather it requires a different approach in which conventional armed forces cannot be used traditionally and their role must be adjusted. The research will try to shed light on the phenomena of modern day terrorism and to prove its correlation with the state conventional armed forces. States are obliged to adjust their security apparatus to the new realism of global society and terrorism as an asymmetrical threat which is a side-product of the unbalanced world.

Keywords: asymmetrical warfare, conventional forces, security, terrorism

Procedia PDF Downloads 238

Authors: Nasim Hashemi, Abbas Sheikhtaheri

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Telemedicine is the use of telecommunication and information technologies to provide health care services that would often not be consistently available in distant rural communities to people at these remote areas. Teleophthalmology is a branch of telemedicine that delivers eye care through digital medical equipment and telecommunications technology. Thus, teleophthalmology can overcome geographical barriers and improve quality, access, and affordability of eye health care services. Since teleophthalmology has been widespread applied in recent years, the aim of this study was to determine the different applications of teleophthalmology in the world. To this end, three bibliographic databases (Medline, ScienceDirect, Scopus) were comprehensively searched with these keywords: eye care, eye health care, primary eye care, diagnosis, detection, and screening of different eye diseases in conjunction with telemedicine, telehealth, teleophthalmology, e-services, and information technology. All types of papers were included in the study with no time restriction. We conducted the search strategies until 2015. Finally 70 articles were surveyed. We classified the results based on the’type of eye problems covered’ and ‘the type of telemedicine services’. Based on the review, from the ‘perspective of health care levels’, there are three level for eye health care as primary, secondary and tertiary eye care. From the ‘perspective of eye care services’, the main application of teleophthalmology in primary eye care was related to the diagnosis of different eye diseases such as diabetic retinopathy, macular edema, strabismus and aged related macular degeneration. The main application of teleophthalmology in secondary and tertiary eye care was related to the screening of eye problems i.e. diabetic retinopathy, astigmatism, glaucoma screening. Teleconsultation between health care providers and ophthalmologists and also education and training sessions for patients were other types of teleophthalmology in world. Real time, store–forward and hybrid methods were the main forms of the communication from the perspective of ‘teleophthalmology mode’ which is used based on IT infrastructure between sending and receiving centers. In aspect of specialists, early detection of serious aged-related ophthalmic disease in population, screening of eye disease processes, consultation in an emergency cases and comprehensive eye examination were the most important benefits of teleophthalmology. Cost-effectiveness of teleophthalmology projects resulted from reducing transportation and accommodation cost, access to affordable eye care services and receiving specialist opinions were also the main advantages of teleophthalmology for patients. Teleophthalmology brings valuable secondary and tertiary care to remote areas. So, applying teleophthalmology for detection, treatment and screening purposes and expanding its use in new applications such as eye surgery will be a key tool to promote public health and integrating eye care to primary health care.

Keywords: applications, telehealth, telemedicine, teleophthalmology

Procedia PDF Downloads 350

Authors: Karolina Rutkowska, Hubert Pausch, Jolanta Oprzadek, Krzysztof Flisikowski

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The placenta is one of the most important organs that plays a crucial role in the fetal growth and development. Placenta dysfunction is one of the primary cause of the intrauterine growth restriction (IUGR). Cattle have the cotyledonary placenta which consists of two anatomical parts: fetal and maternal. In the case of cattle during the first months of pregnancy, it is very easy to separate maternal caruncle from fetal cotyledon tissue, easier in fact than removing an ordinary glove from one's hand. Which in fact make easier to conduct tissue-specific molecular studies. Typically, animal models for the study of IUGR are created using surgical methods and malnutrition of the pregnant mother or in the case of mice by genetic modifications. However, proposed cattle model with MIMT1Del/WT deletion is unique because it was created without any surgical methods what significantly distinguish it from the other animal models. The primary objective of the study was to identify differential expression of selected miRNAs in the placenta from normal and intrauterine growth restricted fetuses. There was examined the expression of miRNA in the fetal and maternal part of the placenta from 24 fetuses (12 samples from the fetal part of the placenta and 12 samples from maternal part of the placenta). In the study, there was done miRNAs sequencing in the placenta of MIMT1Del/WT fetuses and MIMT1WT/WT fetuses. Then, there were selected miRNAs that are involved in fetal growth and development. Analysis of miRNAs expression was conducted on ABI7500 machine. miRNAs expression was analyzed by reverse-transcription polymerase chain reaction (RT-PCR). As the reference gene was used SNORD47. The results were expressed as 2ΔΔCt: ΔΔCt = (Ctij − CtSNORD47j) − (Cti1 − CtSNORD471). Where Ctij and CtSNORD47j are the Ct values for gene i and for SNORD47 in a sample (named j); Cti1 and CtSNORD471 are the Ct values in sample 1. Differences between groups were evaluated with analysis of variance by using One-Way ANOVA. Bonferroni’s tests were used for interpretation of the data. All normalised miRNA expression values are expressed on a value of natural logarithm. The data were expressed as least squares mean with standard errors. Significance was declared when P < 0.05. The study shows that miRNAs expression depends on the part of the placenta where they origin (fetal or maternal) and on the genotype of the animal. miRNAs offer a particularly new approach to study IUGR. Corresponding tissue samples were collected according to the standard veterinary protocols according to the European Union Normative for Care and Use of Experimental Animals. All animal experiments were approved by the Animal Ethics Committee of the State Provincial Office of Southern Finland (ESAVI-2010-08583/YM-23).

