Search results for: spatial patterns

Authors: Olivia A. Wilson, Hannah E. Power, Murray Kendall

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Sydney Harbour is an iconic location with a dense population and low-lying development. On the east coast of Australia, facing the Pacific Ocean, it is exposed to several tsunamigenic trenches. This paper presents a component of the most detailed assessment of the potential for earthquake-generated tsunami impact on Sydney Harbour to date. Models in this study use dynamic tides to account for tide-tsunami interaction. Sydney Harbour’s tidal range is 1.5 m, and the spring tides from January 2015 that are used in the modelling for this study are close to the full tidal range. The tsunami wave trains modelled include hypothetical tsunami generated from earthquakes of magnitude 7.5, 8.0, 8.5, and 9.0 M_W from the Puysegur and New Hebrides trenches as well as representations of the historical 1960 Chilean and 2011 Tohoku events. All wave trains are modelled for the peak wave to coincide with both a low tide and a high tide. A single wave train, representing a 9.0 M_W earthquake at the Puysegur trench, is modelled for peak waves to coincide with every hour across a 12-hour tidal phase. Using the hydrodynamic model ANUGA, results are compared according to the impact parameters of inundation area, depth variation and current speeds. Results show that both maximum inundation area and depth variation are tide dependent. Maximum inundation area increases when coincident with a higher tide, however, hazardous inundation is only observed for the larger waves modelled: NH90high and P90high. The maximum and minimum depths are deeper on higher tides and shallower on lower tides. The difference between maximum and minimum depths varies across different tidal phases although the differences are slight. Maximum current speeds are shown to be a significant hazard for Sydney Harbour; however, they do not show consistent patterns according to tide-tsunami phasing. The maximum current speed hazard is shown to be greater in specific locations such as Spit Bridge, a narrow channel with extensive marine infrastructure. The results presented for Sydney Harbour are novel, and the conclusions are consistent with previous modelling efforts in the greater area. It is shown that tide must be a consideration for both tsunami modelling and emergency management planning. Modelling with peak tsunami waves coinciding with a high tide would be a conservative approach; however, it must be considered that maximum current speeds may be higher on other tides.

Keywords: emergency management, sydney, tide-tsunami interaction, tsunami impact

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Authors: Zeynep Guler

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Argumentation and the production of scientific arguments are essential components that are necessary for helping students become scientifically literate through engaging them in constructing and critiquing ideas. Incorporating argumentation into science classrooms is challenging and can be a long-term process for both students and teachers. Students have difficulty in engaging tasks that require them to craft arguments, evaluate them to seek weaknesses, and revise them. Teachers also struggle with facilitating argumentation when they have underdeveloped science practices, underdeveloped pedagogical knowledge for argumentation science teaching, or underdeveloped teaching practice with argumentation (or a combination of all three). Thus, there is a need to support teachers in developing pedagogy for science teaching as argumentation, planning and implementing teaching practice for facilitating argumentation and also in becoming more agentic in this regards. Looking specifically at the experience of agency within education, it is arguable that agency is necessary for teachers’ renegotiation of professional purposes and practices in the light of changing educational practices. This study investigated how science teachers develop pedagogy for argumentation both individually and with their colleagues and also how teachers become more agentic (or not) through the active engagement of their contexts-for-action that refer to this as an ecological understanding of agency in order to positively influence or change their practice and their students' engagement with argumentation over two academic years. Through educational design study, this study conducted with three secondary science teachers (key stage 3-year 7 students aged 11-12) in the UK to find out if similar or different patterns of developing pedagogy for argumentation and of becoming more agentic emerge as they engage in planning and implementing a cycle of activities during the practice of teaching science with argumentation. Data from video and audio-recording of classroom practice and open-ended interviews with the science teachers were analysed using content analysis. The findings indicated that all the science teachers perceived strong agency in their opportunities to develop and apply pedagogical practices within the classroom. The teachers were pro-actively shaping their practices and classroom contexts in ways that were over and above the amendments to their pedagogy. They demonstrated some outcomes in developing pedagogy for argumentation and becoming more agentic in their teaching in this regards as a result of the collaboration with their colleagues and researcher; some appeared more agentic than others. The role of the collaboration between their colleagues was seen crucial for the teachers’ practice in the schools: close collaboration and support from other teachers in planning and implementing new educational innovations were seen as crucial for the development of pedagogy and becoming more agentic in practice. They needed to understand the importance of scientific argumentation but also understand how it can be planned and integrated into classroom practice. They also perceived constraint emerged from their lack of competence and knowledge in posing appropriate questions to help the students engage in argumentation, providing support for the students' construction of oral and written arguments.

Keywords: argumentation, teacher professional development, teacher agency, students' construction of argument

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Authors: Al Sayed Al Soudy, Valeria Maselli, Gianluca Polese, Anna Di Cosmo

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Cephalopods are considered as a model organism with a rich behavioral repertoire. Sophisticated behaviors were widely studied and described in different species such as Octopus vulgaris, who has evolved the largest and more complex nervous system among invertebrates. In O. vulgaris, cognitive abilities in problem-solving tasks and learning abilities are associated with long-term memory and spatial memory, mediated by highly developed sensory organs. They are equipped with sophisticated eyes, able to discriminate colors even with a single photoreceptor type, vestibular system, ‘lateral line analogue’, primitive ‘hearing’ system and olfactory organs. They can recognize chemical cues either through direct contact with odors sources using suckers or by distance through the olfactory organs. Cephalopods are able to detect widespread waterborne molecules by the olfactory organs. However, many volatile odorant molecules are insoluble or have a very low solubility in water, and must be perceived by direct contact. O. vulgaris, equipped with many chemosensory neurons located in their suckers, exhibits a peculiar behavior that can be provocatively described as 'smell by touch'. The aim of this study is to establish the priority given to chemical vs. visual perception in food choice. Materials and methods: Three different types of food (anchovies, clams, and mussels) were used, and all sessions were recorded with a digital camera. During the acclimatization period, Octopuses were exposed to the three types of food to test their natural food preferences. Later, to verify if food preference is maintained, food was provided in transparent screw-jars with pierced lids to allow both visual and chemical recognition of the food inside. Subsequently, we tested alternatively octopuses with food in sealed transparent screw-jars and food in blind screw-jars with pierced lids. As a control, we used blind sealed jars with the same lid color to verify a random choice among food types. Results and discussion: During the acclimatization period, O. vulgaris shows a higher preference for anchovies (60%) followed by clams (30%), then mussels (10%). After acclimatization, using the transparent and pierced screw jars octopus’s food choices resulted in 50-50 between anchovies and clams, avoiding mussels. Later, guided by just visual sense, with transparent but not pierced jars, their food preferences resulted in 100% anchovies. With pierced but not transparent jars their food preference resulted in 100% anchovies as first food choice, the clams as a second food choice result (33.3%). With no possibility to select food, neither by vision nor by chemoreception, the results were 20% anchovies, 20% clams, and 60% mussels. We conclude that O. vulgaris uses both chemical and visual senses in an integrative way in food choice, but if we exclude one of them, it appears clear that its food preference relies on chemical sense more than on visual perception.

