Search results for: interactions patterns

Authors: Vanessa Caroline De Barros Bonato, Bruna Lima Gomes, Luciano Freschi, Eduardo Purgatto

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The plant hormone ethylene is closely related to the metabolic changes that occur during fruit ripening, including volatile biosynthesis. Although knowledge about the biochemistry pathways that produce flavor compounds and the importance of ethylene to these processes are extensively covered, little is known about the regulation mechanisms. In addition, growing body of evidences indicates that auxin is also involved in controlling ripening. However, there is scarce information about the involvement of auxin in fruit volatile production. This study aimed to assess auxin-ethylene interactions and its influence on tomato fruit volatile profile. Fruits from tomato cultivar Micro-Tom were treated with IAA and ethylene, separately and in combination. The hormonal treatment was performed by injection (IAA) or gas exposure (ethylene) and the volatiles were extracted by Solid Phase Microextraction (SPME) and analyzed by GC-MS. Ethylene levels and color were measured by gas chromatography and colorimetry, respectively. The results indicate that the treatment with IAA (even in the presence of high concentrations of exogenous ethylene), impacted the profile of volatile compounds derived from fatty acids, amino acids, carbohydrates and isoprenoids. Ethylene is a well-known regulator of the transition from green to red color and also is implicated in the biosynthesis of characteristic volatile compounds of tomato fruit. The effects observed suggest the existence of a crosstalk between IAA and ethylene in the aroma volatile formation in the fruit. A possible interference of IAA in the ethylene sensitivity in the fruit flesh is discussed. The data suggest that auxin plays an important role in the volatile synthesis in the tomato fruit and introduce a new level of complexity in the regulation of the fruit aroma formation during ripening.

Keywords: aroma compounds, fruit ripening, fruit quality, phytohormones

Procedia PDF Downloads 392

Authors: Agung A. Ginanjar, Lilitasari, Indra Prasetya, Rizal R. Hanif, Yusrina Rismandini, Atina Hussaana, Nurita P. Sari

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Hyperlipidemia is an increase of lipids and cholesterol in the blood that causes the formation of atherosklerosis. The recent pharmacological therapy nowadays is statin. Many Indonesian people use of medicinal plants. There are several medical plants that people always use to cure hyperlipidemia such as bulbs onion sabrang, areca nuts, and seed of fenugreek. Most people often use a combination therapy of conventional medicine and herbs to achieve the desired therapeutic effect of combination therapy. The use of combination therapy might cause the interaction of pharmacodynamic from those medicines so that it influences the pharmacological effect of one of medicine. The aim of this study is to know the interaction of simvastatin and a cholesterol-lowering herb seen in rats pharmacodynamic simvastatin phase. This research used post-test only controlled group design. Analysis of statistical data normality and homogenity were tested by Kolmogorov Smirnov. The ANOVA test is used when the data is obtained homogeneous but if it is found that the data are not homogeneous then kruskal-wallis test is used. Normal (63.196 mg/dl), negative (70.604 mg/dl), positive (62.512 mg/dl), areca nuts (56.564 mg/dl), fenugreek seed (47.538 ,g/dl), onion sabrang (62.312 mg/dl). The results prove that the combination of herbs and simvastatin did not have a significant difference (P>0,05). The conclusion of this study is that the combination of simvastatin and a cholesterol-lowering herb can cause some pharmacodynamic interactions such as a synergistic effect, antagonist, and a powerful additive, so that combination therapy is not more effective than single simvastatin therapy. The use of the combination therapy is not given in the same time. It would be better if there are some period of time when the combination therapy is applied.