Keywords: placenta, intrauterine growth restriction, miRNA, cattle

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Authors: Lorenzo Petrucci

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This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

Procedia PDF Downloads 157

Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

Procedia PDF Downloads 54

Authors: Abdoulie K. Ceesay

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Within the sequence of the whole genome, it is known that 99.9% of the human genome is similar, whilst our difference lies in just 0.1%. Among these minor dissimilarities, the most common type of genetic variations that occurs in a population is SNP, which arises due to nucleotide substitution in a protein sequence that leads to protein destabilization, alteration in dynamics, and other physio-chemical properties’ distortions. While causing variations, they are equally responsible for our difference in the way we respond to a treatment or a disease, including various cancer types. There are two types of SNPs; synonymous single nucleotide polymorphism (sSNP) and non-synonymous single nucleotide polymorphism (nsSNP). sSNP occur in the gene coding region without causing a change in the encoded amino acid, while nsSNP is deleterious due to its replacement of a nucleotide residue in the gene sequence that results in a change in the encoded amino acid. Predicting the effects of cancer related nsSNPs on protein stability, function, and dynamics is important due to the significance of phenotype-genotype association of cancer. In this thesis, Data of 5 oncogenes (ONGs) (AKT1, ALK, ERBB2, KRAS, BRAF) and 5 tumor suppressor genes (TSGs) (ESR1, CASP8, TET2, PALB2, PTEN) were retrieved from ClinVar. Five common in silico tools; Polyphen, Provean, Mutation Assessor, Suspect, and FATHMM, were used to predict and categorize nsSNPs as deleterious, benign, or neutral. To understand the impact of each variation on the phenotype, Maestro, PremPS, Cupsat, and mCSM-NA in silico structural prediction tools were used. This study comprises of in-depth analysis of 10 cancer gene variants downloaded from Clinvar. Various analysis of the genes was conducted to derive a meaningful conclusion from the data. Research done indicated that pathogenic variants are more common among ONGs. Our research also shows that pathogenic and destabilizing variants are more common among ONGs than TSGs. Moreover, our data indicated that ALK(409) and BRAF(86) has higher benign count among ONGs; whilst among TSGs, PALB2(1308) and PTEN(318) genes have higher benign counts. Looking at the individual cancer genes predisposition or frequencies of causing cancer according to our research data, KRAS(76%), BRAF(55%), and ERBB2(36%) among ONGs; and PTEN(29%) and ESR1(17%) among TSGs have higher tendencies of causing cancer. Obtained results can shed light to the future research in order to pave new frontiers in cancer therapies.

Keywords: tumor suppressor genes (TSGs), oncogenes (ONGs), non synonymous single nucleotide polymorphism (nsSNP), single nucleotide polymorphism (SNP)