Keywords: food choice, Octopus vulgaris, olfaction, sensory organs, visual sense

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Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: Desta Kebede Ayana, Lies Sercu, Demelash Mengistu

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The study is set in Ethiopia, a sub-Saharan multilingual, multiethnic African country, which has seen a significant increase in the number of universities in recent years. The aim of this growth is to provide access to education for all cultural and linguistic groups across the country. However, there are challenges in promoting intercultural competence among students in this diverse context. The aim of the study is to investigate the interculturalization of Ethiopian Higher Education Institutions as perceived by university lecturers and administrators. In particular, the study aims to determine the level of support for this educational innovation and gather suggestions for its implementation and institutionalization. The researchers employed semi-structured interviews with administrators and lecturers from two large Ethiopian universities to gather data. Thematic analysis was utilized for coding and analyzing the interview data, with the assistance of the NVIVO software. The findings obtained from the grounded analysis of the interview data reveal that while there are opportunities for interculturalization in the curriculum and campus life, support for educational innovation remains low. Administrators and lecturers also emphasize the government's responsibility to prioritize interculturalization over other educational innovation goals. The study contributes to the existing literature by examining an under-researched population in an under-researched context. Additionally, the study explores whether Western perspectives of intercultural competence align with the African context, adding to the theoretical understanding of intercultural education. The data for this study was collected through semi-structured interviews conducted with administrators and lecturers from two large Ethiopian universities. The interviews allowed for an in-depth exploration of the participants' views on interculturalization in higher education. Thematic analysis was applied to the interview data, allowing for the identification and organization of recurring themes and patterns. The analysis was conducted using the NVIVO software, which aided in coding and analyzing the data. The study addresses the extent to which administrators and lecturers support the interculturalization of Ethiopian Higher Education Institutions. It also explores their suggestions for implementing and institutionalizing intercultural education, as well as their perspectives on the current level of institutionalization. The study highlights the challenges in interculturalizing Ethiopian universities and emphasizes the need for greater support and prioritization of intercultural education. It also underscores the importance of considering the African context when conceptualizing intercultural competence. This research contributes to the understanding of intercultural education in diverse contexts and provides valuable insights for policymakers and educational institutions aiming to promote intercultural competence in higher education settings.

Keywords: administrators, educational change, Ethiopia, intercultural competence, lecturers

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Authors: Parisa Mansour

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Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

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Authors: Prabhat Kashyap, Krishan Kumar

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Delhi, the capital of India, is one of the most populated and polluted city among the world. In terms of air quality, Delhi’s air is degrading day by day & becomes worst of any major city in the world. The role of biogenic volatile organic compounds (BVOCs) is not much studied in cities like Delhi as a culprit for degraded air quality. They not only play a critical role in rural areas but also determine the atmospheric chemistry of urban areas as well. Particularly, Isoprene (2-methyl 1,3-butadiene, C5H8) is the single largest emitted compound among other BVOCs globally, that influence the tropospheric ozone chemistry in urban environment as the ozone forming potential of isoprene is very high. It is mainly emitted by vegetation & a small but significant portion is also released by vehicular exhaust of petrol operated vehicles. This study investigates the spatial and temporal variations of quantitative measurements of isoprene emissions along with different traffic tracers in 2 different seasons (post-monsoon & winter) at four different locations of Delhi. For the quantification of anthropogenic and biogenic isoprene, two sites from traffic intersections (Punjabi Bagh & CRRI) and two sites from vegetative locations (JNU & Yamuna Biodiversity Park) were selected in the vicinity of isoprene emitting tree species like Ficus religiosa, Dalbergia sissoo, Eucalyptus species etc. The concentrations of traffic tracers like benzene, toluene were also determined & their robust ratios with isoprene were used to differentiate anthropogenic isoprene with biogenic portion at each site. The ozone forming potential (OFP) of all selected species along with isoprene was also estimated. For collection of intra-day samples (3 times a day) in each season, a pre-conditioned fenceline monitoring (FLM) carbopack X thermal desorption tubes were used and further analysis was done with Gas chromatography attached with mass spectrometry (GC-MS). The results of the study proposed that the ambient air isoprene is always higher in post-monsoon season as compared to winter season at all the sites because of high temperature & intense sunlight. The maximum isoprene emission flux was always observed during afternoon hours in both seasons at all sites. The maximum isoprene concentration was found to be 13.95 ppbv at Biodiversity Park during afternoon time in post monsoon season while the lower concentration was observed as low as 0.07 ppbv at the same location during morning hours in winter season. OFP of isoprene at vegetation sites is very high during post-monsoon because of high concentrations. However, OFP for other traffic tracers were high during winter seasons & at traffic locations. Furthermore, high correlation between isoprene emissions with traffic volume at traffic sites revealed that a noteworthy share of its emission also originates from road traffic.

Keywords: biogenic VOCs, isoprene emission, anthropogenic isoprene, urban vegetation

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Authors: G. Zakharov, Z. Aslamazashvili, M. Chikhradze, D. Kvaskhvadze, N. Khidasheli, S. Gvazava

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Traditional technologies for processing iron-containing industrial waste, including steel-rolling production, are associated with significant energy costs, the long duration of processes, and the need to use complex and expensive equipment. Waste generated during the industrial process negatively affects the environment, but at the same time, it is a valuable raw material and can be used to produce new marketable products. The study of the effectiveness of self-propagating high-temperature synthesis (SHS) methods, which are characterized by the simplicity of the necessary equipment, the purity of the final product, and the high processing speed, is under the wide scientific and practical interest to solve the set problem. The work presents technological aspects of the production of Ferro boron by the method of SHS - metallurgy from iron-containing wastes of rolled production for alloying of cast iron and results of the effect of alloying element on the degree of boron assimilation with liquid cast iron. Features of Fe-B system combustion have been investigated, and the main parameters to control the phase composition of synthesis products have been experimentally established. Effect of overloads on patterns of cast ligatures formation and mechanisms structure formation of SHS products was studied. It has been shown that an increase in the content of hematite Fe₂O₃ in iron-containing waste leads to an increase in the content of phase FeB and, accordingly, the amount of boron in the ligature. Boron content in ligature is within 3-14%, and the phase composition of obtained ligatures consists of Fe₂B and FeB phases. Depending on the initial composition of the wastes, the yield of the end product reaches 91 - 94%, and the extraction of boron is 70 - 88%. Combustion processes of high exothermic mixtures allow to obtain a wide range of boron-containing ligatures from industrial wastes. In view of the relatively low melting point of the obtained SHS-ligature, the positive dynamics of boron absorption by liquid iron is established. According to the obtained data, the degree of absorption of the ligature by alloying gray cast iron at 1450°C is 80-85%. When combined with the treatment of liquid cast iron with magnesium, followed by alloying with the developed ligature, boron losses are reduced by 5-7%. At that, uniform distribution of boron micro-additives in the volume of treated liquid metal is provided. Acknowledgment: This work was supported by Shota Rustaveli Georgian National Science Foundation of Georgia (SRGNSFG) under the GENIE project (grant number № CARYS-19-802).