Keywords: onion bulb sabrang, areca nuts, seed of fenugreek, interaction medicine, hyperlipidemia

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Authors: Hadas Sopher, Davide Schaumann, Yehuda E. Kalay

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This paper addresses the shortcomings of architectural computation tools in representing human behavior in built environments, prior to construction and occupancy of those environments. Evaluating whether a design fits the needs of its future users is currently done solely post construction, or is based on the knowledge and intuition of the designer. This issue is of high importance when designing complex buildings such as hospitals, where the quality of treatment as well as patient and staff satisfaction are of major concern. Existing computational pre-occupancy human behavior evaluation methods are geared mainly to test ergonomic issues, such as wheelchair accessibility, emergency egress, etc. As such, they rely on Agent Based Modeling (ABM) techniques, which emphasize the individual user. Yet we know that most human activities are social, and involve a number of actors working together, which ABM methods cannot handle. Therefore, we present an event-based model that manages the interaction between multiple Actors, Spaces, and Activities, to describe dynamically how people use spaces. This approach requires expanding the computational representation of Actors beyond their physical description, to include psychological, social, cultural, and other parameters. The model presented in this paper includes cognitive abilities and rules that describe the response of actors to their physical and social surroundings, based on the actors’ internal status. The model has been applied in a simulation of hospital wards, and showed adaptability to a wide variety of situated behaviors and interactions.

Keywords: agent based modeling, architectural design evaluation, event modeling, human behavior simulation, spatial cognition

Procedia PDF Downloads 257

Authors: Athdath Waduge Susantha Janaka Kumara, Xiefei Zhi, Zin Mie Mie Sein

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Understanding the air temperature variability is crucially important for disaster risk reduction and management. In this study, we used 15 synoptic meteorological stations to assess the spatiotemporal variability of air temperature over Sri Lanka during 1972–2021. The empirical orthogonal function (EOF), Principal component analysis (PCA), Mann-Kendall test, power spectrum analysis and correlation coefficient analysis were used to investigate the long-term trends of air temperature and their possible relation to sea surface temperature (SST) over the region. The results indicate that an increasing trend in air temperature was observed with the abrupt climate change noted in the year 1994. The spatial distribution of EOF1 (63.5%) shows the positive and negative loading dipole patterns from south to northeast, while EOF2 (23.4%) explains warmer (colder) in some parts of central (south and east) areas. The power spectrum of PC1 (PC2) indicates that there is a significant period of 3-4 years (quasi-2 years). Moreover, Indian Ocean Dipole (IOD) provides a strong positive correlation with the air temperature of Sri Lanka, while the EL Nino Southern Oscillation (ENSO) presents a weak negative correlation. Therefore, IOD events led to higher temperatures in the region. This study’s findings can help disaster risk reduction and management in the country.

Keywords: air temperature, interannaul variability, ENSO, IOD

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Authors: Brian Wartell, Michel Boufadel

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Contaminants such as polycyclic aromatic hydrocarbons (PAHs) are compounds present in crude and petroleum oils and are known to be toxic and often carcinogenic. Therefore, a major effort is placed on tracking their subsurface soil concentrations following an oil spill. The PAHs can persist for years in the subsurface especially if there is a lack of oxygen. Both aerobic and anaerobic biodegradation of PAHs encounter the difficulties of both nutrient transport and bioavailability (proximal access) to the organisms of the contaminants. A technology, known as electrokinetics (EK or EK-BIO for ‘electrokinetic bioremediation’) has been found to transport efficiently nutrients or other chemicals in the subsurface. Experiments were conducted to demonstrate migration patterns in both sands and clay for both ionic and nonionic compounds and aerobic biodegradation studies were conducted with soil spiked with Polycyclic Aromatic Hydrocarbons yielding interesting results. In one set of experiment, Self-designed electrokinetic setups were constructed to examine the differences in electromigration and electroosmotic rates. Anionic and non-ionic dyes were used to visualize these phenomena, respectively. In another experiment, a silt-clay soil was spiked with three low-molecular-weight compounds (fluorene, phenanthrene, fluoranthene) and placed within self-designed electrokinetic setups and monitored for aerobic degradation. Plans for additional studies are in progress including the transport of peroxide through anaerobic sands.