Procedia PDF Downloads 66

Authors: Sidramappa Gaddnakeri, Lokanath Malligawad

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Any kind of research on production technology of individual crop / commodity /breed has not brought sustainability or stability in crop production. The sustainability of the system over years depends on the maintenance of the soil health. Organic production system includes use of organic manures, biofertilizers, green manuring for nutrient supply and biopesticides for plant protection helps to sustain the productivity even under adverse climatic condition. The study was initiated to evaluate the performance of different cropping systems under organic, inorganic and integrated production systems at The Institute of Organic Farming, University of Agricultural Sciences, Dharwad (Karnataka-India) under ICAR Network Project on Organic Farming. The trial was conducted for four years (2013-14 to 2016-17) on fixed site. Five cropping systems viz., sequence cropping of cowpea – safflower, greengram– rabi sorghum, maize-bengalgram, sole cropping of pigeonpea and intercropping of groundnut + cotton were evaluated under six nutrient management practices. The nutrient management practices are NM1 (100% Organic farming (Organic manures equivalent to 100% N (Cereals/cotton) or 100% P2O5 (Legumes), NM2 (75% Organic farming (Organic manures equivalent to 75% N (Cereals/cotton) or 100% P2O5 (Legumes) + Cow urine and Vermi-wash application), NM3 (Integrated farming (50% Organic + 50% Inorganic nutrients, NM4 (Integrated farming (75% Organic + 25% Inorganic nutrients, NM5 (100% Inorganic farming (Recommended dose of inorganic fertilizers)) and NM6 (Recommended dose of inorganic fertilizers + Recommended rate of farm yard manure (FYM). Among the cropping systems evaluated for different production systems indicated that the Groundnut + Hybrid cotton (2:1) intercropping system found more remunerative as compared to Sole pigeonpea cropping system, Greengram-Sorghum sequence cropping system, Maize-Chickpea sequence cropping system and Cowpea-Safflower sequence cropping system irrespective of the production systems. Production practices involving application of recommended rates of fertilizers + recommended rates of organic manures (Farmyard manure) produced higher net monetary returns and higher B:C ratio as compared to integrated production system involving application of 50 % organics + 50 % inorganic and application of 75 % organics + 25 % inorganic and organic production system only Both the two organic production systems viz., 100 % Organic production system (Organic manures equivalent to 100 % N (Cereals/cotton) or 100 % P2O5 (Legumes) and 75 % Organic production system (Organic manures equivalent to 75 % N (Cereals) or 100 % P2O5 (Legumes) + Cow urine and Vermi-wash application) are found to be on par. Further, integrated production system involving application of organic manures and inorganic fertilizers found more beneficial over organic production systems.

Keywords: cropping systems, production systems, cowpea, safflower, greengram, pigeonpea, groundnut, cotton

Procedia PDF Downloads 171

Authors: Anand K. Vinu, Vaishnav Vimal, Sasi Gopalan

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All spacecraft components have a range of allowable temperatures that must be maintained to meet survival and operational requirements during all mission phases. Due to heat absorption, transfer, and emission on one side, the satellite surface presents an asymmetric temperature distribution and causes a change in momentum, which can manifest in spinning and non-spinning satellites in different manners. This problem can cause orbital decays in satellites which, if not corrected, will interfere with its primary objective. The thermal analysis of any satellite requires data from the power budget for each of the components used. This is because each of the components has different power requirements, and they are used at specific times in an orbit. There are three different cases that are run, one is the worst operational hot case, the other one is the worst non-operational cold case, and finally, the operational cold case. Sunlight is a major source of heating that takes place on the satellite. The way in which it affects the spacecraft depends on the distance from the Sun. Any part of a spacecraft or satellite facing the Sun will absorb heat (a net gain), and any facing away will radiate heat (a net loss). We can use the state-of-the-art foldable hybrid insulator/radiator panel. When the panels are opened, that particular side acts as a radiator for dissipating the heat. Here the insulator, in our case, the aerogel, is sandwiched with solar cells and radiator fins (solar cells outside and radiator fins inside). Each insulated side panel can be opened and closed using actuators depending on the telemetry data of the CubeSat. The opening and closing of the panels are dependent on the special code designed for this particular application, where the computer calculates where the Sun is relative to the satellites. According to the data obtained from the sensors, the computer decides which panel to open and by how many degrees. For example, if the panels open 180 degrees, the solar panels will directly face the Sun, in turn increasing the current generator of that particular panel. One example is when one of the corners of the CubeSat is facing or if more than one side is having a considerable amount of sun rays incident on it. Then the code will analyze the optimum opening angle for each panel and adjust accordingly. Another means of cooling is the passive way of cooling. It is the most suitable system for a CubeSat because of its limited power budget constraints, low mass requirements, and less complex design. Other than this fact, it also has other advantages in terms of reliability and cost. One of the passive means is to make the whole chase act as a heat sink. For this, we can make the entire chase out of heat pipes and connect the heat source to this chase with a thermal strap that transfers the heat to the chassis.