Keywords: self-propagating high-temperature synthesis, cast iron, industrial waste, ductile iron, structure formation

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Authors: Josef Uher, Jana Boháčová, Richard Kadeřábek

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In this paper, we present a multi-robot imaging and irradiation research platform referred to as Irradion, with full capabilities of portable arbitrary path computed tomography (CT). Irradion is an imaging and irradiation unit entirely based on robotic arms for research on cancer treatment with ion beams on small animals (mice or rats). The platform comprises two subsystems that combine several imaging modalities, such as 2D X-ray imaging, CT, and particle tracking, with precise positioning of a small animal for imaging and irradiation. Computed Tomography: The CT subsystem of the Irradion platform is equipped with two 6-joint robotic arms that position a photon counting detector and an X-ray tube independently and freely around the scanned specimen and allow image acquisition utilizing computed tomography. Irradiation measures nearly all conventional 2D and 3D trajectories of X-ray imaging with precisely calibrated and repeatable geometrical accuracy leading to a spatial resolution of up to 50 µm. In addition, the photon counting detectors allow X-ray photon energy discrimination, which can suppress scattered radiation, thus improving image contrast. It can also measure absorption spectra and recognize different materials (tissue) types. X-ray video recording and real-time imaging options can be applied for studies of dynamic processes, including in vivo specimens. Moreover, Irradion opens the door to exploring new 2D and 3D X-ray imaging approaches. We demonstrate in this publication various novel scan trajectories and their benefits. Proton Imaging and Particle Tracking: The Irradion platform allows combining several imaging modules with any required number of robots. The proton tracking module comprises another two robots, each holding particle tracking detectors with position, energy, and time-sensitive sensors Timepix3. Timepix3 detectors can track particles entering and exiting the specimen and allow accurate guiding of photon/ion beams for irradiation. In addition, quantifying the energy losses before and after the specimen brings essential information for precise irradiation planning and verification. Work on the small animal research platform Irradion involved advanced software and hardware development that will offer researchers a novel way to investigate new approaches in (i) radiotherapy, (ii) spectral CT, (iii) arbitrary path CT, (iv) particle tracking. The robotic platform for imaging and radiation research developed for the project is an entirely new product on the market. Preclinical research systems with precision robotic irradiation with photon/ion beams combined with multimodality high-resolution imaging do not exist currently. The researched technology can potentially cause a significant leap forward compared to the current, first-generation primary devices.

Keywords: arbitrary path CT, robotic CT, modular, multi-robot, small animal imaging

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Authors: A. Maghoul, A. Rostampouryasouri, MR. Maghami

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The development of an urban design and power network planning has been gaining momentum in recent years. The integration of renewable energy with urban design has been widely regarded as an increasingly important solution leading to climate change and energy security. Through the use of passive strategies and solar integration with Urban Building Energy Modeling (UBEM) tools, architects and designers can create high-quality designs that meet the needs of clients and stakeholders. To determine the most effective ways of combining renewable energy with urban development, we analyze the relationship between urban form and renewable energy production. The procedure involved in this practice include passive solar gain (in building design and urban design), solar integration, location strategy, and 3D models with a case study conducted in Tehran, Iran. The study emphasizes the importance of spatial and temporal considerations in the development of sector coupling strategies for solar power establishment in arid and semi-arid regions. The substation considered in the research consists of two parallel transformers, 13 lines, and 38 connection points. Each urban load connection point is equipped with 500 kW of solar PV capacity and 1 kWh of battery Energy Storage (BES) to store excess power generated from solar, injecting it into the urban network during peak periods. The simulations and analyses have occurred in EnergyPlus software. Passive solar gain involves maximizing the amount of sunlight that enters a building to reduce the need for artificial lighting and heating. Solar integration involves integrating solar photovoltaic (PV) power into smart grids to reduce emissions and increase energy efficiency. Location strategy is crucial to maximize the utilization of solar PV in an urban distribution feeder. Additionally, 3D models are made in Revit, and they are keys component of decision-making in areas including climate change mitigation, urban planning, and infrastructure. we applied these strategies in this research, and the results show that it is possible to create sustainable and energy-efficient urban environments. Furthermore, demand response programs can be used in conjunction with solar integration to optimize energy usage and reduce the strain on the power grid. This study highlights the influence of ancient Persian architecture on Iran's urban planning system, as well as the potential for reducing pollutants in building construction. Additionally, the paper explores the advances in eco-city planning and development and the emerging practices and strategies for integrating sustainability goals.

Keywords: energy-efficient urban planning, sustainable architecture, solar energy, sustainable urban design

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Authors: Masato Koizumi, Yuya Oshio, Ikkoh Funaki

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Magnetoplasma Sail (MPS) is a future spacecraft propulsion that generates high levels of thrust by inducing an artificial magnetosphere to capture and deflect solar wind charged particles in order to transfer momentum to the spacecraft. By injecting plasma in the spacecraft’s magnetic field region, the ring current azimuthally drifts on the equatorial plane about the dipole magnetic field generated by the current flowing through the solenoid attached on board the spacecraft. This ring current results in magnetosphere inflation which improves the thrust performance of MPS spacecraft. In this present study, the ring current was experimentally measured using three Rogowski Current Probes positioned in a circular array about the laboratory model of MPS spacecraft. This investigation aims to determine the detailed structure of ring current through physical experimentation performed under two different magnetic field strengths engendered by varying the applied voltage on the solenoid with 300 V and 600 V. The expected outcome was that the three current probes would detect the same current since all three probes were positioned at equal radial distance of 63 mm from the center of the solenoid. Although experimental results were numerically implausible due to probable procedural error, the trends of the results revealed three pieces of perceptive evidence of the ring current behavior. The first aspect is that the drift direction of the ring current depended on the strength of the applied magnetic field. The second aspect is that the diamagnetic current developed at a radial distance not occupied by the three current probes under the presence of solar wind. The third aspect is that the ring current distribution varied along the circumferential path about the spacecraft’s magnetic field. Although this study yielded experimental evidence that differed from the original hypothesis, the three key findings of this study have informed two critical MPS design solutions that will potentially improve thrust performance. The first design solution is the positioning of the plasma injection point. Based on the implication of the first of the three aspects of ring current behavior, the plasma injection point must be located at a distance instead of at close proximity from the MPS Solenoid for the ring current to drift in the direction that will result in magnetosphere inflation. The second design solution, predicated by the third aspect of ring current behavior, is the symmetrical configuration of plasma injection points. In this study, an asymmetrical configuration of plasma injection points using one plasma source resulted in a non-uniform distribution of ring current along the azimuthal path. This distorts the geometry of the inflated magnetosphere which minimizes the deflection area for the solar wind. Therefore, to realize a ring current that best provides the maximum possible inflated magnetosphere, multiple plasma sources must be spaced evenly apart for the plasma to be injected evenly along its azimuthal path.