Keywords: bioavailability, bioremediation, electrokinetics, subsurface transport

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Irena Smetackova

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The important part of school mathematics are word problems which represent the connection between school knowledge and life reality. To find the reasons why students consider word problems to be difficult, it is necessary to take into consideration the motivational settings, besides mathematical knowledge and reading skills. Our goal is to identify whether the familiar or unfamiliar context of math word problem influences solving success rate and if so, whether the reasons are motivational or cognitive. For this purpose, we conducted three steps study in group of fifty pupils 9-10 years old. In the first step, we asked pupils to create ‘the best’ word problems for entered numerical formula. The set of 19 word problems with different contexts were selected. In the second step, pupils were asked to evaluate (without solving) how they like each item and how easy it is for them. The 6 word problems with low preference and low estimated success rate were selected and combined with other 6 problems with high preference and success rate. In the third step, the same pupils were asked to solve the word problems. The analysis showed that pupils attitudes and solving toward word problems varied by the context. The strong gender patterns both in preferred contexts and in estimated success rates were identified however the real success rate did not differ so strongly. The success gap between word problems with and without preferred contexts were stronger than the gap between problems with and without real experience with the context. The hypothesis that motivational factors are more important than cognitive factors was confirmed.

Keywords: mathematics, context of reality, motivation, cognition, word problems

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Authors: Surabhi Pandey, Pavuluri Srinivasa Rao

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Extrusion processing is a high-temperature short time (HTST) treatment which can improve protein quality and digestibility together with retaining active nutrients. In-vitro protein digestibility of plant protein-based foods is generally enhanced by extrusion. The current study aimed to investigate the effect of extrusion cooking on in-vitro protein digestibility (IVPD) and conformational modification of protein in green banana flour extrudates. Green banana flour was extruded through a co-rotating twin-screw extruder varying the moisture content, barrel temperature, screw speed in the range of 10-20 %, 60-80 °C, 200-300 rpm, respectively, at constant feed rate. Response surface methodology was used to optimise the result for IVPD. Fourier-transform infrared spectroscopy (FTIR) analysis provided a convenient and powerful means to monitor interactions and changes in functional and conformational properties of extrudates. Results showed that protein digestibility was highest in extrudate produced at 80°C, 250 rpm and 15% feed moisture. FTIR analysis was done for the optimised sample having highest IVPD. FTIR analysis showed that there were no changes in primary structure of protein while the secondary protein structure changed. In order to explain this behaviour, infrared spectroscopy analysis was carried out, mainly in the amide I and II regions. Moreover, curve fitting analysis showed the conformational changes produced in the flour due to protein denaturation. The quantitative analysis of the changes in the amide I and II regions provided information about the modifications produced in banana flour extrudates.

Keywords: extrusion, FTIR, protein conformation, raw banana flour, SDS-PAGE method

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Authors: Bindu S., Malavika Anakkathil Anil, Jayashree S. Bhat

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The dyadic interaction between the parent and child during story narration facilitates the emergence of early literacy skills. Early shared reading experiences positively predict better reading and language outcomes in children who experience rich communicative and effective interactions during shared book reading. However, research is yet to systematically explore mother’s perspective towards story narration and how employment may influence their perspectives. The study analysed the perspectives of employed and unemployed mothers of typically developing children between the age ranges of 2 to 5 years through a questionnaire which covered domains on story narration exposure and parental attitudes & beliefs. The results indicate no statistical difference between employed mothers (M=8.5, SD=3.4) and unemployed mothers (M=10.1, SD=1.06). Whereas, post-hoc comparisons using the scheffe test, revealed a significant difference in scores. An increasing score was obtained as the age of the child increased. This change could be attributed due to the integration of children in preschools which could have contributed to the change of perception towards story narration. Older children’s mother perceive story narration to be an important part of their curriculum, which could facilitate rich vocabulary and language output. Younger children’s parents are however not realising the significance of story narration and its impact on the emergent literacy skills. Parent-child interaction is a significant contributor to a healthy social and cultural development. The study emphasises on the need of mothers to engage in preliteracy based activities which contribute to better academic performance in later stages.