Keywords: passive cooling, CubeSat, efficiency, satellite, stationary satellite

Procedia PDF Downloads 77

Authors: Maciej Zasuwa, Grzegorz Ptasinski, Antoni Kopyt

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Nowadays flight simulators offer tremendous possibilities for safe and cost-effective pilot training, by utilization of powerful, computational tools. Due to technology outpacing methodology, vast majority of training related work is done by human instructors. It makes assessment not efficient, and vulnerable to instructors’ subjectivity. The research presents an Objective Assessment Tool (gOAT) developed at the Warsaw University of Technology, and tested on SW-4 helicopter flight simulator. The tool uses database of the predefined manoeuvres, defined and integrated to the virtual environment. These were implemented, basing on Aeronautical Design Standard Performance Specification Handling Qualities Requirements for Military Rotorcraft (ADS-33), with predefined Mission-Task-Elements (MTEs). The core element of the gOAT enhanced algorithm that provides instructor a new set of information. In details, a set of objective flight parameters fused with report about psychophysical state of the pilot. While the pilot performs the task, the gOAT system automatically calculates performance using the embedded algorithms, data registered by the simulator software (position, orientation, velocity, etc.), as well as measurements of physiological changes of pilot’s psychophysiological state (temperature, sweating, heart rate). Complete set of measurements is presented on-line to instructor’s station and shown in dedicated graphical interface. The presented tool is based on open source solutions, and flexible for editing. Additional manoeuvres can be easily added using guide developed by authors, and MTEs can be changed by instructor even during an exercise. Algorithm and measurements used allow not only to implement basic stress level measurements, but also to reduce instructor’s workload significantly. Tool developed can be used for training purpose, as well as periodical checks of the aircrew. Flexibility and ease of modifications allow the further development to be wide ranged, and the tool to be customized. Depending on simulation purpose, gOAT can be adjusted to support simulator of aircraft, helicopter, or unmanned aerial vehicle (UAV).

Keywords: automated assessment, flight simulator, human factors, pilot training

Procedia PDF Downloads 128

Authors: Amal G. Kurian

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The use of mathematical modeling has seen a considerable boost in recent times with the development of many advanced algorithms and mathematical modeling capabilities. The advantages this method has over other methods are that they are much closer to standard physics theories and thus represent a better theoretical model. They take lesser solving time and have the ability to change various parameters for optimization, which is a big advantage, especially in automotive industry. This thesis work focuses on a thorough investigation of the effects of vehicle speed and road roughness on a heavy commercial vehicle ride and structural dynamic responses. Since commercial vehicles are kept in operation continuously for longer periods of time, it is important to study effects of various physical conditions on the vehicle and its user. For this purpose, various experimental as well as simulation methodologies, are adopted ranging from experimental transfer path analysis to various road scenario simulations. To effectively investigate and eliminate several causes of unwanted responses, an efficient and robust technique is needed. Carrying forward this motivation, the present work focuses on the development of a mathematical model of a 4-axle configuration heavy commercial vehicle (HCV) capable of calculating responses of the vehicle on different road PSD inputs and vehicle speeds. Outputs from the model will include response transfer functions and PSDs and wheel forces experienced. A MATLAB code will be developed to implement the objectives in a robust and flexible manner which can be exploited further in a study of responses due to various suspension parameters, loading conditions as well as vehicle dimensions. The thesis work resulted in quantifying the effect of various physical conditions on ride comfort of the vehicle. An increase in discomfort is seen with velocity increase; also the effect of road profiles has a considerable effect on comfort of the driver. Details of dominant modes at each frequency are analysed and mentioned in work. The reduction in ride height or deflection of tire and suspension with loading along with load on each axle is analysed and it is seen that the front axle supports a greater portion of vehicle weight while more of payload weight comes on fourth and third axles. The deflection of the vehicle is seen to be well inside acceptable limits.