Keywords: Magnetoplasma Sail, magnetosphere inflation, ring current, spacecraft propulsion

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Authors: Michelle Blewitt, Scott P. Wilson, Heidi Tait, Juniper Riordan

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Rubber crumb is a physical and chemical pollutant of concern for the environment and human health, warranting immediate investigations into its pathways to the environment and potential impacts. This emerging microplastic is created by shredding end-of-life tyres into ‘rubber crumb’ particles between 1-5mm used on synthetic turf fields and soft-fall playgrounds as a solution to intensifying tyre waste worldwide. Despite having known toxic and carcinogenic properties, studies into the transportation pathways and movement patterns of rubber crumbs from these surfaces remain in their infancy. To address this deficit, AUSMAP, the Australian Microplastic Assessment Project, in partnership with the Tangaroa Blue Foundation, conducted a study to quantify crumb loss from soft-fall surfaces. To our best knowledge, this is the first of its kind, with funding for the audits being provided by the Australian Government’s Reef Trust. Sampling occurred at 12 soft-fall playgrounds within the Great Barrier Reef Catchment Area on Australia’s North-East coast, in close proximity to the United Nations World Heritage Listed Reef. Samples were collected over a 12-month period using randomized sediment cores at 0, 2 and 4 meters away from the playground edge along a 20-meter transect. This approach facilitated two objectives pertaining to particle movement: to establish that crumb loss is occurring and that it decreases with distance from the soft-fall surface. Rubber crumb abundance was expressed as a total value and used to determine an expected average of rubber crumb loss per m2. An Analysis of Variance (ANOVA) was used to compare the differences in crumb abundance at each interval from the playground. Site characteristics, including surrounding sediment type, playground age, degree of ultra-violet exposure and amount of foot traffic, were additionally recorded for the comparison. Preliminary findings indicate that crumb is being lost at considerable rates from soft-fall playgrounds in the region, emphasizing an urgent need to further examine it as a potential source of aquatic pollution, soil contamination and threat to individuals who regularly utilize these surfaces. Additional implications for the future of rubber crumbs as a fit-for-purpose recycling initiative will be discussed with regard to industry, governments and the economic burden of surface maintenance and/ or replacement.

Keywords: microplastics, toxic rubber crumb, litter pathways, marine environment

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Authors: A. Van Staden, A. Tolmie, E. Vorster

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Research confirms the multifaceted nature of spelling development and underscores the importance of both cognitive and linguistic skills that affect sound spelling development such as working and long-term memory, phonological and orthographic awareness, mental orthographic images, semantic knowledge and morphological awareness. This has clear implications for many South African English second language spellers (L2) who attempt to become proficient spellers. Since English has an opaque orthography, with irregular spelling patterns and insufficient sound/grapheme correspondences, L2 spellers can neither rely, nor draw on the phonological awareness skills of their first language (for example Sesotho and many other African languages), to assist them to spell the majority of English words. Epistemologically, this research is informed by social constructivism. In addition the researchers also hypothesized that the principles of the Overlapping Waves Theory was an appropriate lens through which to investigate whether L2 spellers could significantly improve their spelling skills via the implementation of an alternative route to spelling development, namely the orthographic route, and more specifically via the application of visual imagery. Post-test results confirmed the results of previous research that argues for the interactive nature of different cognitive and linguistic systems such as working memory and its subsystems and long-term memory, as learners were systematically guided to store visual orthographic images of words in their long-term lexicons. Moreover, the results have shown that L2 spellers in the experimental group (n = 9) significantly outperformed L2 spellers (n = 9) in the control group whose intervention involved phonological awareness (and coding) including the teaching of spelling rules. Consequently, L2 learners in the experimental group significantly improved in all the post-test measures included in this investigation, namely the four sub-tests of short-term memory; as well as two spelling measures (i.e. diagnostic and standardized measures). Against this background, the findings of this study look promising and have shown that, within a social-constructivist learning environment, learners can be systematically guided to apply higher-order thinking processes such as visual imagery to successfully store and retrieve mental images of spelling words from their output lexicons. Moreover, results from the present study could play an important role in directing research into this under-researched aspect of L2 literacy development within the South African education context.

Keywords: English second language spellers, phonological and orthographic coding, social constructivism, visual imagery as spelling strategy

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Ming-Dong Wang, Abigail F. Ruby, Michelle E. Ross

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Methylphenidate is a first-line treatment drug for attention deficit hyperactivity disorder (ADHD), a common mental health disorder in children and adolescents. Over the last several decades, the rate of children and adolescents using ADHD medication has been increasing in many countries. A recent study found that the prevalence of ADHD medication use among children aged 3-18 years increased in 13 different world regions between 2001 and 2015, where the absolute increase ranged from 0.02 to 0.26% per year. The goal of this study was to examine the use of methylphenidate in Canadian children and its associated adverse reactions. Methylphenidate use information among young Canadians aged 0-14 years was extracted from IQVIA data on prescriptions dispensed by pharmacies between April 2014 and June 2020. The adverse reaction information associated with methylphenidate use was extracted from the Canada Vigilance database for the same time period. Methylphenidate use trends were analyzed based on sex, age group (0-4 years, 5-9 years, and 10-14 years), and geographical location (province). The common classes of adverse reactions associated with methylphenidate use were sorted, and the relative risks associated with methylphenidate use as compared with two second-line amphetamine medications for ADHD were estimated. This study revealed that among Canadians aged 0-14 years, every 100 people used about 25 prescriptions (or 23,000 mg) of methylphenidate per year during the study period, and the use increased with time. Boys used almost three times more methylphenidate than girls. The amount of drug used was inversely associated with age: Canadians aged 10-14 years used nearly three times as many drugs compared to those aged 5-9 years. Seasonal methylphenidate use patterns were apparent among young Canadians, but the seasonal trends differed among the three age groups. Methylphenidate use varied from region to region, and the highest methylphenidate use was observed in Quebec, where the use of methylphenidate was at least double that of any other province. During the study period, Health Canada received 304 adverse reaction reports associated with the use of methylphenidate for Canadians aged 0-14 years. The number of adverse reaction reports received for boys was 3.5 times higher than that for girls. The three most common adverse reaction classes were psychiatric disorders, nervous system disorders and injury, poisoning procedural complications. The number one commonly reported adverse reaction for boys was aggression (11.2%), while for girls, it was a tremor (9.6%). The safety profile in terms of adverse reaction classes associated with methylphenidate use was similar to that of the selected control products. Methylphenidate is a commonly used pharmaceutical product in young Canadians, particularly in the province of Quebec. Boys used approximately three times more of this product as compared to girls. Future investigation is needed to determine what factors are associated with the observed geographic variations in Canada.