Keywords: early literacy skill, employment, language development, mother’s perspective, story narration

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Authors: Waranya Pongpaiboon, Warangkana Srichamnong, Supat Chaiyakul

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Enzymatic modification of rice flour can produce highly functional derivatives use in food industries. This study aimed to evaluate the physical properties and resistant starch content of rice flour residues hydrolyzed by α-amylase. Rice flour hydrolyzed by α-amylase (60 and 300 u/g) for 1, 24 and 48 hours were investigated. Increasing enzyme concentration and hydrolysis time resulted in decreased rice flour residue’s lightness (L*) but increased redness (a*) and yellowness (b*) of rice flour residues. The resistant starch content and peak viscosity increased when hydrolysis time increased. Pasting temperature, trough viscosity, breakdown, final viscosity, setback and peak time of the hydrolyzed flours were not significantly different (p>0.05). The morphology of native flour was smooth without observable pores and polygonal with sharp angles and edges. However, after hydrolysis, granules with a slightly rough and porous surface were observed and a rough and porous surface was increased with increasing hydrolyzed time. The X-ray diffraction patterns of native flour showed A-type configuration, which hydrolyzed flour showed almost 0% crystallinity indicated that both amorphous and crystalline structures of starch were simultaneously hydrolyzed by α-amylase.

Keywords: α-Amylase, enzymatic hydrolysis, pasting properties, resistant starch

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Authors: Nisar Alungal Chungath

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“No human being is illegal" has become a dictum strongly upheld in the context of global immigration and migration, highlighting the ethical and moral dimensions of how societies and governments treat individuals and communities who have crossed political borders or are living in a country without legal authorization. It seeks to shift the focus from categorizing human beings as illegal immigrants to recognizing their inherent human rights and the complexities of their circumstances. As a complex social phenomenon, law has been a crucial instrument in shaping, regulating and governing human societies and vice versa. The law has now become a humongous political project of the modern majoritarian regimes to democratically illegitimize and illegalize the unpopular sections and minorities. Drawing from the theoretical frameworks of dialectics, the paper explores the philosophical underpinnings of the historical evolution and dynamic nature of modern law. The paper employs a phenomenological approach to analyze the dialectical relations between individuals, societies, and legal systems, aiming to shed light on the ethical and political implications of these interactions. By examining the historical essence of law, its relationship with social and cultural norms, and the role of power dynamics, this article argues for constantly maintaining the dialectics of law—the dynamic interplay between legal norms, social practices, cultural values, and historical contexts through a philosophical and phenomenological lens, in order to bridge the gap between universal principles and particular contexts. The paper will shed light to the dialectics of the law in the context of instances of the legal persecutions of the modern secular democracies such as Citizenship Amendment Act-2019, India.

Keywords: phenomenology, dialectic, modern law, politics, resistance, margins

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Authors: Erina Wulansari, Bambang Soemardiono, Ispurwono Soemarno

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Designing sustainable tourism area is defined as an attempt to design an area, that brings the natural environmental conditions as components are available with a wealth of social conditions and the conservation of natural and cultural heritage. To understanding tourism area in this study is not only focus on the location of the tourist object, but rather to a tourist attraction around the area, tourism objects such as the existence of residential area (settlement), a commercial area, public service area, and the natural environmental area. The principle of success in designing a sustainable tourism area is able to integrate and balance between the limited space and the variety of activities that’s always continuously to growth up. The limited space in this area of tourism needs to be managed properly to minimize the damage of environmental as a result of tourism activities hue. This research aims to identify space in this area of tourism through land suitability approach as an effort to create a sustainable design, especially in terms of ecological. This study will be used several analytical techniques to achieve the research objectives as superimposing analysis with GIS 9.3 software and Analysis Hierarchy Process. Expected outcomes are in the form of classification and criteria of usable space in designing embodiment tourism area. In addition, this study can provide input to the order of settlement patterns as part of the environment in the area of sustainable tourism.