Keywords: mathematical modeling, HCV, suspension, ride analysis

Procedia PDF Downloads 234

Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

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With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

Procedia PDF Downloads 95

Authors: Ayla Roberta Galaco, Juliana Fonseca De Lima, Osvaldo Antonio Serra

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Coordination polymers, also known as metal-organic frameworks (MOFs) or lanthanoide organic frameworks (LOFs) have been reported due of their promising applications in gas storage, separation, catalysis, luminescence, magnetism, drug delivery, and so on. As a type of organic–inorganic hybrid materials, the properties of coordination polymers could be chosen by deliberately selecting the organic and inorganic components. LOFs have received considerable attention because of their properties such as porosity, luminescence, and magnetism. Methods such as solvothermal synthesis are important as a strategy to control the structural and morphological properties as well as the composition of the target compounds. In this work the first solvothermal synthesis was employed to obtain the compound [Y0.4,Yb0.4,Er0.2(dmf)(for)(H2O)(tft)], by using terephthalic acid (tft) and oxalic acid, decomposed in formate (for), as ligands; Yttrium, Ytterbium and, Erbium as metal centers, in DMF and water for 4 days under 160 °C. The semi-rigid terephthalic acid (dicarboxylic) coordinates with Ln3+ ions and also is possible to form a polyfunctional bridge. On the other hand, oxalate anion has no high-energy vibrational groups, which benefits the excitation of Yb3+ in upconversion process. It was observed that the compounds with water molecules in the coordination sphere of the lanthanoide ions cause lower crystalline properties and change the structure of the LOF (1D, 2D, 3D). In the FTIR, the bands at 1589 and 1500 cm-1 correspond to the asymmetric stretching vibration of –COO. The band at 1383 cm-1 is assigned to the symmetric stretching vibration of –COO. Single crystal X-ray diffraction study reveals an infinite 3D coordination framework that crystalizes in space group P21/c. The other three products, [TR(chel)(ofd)0,5(H2O)2], where TR= Eu3+, Y3, and Yb3+/Er3+ were obtained by using 1, 2-phenylenedioxydiacetic acid (ofd) and chelidonic acid (chel) as organic ligands. Thermal analysis shows that the lanthanoide organic frameworks do not collapse at temperatures below 250 °C. By the polycrystalline X-ray diffraction patterns (PXRD) it was observed that the compounds with Eu3+, Y3+, and Yb3+/Er3+ ions are isostructural. From PXRD patterns, high crystallinity can be noticed for the complexes. The final products were characterized by single X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), energy dispersive spectroscopy (EDS) and thermogravimetric analysis (TGA). The X-ray diffraction (XRD) is an effective method to investigate crystalline properties of synthesized materials. The solid crystal obtained in the synthesis show peaks at 2θ < 10°, indicating the MOF formation. The chemical composition of LOFs was also confirmed by EDS.

Keywords: isostructural, lanthanoids, lanthanoids organic frameworks (LOFs), metal organic frameworks (MOFs), thermogravimetry, X-Ray diffraction

Procedia PDF Downloads 233

Authors: Sharmeen Rahman, Daniel Schmidt, Jane Hughes

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Paratya australiensis Kemp (Decapoda: Atyidae) is a widely distributed indigenous freshwater shrimp, highly abundant in eastern Australia. This species has been considered as a model stream organism to study genetics, dispersal, biology, behaviour and evolution in Atyids. Paratya has a filter feeding and scavenging habit which plays a significant role in the formation of lotic community structure. It has been shown to reduce periphyton and sediment from hard substrates of coastal streams and hence acts as a strongly-interacting ecosystem macroconsumer. Besides, Paratya is one of the major food sources for stream dwelling fishes. Paratya australiensis is a cryptic species complex consisting of 9 highly divergent mitochondrial DNA lineages. Among them, one lineage has been observed to favour upstream sites at higher altitudes, with cooler water temperatures. This study aims to identify local adaptation in upstream and downstream populations of this lineage in three streams in the Conondale Range, North-eastern Brisbane, Queensland, Australia. Two populations (up and down stream) from each stream have been chosen to test for local adaptation, and a parallel pattern of adaptation is expected across all streams. Six populations each consisting of 24 individuals were sequenced using the Restriction Site Associated DNA-seq (RAD-seq) technique. Genetic markers (SNPs) were developed using double digest RAD sequencing (ddRAD-seq). These were used for de novo assembly of Paratya genome. De novo assembly was done using the STACKs program and produced 56, 344 loci for 47 individuals from one stream. Among these individuals, 39 individuals shared 5819 loci, and these markers are being used to test for local adaptation using Fst outlier tests (Arlequin) and Bayesian analysis (BayeScan) between up and downstream populations. Fst outlier test detected 27 loci likely to be under selection and the Bayesian analysis also detected 27 loci as under selection. Among these 27 loci, 3 loci showed evidence of selection at a significance level using BayeScan program. On the other hand, up and downstream populations are strongly diverged at neutral loci with a Fst =0.37. Similar analysis will be done with all six populations to determine if there is a parallel pattern of adaptation across all streams. Furthermore, multi-locus among population covariance analysis will be done to identify potential markers under selection as well as to compare single locus versus multi-locus approaches for detecting local adaptation. Adaptive genes identified in this study can be used for future studies to design primers and test for adaptation in related crustacean species.