Keywords: adverse reaction risk, methylphenidate, prescription trend, use variation

Procedia PDF Downloads 147

Authors: Guntur Bagus Pamungkas

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As part of a tropical country that is normally rich in forest land areas, Indonesia has always been in the world's spotlight due to its significantly increasing process of deforestation. In one hand, it is related to the mainstay for maintaining the sustainability of the earth's ecosystem functions. On the other hand, they also cover the various potential sources of the global economy. Therefore, it can always be the target of different scale of investors to excessively exploit them. No wonder the emergence of disasters in various characteristics always comes up. In fact, the deforestation phenomenon does not only occur in various forest land areas in the main islands of Indonesia but also includes Java Island, the most densely populated areas in the world. This island only remains the forest land of about 9.8% of the total forest land in Indonesia due to its long history of it, especially in Central Java Province, the most densely populated area in Java. Again, not surprisingly, this province belongs to the area with the highest frequency of disasters because of it, landslides in particular. One of the areas that often experience it is Banjarnegara District, especially in mountainous areas that lies in the range from 1000 to 3000 meters above sea level, where the remains of land forest area can easyly still be found. Even among them still leaves less untouchable tropical rain forest whose area also covers part of a neighboring district, Pekalongan, which is considered to be the rest of the world's little paradise on Earth. The district's landscape is indeed beautiful, especially in the Dieng area, a major tourist destination in Central Java Province after Borobudur Temple. However, annually hazardous always threatens this district due to this landslide disaster. Even, there was a tragic event that was buried with its inhabitants a few decades ago. This research aims to find part of the concept of effective forest management through monitoring the presence of remaining forest areas in this area. The research implemented monitoring of deforestation rates using the Stochastic Cellular Automata-Markov Chain (SCA-MC) method, which serves to provide a spatial simulation of land use and cover changes (LULCC). This geospatial process uses the Landsat-8 OLI image product with Thermal Infra-Red Sensors (TIRS) Band 10 in 2020 and Landsat 5 TM with TIRS Band 6 in 2010. Then it is also integrated with physical and social geography issues using the QGIS 2.18.11 application with the Mollusce Plugin, which serves to clarify and calculate the area of land use and cover, especially in forest areas—using the LULCC method, which calculates the rate of forest area reduction in 2010-2020 in Banjarnegara District. Since the dependence of this area on the use of forest land is quite high, concepts and preventive actions are needed, such as rehabilitation and reforestation of critical lands through providing proper monitoring and targeted forest management to restore its ecosystem in the future.

Keywords: deforestation, populous area, LULCC method, proper control and effective forest management

Procedia PDF Downloads 121

Authors: Mao Zhaofang, Xu Yida, Fang Kan, Fu Enyuan, Zhao Zhao

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Nowadays, last-mile distribution plays an increasingly important role in the whole industrial chain delivery link and accounts for a large proportion of the whole distribution process cost. Promoting the upgrading of logistics networks and improving the layout of final distribution points has become one of the trends in the development of modern logistics. Due to the discrete and heterogeneous needs and spatial distribution of customer demand, which will lead to a higher delivery failure rate and lower vehicle utilization, last-mile delivery has become a time-consuming and uncertain process. As a result, courier companies have introduced a range of innovative parcel storage facilities, including pick-up points and lockers. The introduction of pick-up points and lockers has not only improved the users’ experience but has also helped logistics and courier companies achieve large-scale economy. Against the backdrop of the COVID-19 of the previous period, contactless delivery has become a new hotspot, which has also created new opportunities for the development of collection services. Therefore, a key issue for logistics companies is how to design/redesign their last-mile distribution network systems to create integrated logistics and distribution networks that consider pick-up points and lockers. This paper focuses on the introduction of self-pickup facilities in new logistics and distribution scenarios and the heterogeneous demands of customers. In this paper, we consider two types of demand, including ordinary products and refrigerated products, as well as corresponding transportation vehicles. We consider the constraints associated with self-pickup points and lockers and then address the location-routing problem with self-pickup facilities and heterogeneous demands (LRP-PFHD). To solve this challenging problem, we propose a mixed integer linear programming (MILP) model that aims to minimize the total cost, which includes the facility opening cost, the variable transport cost, and the fixed transport cost. Due to the NP-hardness of the problem, we propose a hybrid adaptive large-neighbourhood search algorithm to solve LRP-PFHD. We evaluate the effectiveness and efficiency of the proposed algorithm by using instances generated based on benchmark instances. The results demonstrate that the hybrid adaptive large neighbourhood search algorithm is more efficient than MILP solvers such as Gurobi for LRP-PFHD, especially for large-scale instances. In addition, we made a comprehensive analysis of some important parameters (e.g., facility opening cost and transportation cost) to explore their impacts on the results and suggested helpful managerial insights for courier companies.

Keywords: city logistics, last-mile delivery, location-routing, adaptive large neighborhood search

Procedia PDF Downloads 62

Authors: Jesús Horacio, Alfredo Ollero, Víctor Bouzas-Blanco, Augusto Pérez-Alberti

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Rivers have traditionally been classified, assessed and managed in terms of hydrological, chemical and / or biological criteria. Geomorphological classifications had in the past a secondary role, although proposals like River Styles Framework, Catchment Baseline Survey or Stroud Rural Sustainable Drainage Project did incorporate geomorphology for management decision-making. In recent years many studies have been attracted to the geomorphological component. The geomorphological processes and their associated forms determine the structure of a river system. Understanding these processes and forms is a critical component of the sustainable rehabilitation of aquatic ecosystems. The fluvial auto-classification approach suggests that a river is a self-built natural system, with processes and forms designed to effectively preserve their ecological function (hydrologic, sedimentological and biological regime). Fluvial systems are formed by a wide range of elements with multiple non-linear interactions on different spatial and temporal scales. Besides, the fluvial auto-classification concept is built using data from the river itself, so that each classification developed is peculiar to the river studied. The variables used in the classification are specific stream power and mean grain size. A discriminant analysis showed that these variables are the best characterized processes and forms. The statistical technique applied allows to get an individual discriminant equation for each geomorphological type. The geomorphological classification was developed using sites with high naturalness. Each site is a control point of high ecological and geomorphological quality. The changes in the conditions of the control points will be quickly recognizable, and easy to apply a right management measures to recover the geomorphological type. The study focused on Galicia (NW Spain) and the mapping was made analyzing 122 control points (sites) distributed over eight river basins. In sum, this study provides a method for fluvial geomorphological classification that works as an open and flexible tool underlying the fluvial auto-classification concept. The hydrographic mapping is the visual expression of the results, such that each river has a particular map according to its geomorphological characteristics. Each geomorphological type is represented by a particular type of hydraulic geometry (channel width, width-depth ratio, hydraulic radius, etc.). An alteration of this geometry is indicative of a geomorphological disturbance (whether natural or anthropogenic). Hydrographic mapping is also dynamic because its meaning changes if there is a modification in the specific stream power and/or the mean grain size, that is, in the value of their equations. The researcher has to check annually some of the control points. This procedure allows to monitor the geomorphology quality of the rivers and to see if there are any alterations. The maps are useful to researchers and managers, especially for conservation work and river restoration.