Keywords: sustainable tourism area, land suitability, limited space, environment, criteria

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Authors: Laura Jenkins, Tim Eschle, Joanne Ciafone, Colin Hamilton

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An original working memory model suggested the separation of visual and verbal systems in working memory architecture, in which only visual working memory components were used during visual working memory tasks. It was later suggested that the visuo spatial sketch pad was the only memory component at use during visual working memory tasks, and components such as the phonological loop were not considered. In more recent years, a contrasting approach has been developed with the use of an executive resource to incorporate both visual and verbal representations in visual working memory paradigms. This was supported using research demonstrating the use of verbal representations and an executive resource in a visual matrix patterns task. The aim of the current research is to investigate the working memory architecture during both a quantitative and a qualitative visual working memory task. A dual task method will be used. Three secondary tasks will be used which are designed to hit specific components within the working memory architecture – Dynamic Visual Noise (visual components), Visual Attention (spatial components) and Verbal Attention (verbal components). A comparison of the visual working memory tasks will be made to discover if verbal representations are at use, as the previous literature suggested. This direct comparison has not been made so far in the literature. Considerations will be made as to whether a domain specific approach should be employed when discussing visual working memory tasks, or whether a more domain general approach could be used instead.

Keywords: semantic organisation, visual memory, change detection

Procedia PDF Downloads 591

Authors: M. Sreedhar Babu, Vishal Garg, S. B. Akella, Shibu Clement, N. K. S Rajan

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Producer gas is a biomass derived gaseous fuel which is extensively used in internal combustion engines for power generation application. Unlike the conventional hydrocarbon fuels (Gasoline and Natural gas), the combustion properties of producer gas fuel are much different. Therefore, setting of optimal spark time for efficient engine operation is required. Owing to the fluctuating tendency of producer gas composition during gasification process, the heat release patterns (dictating the power output and emissions) obtained are quite different from conventional fuels. It was found that, valve lift timing is yet another factor which influences the burn rate of producer gas fuel, and thus, the heat release rate of the engine. Therefore, the present study was motivated to estimate the influence of valve lift timing analytically (Wiebe model) on the burn rate of producer gas through curve fitting against experimentally obtained mass fraction burn curves of several producer gas compositions. Furthermore, Wiebe models are widely used in zero-dimensional codes for engine parametric studies and are quite popular. This study also addresses the influence of hydrogen and methane concentration of producer gas on combustion trends, which are known to cause dynamics in engine combustion.

Keywords: combustion duration (CD), crank angle (CA), mass fraction burnt (MFB), producer sas (PG), Wiebe Combustion Model (WCM), wide open throttle (WOT)

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Authors: Hamilton V. Niculescu

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This paper discusses findings relating to people's engagement with mobile communication technologies and remote automated systems. This interdisciplinary study employs a constructivist grounded theory methodology, with qualitative data that was generated following in-depth semi-structured interviews with 18 people living in Ireland being corroborated with participants' observations and quantitative data. Additional data was collected following participants' remote interaction with six custom-built automated enclosures, located at six different sites around Dublin, Republic of Ireland. This paper argues that ownership and education play a vital role in people engaging with and adoption of new technologies. Analysis of participants' behavior and attitude towards Information Communication Technologies (ICT) suggests that innovations do not always improve peoples' social inclusion. Technological innovations are sometimes perceived as destroying communities and create a dysfunctional society. Moreover, the findings indicate that a lack of public information and support from Irish governmental institutions, as well as limited off-the-shelves availability, has led to low trust and adoption of renewable technologies. A limited variation in participants' behavior and interaction patterns with technologies was observed during the study. This suggests that people will eventually adopt new technologies according to their needs and experience, even though they initially rejected the idea of changing their lifestyle.