Keywords: Paratya australiensis, rainforest streams, selection, single nucleotide polymorphism (SNPs)

Procedia PDF Downloads 232

Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

Procedia PDF Downloads 32

Authors: M. H. A. D. de Silva, R. P. Hewawasam, M. A. G. Iresha

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Macrosomia is common in infants born to not only women diagnosed with gestational diabetes mellitus but also non-diabetic obese women. Maternal Body Mass Index (BMI) correlates with the incidence of large for gestational age infants. Obesity has reached epidemic levels in modern societies. During the past two decades, obesity in children and adolescents has risen significantly in Asian populations including Sri Lanka. There is increasing evidence to believe that infants who are born large for gestational age are more likely to be obese in childhood and adolescence and are at risk of cardiovascular and metabolic complications later in life. It is also established that Asians have lower skeletal muscle mass, low bone mineral content and excess body fat for a given BMI indicating a genetic predisposition in the occurrence of obesity. The objective of this study is to determine the effect of maternal weight, weight gain during pregnancy, c-peptide and insulin concentrations in the cord blood on the birth of appropriate for and large for gestational age infants in a tertiary care center in Southern Sri Lanka. Umbilical cord blood was collected from 90 newborns (Male 40, Female 50; gestational age 35-42 weeks) after double clamping the umbilical cord before separation of the placenta and the concentration of insulin and C-peptide were measured by ELISA technique. Anthropometric parameters of the newborn such as birth weight, length, ponderal index, occipital frontal, chest, hip and calf circumferences were measured, and characteristics of the mother were collected. The relationship between insulin, C-peptide and anthropometrics were assessed by Spearman correlation. The multiple logistic regression analysis examined influences of maternal weight, weight gain during pregnancy, C-peptide and insulin concentrations in cord blood as covariates on the birth of large for gestational age infants. A significant difference (P<0.001) was observed between the insulin levels of infants born large for gestational age (18.73 ± 0.52 µlU/ml) and appropriate for gestational age (13.08 ± 0.56 µlU/ml). Consistently, A significant decrease in concentration (41.68%, P<0.001) was observed between C-peptide levels of infants born large for gestational age and appropriate for gestational age. Cord blood insulin and C-peptide levels had a significant correlation with birth weight (r=0.35, P<0.05) of the newborn at delivery. Maternal weight and BMI which are indicators of maternal nutrition were proven to be directly correlated with birth weight and length. To our knowledge, this relationship was investigated for the first time in a Sri Lankan setting and was also evident in our results. This study confirmed the fact that insulin and C-peptide play a major role in regulating fetal growth. According to the results obtained in this study, we can suggest that the increased BMI of the mother has a direct influence on increased maternal insulin secretion, which may subsequently affect cord insulin and C-peptide levels and also birth weight of the infant.

Keywords: C-peptide, insulin, large for gestational age, maternal weight

Procedia PDF Downloads 144

Authors: Tiffanie-Marie Borg, Yasmin Zeinolabediny, Nima Heidari, Ali Noorani, Mark Slevin, Angel Cullen, Stefano Olgiati, Alberto Zerbi, Alessandro Danovi, Adrian Wilson