Keywords: fluvial auto-classification concept, mapping, geomorphology, river

Procedia PDF Downloads 354

Authors: Nina Sankat, Gerd Wilsch, Cassian Gottlieb, Steven Millar, Tobias Guenther

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Laser-Induced Breakdown Spectroscopy (LIBS) is a combination of laser ablation and optical emission spectroscopy, which in principle can simultaneously analyze all elements on the periodic table. Materials can be analyzed in terms of chemical composition in a two-dimensional, time efficient and minor destructive manner. These advantages predestine LIBS as a monitoring technique in the field of civil engineering. The decreasing service life of concrete infrastructures is a continuously growing problematic. A variety of intruding, harmful substances can damage the reinforcement or the concrete itself. To insure a sufficient service life a regular monitoring of the structure is necessary. LIBS offers many applications to accomplish a successful examination of the conditions of concrete structures. A selection of those applications are the 2D-evaluation of chlorine-, sodium- and sulfur-concentration, the identification of carbonation depths and the representation of the heterogeneity of concrete. LIBS obtains this information by using a pulsed laser with a short pulse length (some mJ), which is focused on the surfaces of the analyzed specimen, for this only an optical access is needed. Because of the high power density (some GW/cm²) a minimal amount of material is vaporized and transformed into a plasma. This plasma emits light depending on the chemical composition of the vaporized material. By analyzing the emitted light, information for every measurement point is gained. The chemical composition of the scanned area is visualized in a 2D-map with spatial resolutions up to 0.1 mm x 0.1 mm. Those 2D-maps can be converted into classic depth profiles, as typically seen for the results of chloride concentration provided by chemical analysis like potentiometric titration. However, the 2D-visualization offers many advantages like illustrating chlorine carrying cracks, direct imaging of the carbonation depth and in general allowing the separation of the aggregates from the cement paste. By calibrating the LIBS-System, not only qualitative but quantitative results can be obtained. Those quantitative results can also be based on the cement paste, while excluding the aggregates. An additional advantage of LIBS is its mobility. By using the mobile system, located at BAM, onsite measurements are feasible. The mobile LIBS-system was already used to obtain chloride, sodium and sulfur concentrations onsite of parking decks, bridges and sewage treatment plants even under hard conditions like ongoing construction work or rough weather. All those prospects make LIBS a promising method to secure the integrity of infrastructures in a sustainable manner.

Keywords: concrete, damage assessment, harmful substances, LIBS

Procedia PDF Downloads 166

Authors: Somnath Bhattacharya, Kamal Sharma, Vaibhav Sonkar

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Composite materials emerged in the middle of the 20th century as a promising class of engineering materials providing new prospects for modern technology. Recently, a new class of composite materials known as functionally graded materials (FGMs) has drawn considerable attention of the scientific community. In general, FGMs are defined as composite materials in which the composition or microstructure or both are locally varied so that a certain variation of the local material properties is achieved. This gradual change in composition and microstructure of material is suitable to get gradient of properties and performances. FGMs are synthesized in such a way that they possess continuous spatial variations in volume fractions of their constituents to yield a predetermined composition. These variations lead to the formation of a non-homogeneous macrostructure with continuously varying mechanical and / or thermal properties in one or more than one direction. Lightweight functionally graded composites with high strength to weight and stiffness to weight ratios have been used successfully in aircraft industry and other engineering applications like in electronics industry and in thermal barrier coatings. In the present work, elastic-plastic crack growth problems (using Ramberg-Osgood Model) in an FGM plate under cyclic load has been explored by extended finite element method. Both edge and centre crack problems have been solved by taking additionally holes, inclusions and minor cracks under plane stress conditions. Both soft and hard inclusions have been implemented in the problems. The validity of linear elastic fracture mechanics theory is limited to the brittle materials. A rectangular plate of functionally graded material of length 100 mm and height 200 mm with 100% copper-nickel alloy on left side and 100% ceramic (alumina) on right side is considered in the problem. Exponential gradation in property is imparted in x-direction. A uniform traction of 100 MPa is applied to the top edge of the rectangular domain along y direction. In some problems, domain contains major crack along with minor cracks or / and holes or / and inclusions. Major crack is located the centre of the left edge or the centre of the domain. The discontinuities, such as minor cracks, holes, and inclusions are added either singly or in combination with each other. On the basis of this study, it is found that effect of minor crack in the domain’s failure crack length is minimum whereas soft inclusions have moderate effect and the effect of holes have maximum effect. It is observed that the crack growth is more before the failure in each case when hard inclusions are present in place of soft inclusions.

Keywords: elastic-plastic, fatigue crack, functionally graded materials, extended finite element method (XFEM)

Procedia PDF Downloads 372

Authors: Samuele Ghignoli, Valentina de Lorenzi, Gianmarco Ferri, Stefano Luin, Francesco Cardarelli

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Insulin and glucagon are the two essential hormones for maintaining proper blood glucose homeostasis, which is disrupted in Diabetes. A constantly growing research interest has been focused on the study of the subcellular structures involved in hormone secretion, namely insulin- and glucagon-containing granules, and on the mechanisms regulating their behaviour. Yet, while several successful attempts were reported describing the dynamic properties of insulin granules, little is known about their counterparts in α cells, the glucagon-containing granules. To fill this gap, we used αTC1 clone 9 cells as a model of α cells and ZIGIR as a fluorescent Zinc chelator for granule labelling. We started by using spatiotemporal fluorescence correlation spectroscopy in the form of imaging-derived mean square displacement (iMSD) analysis. This afforded quantitative information on the average dynamical and structural properties of glucagon granules having insulin granules as a benchmark. Interestingly, the iMSD sensitivity to average granule size allowed us to confirm that glucagon granules are smaller than insulin ones (~1.4 folds, further validated by STORM imaging). To investigate possible heterogeneities in granule dynamic properties, we moved from correlation spectroscopy to single particle tracking (SPT). We developed a MATLAB script to localize and track single granules with high spatial resolution. This enabled us to classify the glucagon granules, based on their dynamic properties, as ‘blocked’ (i.e., trajectories corresponding to immobile granules), ‘confined/diffusive’ (i.e., trajectories corresponding to slowly moving granules in a defined region of the cell), or ‘drifted’ (i.e., trajectories corresponding to fast-moving granules). In cell-culturing control conditions, results show this average distribution: 32.9 ± 9.3% blocked, 59.6 ± 9.3% conf/diff, and 7.4 ± 3.2% drifted. This benchmarking provided us with a foundation for investigating selected experimental conditions of interest, such as the glucagon-granule relationship with the cytoskeleton. For instance, if Nocodazole (10 μM) is used for microtubule depolymerization, the percentage of drifted motion collapses to 3.5 ± 1.7% while immobile granules increase to 56.0 ± 10.7% (remaining 40.4 ± 10.2% of conf/diff). This result confirms the clear link between glucagon-granule motion and cytoskeleton structures, a first step towards understanding the intracellular behaviour of this subcellular compartment. The information collected might now serve to support future investigations on glucagon granules in physiology and disease. Acknowledgment: This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 866127, project CAPTUR3D).

Keywords: glucagon granules, single particle tracking, correlation spectroscopy, ZIGIR

Procedia PDF Downloads 82

Authors: Ombir Singh

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In spite of the religious and cultural pre-dominance of the river Ganga in the Indian ethos, fragmentation and degradation of the river continued down the ages. Recognizing the national concern on environmental degradation of the river and its basin, Ministry of Water Resources, River Development & Ganga Rejuvenation (MoWR,RD&GR), Government of India has initiated a number of pilot schemes for the rejuvenation of river Ganga under the ‘Namami Gange’ Programme. Considering the diversity, complexity, and intricacies of forest ecosystems and pivotal multiple functions performed by them and their inter-connectedness with highly dynamic river ecosystems, forestry interventions all along the river Ganga from its origin at Gaumukh, Uttarakhand to its mouth at Ganga Sagar, West Bengal has been planned by the ministry. For that Forest Research Institute (FRI) in collaboration with National Mission for Clean Ganga (NMCG) has prepared a Detailed Project Report (DPR) on Forestry Interventions for Ganga. The Institute has adopted an extensive consultative process at the national and state levels involving various stakeholders relevant in the context of river Ganga and employed a science-based methodology including use of remote sensing and GIS technologies for geo-spatial analysis, modeling and prioritization of sites for proposed forestation and conservation interventions. Four sets of field data formats were designed to obtain the field based information for forestry interventions, mainly plantations and conservation measures along the river course. In response, five stakeholder State Forest Departments had submitted more than 8,000 data sheets to the Institute. In order to analyze a voluminous field data received from five participating states, the Institute also developed a software to collate, analyze and generation of reports on proposed sites in Ganga basin. FRI has developed potential plantation and treatment models for the proposed forestry and other conservation measures in major three types of landscape components visualized in the Ganga riverscape. These are: (i) Natural, (ii) Agriculture, and (iii) Urban Landscapes. Suggested plantation models broadly varied for the Uttarakhand Himalayas and the Ganga Plains in five participating states. Besides extensive plantations in three type of landscapes within the riverscape, various conservation measures such as soil and water conservation, riparian wildlife management, wetland management, bioremediation and bio-filtration and supporting activities such as policy and law intervention, concurrent research, monitoring and evaluation, and mass awareness campaigns have been envisioned in the DPR. The DPR also incorporates the details of the implementation mechanism, budget provisioned for different components of the project besides allocation of budget state-wise to five implementing agencies, national partner organizations and the Nodal Ministry.

Keywords: conservation, Ganga, river, water, forestry interventions

Procedia PDF Downloads 137

Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

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Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

Procedia PDF Downloads 82

Authors: Sinead Morrison, Ann Swillen, Therese Van Amelsvoort, Samuel Chawner, Elfi Vergaelen, Michael Owen, Marianne Van Den Bree

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22q11.2 Deletion Syndrome (22q11.2DS) is caused by the deletion of approximately 60 genes on chromosome 22 and is associated with high rates of neurodevelopmental disorders such as Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD). The presentation of these disorders in 22q11.2DS is reported to be comparable to idiopathic forms and therefore presents a valuable model for understanding mechanisms of neurodevelopmental disorders. Cognitive deficits are thought to be a core feature of neurodevelopmental disorders, and possibly manifest in behavioural and emotional problems. There have been mixed findings in 22q11.2DS on whether the presence of ADHD or ASD is associated with greater cognitive deficits. Furthermore, the influence of developmental stage has never been taken into account. The aim was therefore to examine whether the presence of ADHD or ASD was associated with cognitive deficits in childhood and/or adolescence in 22q11.2DS. We conducted the largest study to date of this kind in 22q11.2DS. The same battery of tasks measuring processing speed, attention and spatial working memory were completed by 135 participants with 22q11.2DS. Wechsler IQ tests were completed, yielding Full Scale (FSIQ), Verbal (VIQ) and Performance IQ (PIQ). Age-standardised difference scores were produced for each participant. Developmental stages were defined as children (6-10 years) and adolescents (10-18 years). ADHD diagnosis was ascertained from a semi-structured interview with a parent. ASD status was ascertained from a questionnaire completed by a parent. Interaction and main effects of cognitive performance of those with or without a diagnosis of ADHD or ASD in childhood or adolescence were conducted with 2x2 ANOVA. Significant interactions were followed up with t-tests of simple effects. Adolescents with ASD displayed greater deficits in all measures (processing speed, p = 0.022; sustained attention, p = 0.016; working memory, p = 0.006) than adolescents without ASD; there was no difference between children with and without ASD. There were no significant differences on IQ measures. Both children and adolescents with ADHD displayed greater deficits on sustained attention (p = 0.002) than those without ADHD. There were no significant differences on any other measures for ADHD. Magnitude of cognitive deficit in individuals with 22q11.2DS varied by cognitive domain, developmental stage and presence of neurodevelopmental disorder. Adolescents with 22q11.2DS and ASD showed greater deficits on all measures, which suggests there may be a sensitive period in childhood to acquire these domains, or reflect increasing social and academic demands in adolescence. The finding of poorer sustained attention in children and adolescents with ADHD supports previous research and suggests a specific deficit which can be separated from processing speed and working memory. This research provides unique insights into the association of ASD and ADHD with cognitive deficits in a group at high genomic risk of neurodevelopmental disorders.