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Knee Osteoarthritis (OA) is a critical cause of disability globally. In recent years, there has been growing interest in non-invasive treatments, such as intra-articular injection of micro-fragmented fat (MFAT), showing great potential in treating OA. Mesenchymal stem cells (MSCs), originating from pericytes of micro-vessels in MFAT, can differentiate into mesenchymal lineage cells such as cartilage, osteocytes, adipocytes, and osteoblasts. Secretion of growth factor and cytokines from MSCs have the capability to inhibit T cell growth, reduced pain and inflammation, and create a micro-environment that through paracrine signaling, can promote joint repair and cartilage regeneration. Here we have shown, for the first time, data supporting the hypothesis that women respond better in terms of improvements in pain and function to MFAT injection compared to men. Historically, women have been underrepresented in studies, and studies with both sexes regularly fail to analyse the results by sex. To mitigate this bias and quantify it, we describe a technique using reproducible statistical analysis and replicable results with Open Access statistical software R to calculate the magnitude of this difference. Genetic, hormonal, environmental, and age factors play a role in our observed difference between the sexes. This observational, intention-to-treat study included the complete sample of 456 patients who agreed to be scored for pain (visual analogue scale (VAS)) and function (Oxford knee score (OKS)) at baseline regardless of subsequent changes to adherence or status during follow-up. We report that a significantly larger number of women responded to treatment than men: [90% vs. 60% change in VAS scores with 87% vs. 65% change in OKS scores, respectively]. Women overall had a stronger positive response to treatment with reduced pain and improved mobility and function. Pre-injection, our cohort of women were in more pain with worse joint function which is quite common to see in orthopaedics. However, during the 2-year follow-up, they consistently maintained a lower incidence of discomfort with superior joint function. This data clearly identifies a clear need for further studies to identify the cell and molecular biological and other basis for these differences and be able to utilize this information for stratification in order to improve outcome for both women and men.

Keywords: gender differences, micro-fragmented adipose tissue, knee osteoarthritis, stem cells

Procedia PDF Downloads 171

Authors: Walter Vera-Ortega, Idoia Busnadiego, Sam J. Wilson

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Introduction: Human Immunodeficiency Virus type 1 (HIV-1) is responsible for the acquired immunodeficiency syndrome (AIDS), a leading cause of death worldwide infecting millions of people each year. Despite intensive research in vaccine development, therapies against HIV-1 infection are not curative, and the huge genetic variability of HIV-1 challenges to drug development. Current animal models for HIV-1 research present important limitations, impairing the progress of in vivo approaches. Macaques require a CD8+ depletion to progress to AIDS, and the maintenance cost is high. Mice are a cheaper alternative but need to be 'humanized,' and breeding is not possible. The development of an HIV-1 clone able to replicate in mice is a challenging proposal. The lack of human co-factors in mice impedes the function of the HIV-1 accessory proteins, Tat and Rev, hampering HIV-1 replication. However, Tat and Rev function can be replaced by constitutive/chimeric promoters, codon-optimized proteins and the constitutive transport element (CTE), generating a novel HIV-1 clone able to replicate in mice without disrupting the amino acid sequence of the virus. By minimally manipulating the genomic 'identity' of the virus, we propose the generation of an HIV-1 clone able to replicate in mice to assist in antiviral drug development. Methods: i) Plasmid construction: The chimeric promoters and CTE copies were cloned by PCR using lentiviral vectors as templates (pCGSW and pSIV-MPCG). Tat mutants were generated from replication competent HIV-1 plasmids (NHG and NL4-3). ii) Infectivity assays: Retroviral vectors were generated by transfection of human 293T cells and murine NIH 3T3 cells. Virus titre was determined by flow cytometry measuring GFP expression. Human B-cells (AA-2) and Hela cells (TZMbl) were used for infectivity assays. iii) Protein analysis: Tat protein expression was determined by TZMbl assay and HIV-1 capsid by western blot. Results: We have determined that NIH 3T3 cells are able to generate HIV-1 particles. However, they are not infectious, and further analysis needs to be performed. Codon-optimized HIV-1 constructs are efficiently made in 293T cells in a Tat and Rev independent manner and capable of packaging a competent genome in trans. CSGW is capable of generating infectious particles in the absence of Tat and Rev in human cells when 4 copies of the CTE are placed preceding the 3’LTR. HIV-1 Tat mutant clones encoding different promoters are functional during the first cycle of replication when Tat is added in trans. Conclusion: Our findings suggest that the development of an HIV-1 Tat-Rev independent clone is challenging but achievable aim. However, further investigations need to be developed prior presenting our HIV-1 clone as a candidate model for research.

Keywords: codon-optimized, constitutive transport element, HIV-1, long terminal repeats, research model

Procedia PDF Downloads 287

Authors: Ella Tyuryumina, Alexey Neznanov

Abstract:

Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

Procedia PDF Downloads 317

Authors: Sanjay Rathee, Arti Kashyap

Abstract:

Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

Procedia PDF Downloads 268