Keywords: 22q11.2 deletion syndrome, attention deficit hyperactivity disorder, autism spectrum disorder, cognitive development

Procedia PDF Downloads 135

Authors: Giorgia Carratta

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Since the beginning of mass production, plastic items have been crucial in our daily lives. Thanks to their physical and chemical properties, plastic materials have proven almost irreplaceable in a number of economic sectors such as packaging, automotive, building and construction, textile, and many others. At the same time, the disruptive consequences of plastic pollution have been progressively brought to light in all environmental compartments. The overaccumulation of plastics in the environment, and its adverse effects on habitats, wildlife, and (most likely) human health, represents a call for action to decision-makers around the globe. From a regulatory perspective, plastic production is an unprecedented challenge at all levels of governance. At the international level, the design of new legal instruments, the amendment of existing ones, and the coordination among the several relevant policy areas requires considerable effort. Under the pressure of both increasing scientific evidence and a concerned public opinion, countries seem to slowly move towards the discussion of a new international ‘plastic treaty.’ However, whether, how, and with which scopes such instrument would be adopted is still to be seen. Additionally, governments are establishing regional-basedstrategies, prone to consider the specificities of the plastic issue in a certain geographical area. Thanks to the new Circular Economy Action Plan, approved in March 2020 by the European Commission, EU countries are slowly but steadily shifting to a carbon neutral, circular economy in the attempt to reduce the pressure on natural resources and, parallelly, facilitate sustainable economic growth. In this context, the EU Plastic Strategy is promising to change the way plastic is designed, produced, used, and treated after consumption. In fact, only in the EU27 Member States, almost 26 million tons of plastic waste are generated herein every year, whose 24,9% is still destined to landfill. Positive effects of the Strategy also include a more effective protection of our environment, especially the marine one, the reduction of greenhouse gas emissions, a reduced need for imported fossil energy sources, more sustainable production and consumption patterns. As promising as it may sound, the road ahead is still long. The need to implement these measures in domestic legislations makes their outcome difficult to predict at the moment. An analysis of the current international and European Union legal framework on plastic pollution, binding, and voluntary instruments included, could serve to detect ‘blind spots’ in the current governance as well as to facilitate the development of policy interventions along the plastic value chain, where it appears more needed.

Keywords: environmental law, European union, governance, plastic pollution, sustainability

Procedia PDF Downloads 93

Authors: Siuzan Uorner

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The era of late modernity is characterized, on the one hand, by social disintegration, values of personal freedom, tolerance, and self-expression. Boundaries between the accessible and the elitist, normal and abnormal are blurring. On the other hand, traditional social institutions, such as religion (especially Russian Orthodox Church), exist, criticizing lifestyle and worldview other than conventionally structured canons. Despite the declared values and opportunities in late modern society, people's freedom is ambivalent. Personal identity and its aspects are becoming a subject of choice. Hence, combinations of identity aspects can be incompatible. Our theoretical framework is based on P. Ricoeur's concept of narrative identity and hermeneutics, E. Goffman’s theory of social stigma, self-presentation, discrepant roles and W. James lectures about varieties of religious experience. This paper aims to reconstruct ways of coping with incompatible identities of Orthodox gays (an extreme sampling of a combination of sexual orientation and religious identity in a heteronormative society). This study focuses on the discourse of Orthodox gay parishioners and ROC gay priests in Russia (sampling ‘hard to reach’ populations because of the secrecy of gay community in ROC and sensitivity of the topic itself). We conducted a qualitative research design, using in-depth personal semi-structured online-interviews. Recruiting of informants took place in 'Nuntiare et Recreare' (Russian movement of religious LGBT) page in VKontakte through the post with an invitation to participate in the research. In this work, we analyzed interview transcripts using axial coding. We chose the Grounded Theory methodology to construct a theory from empirical data and contribute to the growing body of knowledge in ways of harmonizing incompatible identities in late modern societies. The research has found that there are two types of conflicts Orthodox gays meet with: canonic contradictions (postulates of Scripture and its interpretations) and problems in social interaction, mainly with ROC priests and Orthodox parishioners. We have revealed semantic meanings of most commonly used words that appear in the narratives (words such as ‘love’, ‘sin’, ‘religion’ etc.). Finally, we have reconstructed biographical patterns of LGBT social movements’ involvement. This paper argues that all incompatibilities are harmonizing in the narrative itself. As Ricoeur has suggested, the narrative configuration allows the speaker to gather facts and events together and to compose causal relationships between them. Sexual orientation and religious identity are getting along and harmonizing in the narrative.

Keywords: gay priests, incompatible identities, narrative identity, Orthodox gays, religious identity, ROC, sexual orientation

Procedia PDF Downloads 120

Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

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Precision Agriculture has long being benefited from crop fields’ aerial imagery. This important tool has allowed identifying patterns in crop fields, generating useful information to the production management. Reflectance intensity data in different ranges from the electromagnetic spectrum may indicate presence or absence of nutrients in the soil of an area. Different relations between the different light bands may generate even more detailed information. The knowledge of the nutrients content in the soil or in the crop during its growth is a valuable asset to the farmer that seeks to optimize its yield. However, small farmers in Brazil often lack the resources to access this kind information, and, even when they do, it is not presented in a comprehensive and/or objective way. So, the challenges of implementing this technology ranges from the sampling of the imagery, using aerial platforms, building of a mosaic with the images to cover the entire crop field, extracting the reflectance information from it and analyzing its relationship with the parameters of interest, to the display of the results in a manner that the farmer may take the necessary decisions more objectively. In this work, it’s proposed an analysis of soil nutrient contents based on image processing of satellite imagery and comparing its outtakes with commercial laboratory’s chemical analysis. Also, sources of satellite imagery are compared, to assess the feasibility of using Google Earth data in this application, and the impacts of doing so, versus the application of imagery from satellites like Landsat-8 and Pleiades. Furthermore, an algorithm for building mosaics is implemented using Google Earth imagery and finally, the possibility of using unmanned aerial vehicles is analyzed. From the data obtained, some soil parameters are estimated, namely, the content of Potassium, Phosphorus, Boron, Manganese, among others. The suitability of Google Earth Imagery for this application is verified within a reasonable margin, when compared to Pleiades Satellite imagery and to the current commercial model. It is also verified that the mosaic construction method has little or no influence on the estimation results. Variability maps are created over the covered area and the impacts of the image resolution and sample time frame are discussed, allowing easy assessments of the results. The final results show that easy and cheaper remote sensing and analysis methods are possible and feasible alternatives for the small farmer, with little access to technological and/or financial resources, to make more accurate decisions about soil nutrient management.

Keywords: remote sensing, precision agriculture, mosaic, soil, nutrient content, satellite imagery, aerial imagery

Procedia PDF Downloads 159

Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

Abstract:

This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

Abstract:

Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

Abstract:

Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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