Keywords: automation, communication, ICT, renewables

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Authors: Nancy Bartekian, Kaelan Vazquez, Christine Reyna

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Immigrants coming into the United States of America may justify the American system (political, economic, healthcare, criminal justice) and see it as functional. This may be explained because they may come from countries that are even more unstable than the U.S. and/or come here to benefit from the promise of the “American dream” -a narrative that they might be more likely to believe in if they were willing to undergo the costly and sometimes dangerous process to immigrate. Conversely, native-born Americans, as well as immigrants who may have lived in America for a longer period of time, would have more experiences with the various broken systems in America that are dysfunctional, fail to provide adequate services equitably, and/or are steeped in systemic racism and other biases that disadvantage lower-status groups. Thus, our research expects that system justification would decrease, and condemnation would increase with more time spent in the U.S. for immigrant groups. We predict that a) those not born in the U.S. will be more likely to justify the system, b) they will also be less likely to condemn the system, and c) the longer an immigrant has been in the U.S. the less likely they will to justify, and more they will to condemn the system. We will use a mixed-model multivariate analysis of covariance (MANCOVA) and control for race, income, and education. We will also run linear regression models to test if there is a relationship between the length of time in the United States and a decrease in system justification, and length of time and an increase in system condemnation for those not born in the U.S. We will also conduct exploratory analyses to see if the predicted patterns are more likely within certain systems over other systems (political, economic, healthcare, criminal justice).

Keywords: immigration, system justification, system condemnation, system qualification

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Authors: M. Kobylanski, D. Buskulic, P.-H. Duron, D. Revuz, F. Ruggieri, E. Sandier, C. Tijus

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In order to design a cooperative e-learning platform, we observed teams of Teacher [T], Computer Scientist [CS] and exerciser's programmer-designer [ED] cooperating for the conception of a self-correcting exercise, but without the use of such a device in order to catch the kind of interactions a useful platform might provide. To do so, we first run a task analysis on how T, CS and ED should be cooperating in order to achieve, at best, the task of creating and implementing self-directed, self-paced, repeatable self-correcting exercises (RSE) in the context of open educational resources. The formalization of the whole process was based on the “objectives, activities and evaluations” theory of educational task analysis. Second, using the resulting frame as a “how-to-do it” guide, we run a series of three contrasted Hackathon of RSE-production to collect data about the cooperative process that could be later used to design the collaborative e-learning platform. Third, we used two complementary methods to collect, to code and to analyze the adequate survey data: the directional flow of interaction among T-CS-ED experts holding a functional role, and the Means-End Problem Solving analysis. Fourth, we listed the set of derived recommendations useful for the design of the exerciser as a cooperative e-learning platform. Final recommendations underline the necessity of building (i) an ecosystem that allows to sustain teams of T-CS-ED experts, (ii) a data safety platform although offering accessibility and open discussion about the production of exercises with their resources and (iii) a good architecture allowing the inheritance of parts of the coding of any exercise already in the data base as well as fast implementation of new kinds of exercises along with their associated learning activities.

Keywords: editorialization, open educational resources, pedagogical alignment, produsage, repeatable self-correcting exercises, team roles

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Authors: Z. Jamalzadeh, A. Niaei, H. Erfannia

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Due to developing industries, the emission of pollutants such as NOx, SOx, and CO2 are rapidly increased. Generally, NOx is attributed to the mono nitrogen oxides of NO and NO2 that is one of the most important atmospheric contaminants. Hence, controlling the emission of nitrogen oxides is environmentally urgent. Selective catalytic reduction of NOx is one of the most common techniques for NOx removal in which zeolites have wide application due to their high performance. In zeolitic processes, the catalytic reaction occurs mostly in the pores. Therefore, investigation of the adsorption phenomena of the molecules in order to gain an insight and understand the catalytic cycle is of important. Hence, in current study, benefiting from molecular simulations, the adsorption phenomena in the nanocatalysts of SCR of NOx process was investigated in order to get a good insight of the catalysts’ behavior. The effect of cation addition to the support in the catalysts’ behavior through adsorption step was explored by Mont Carlo (MC) using Materials Studio Package. Simulation time of 1 Ns accompanying 1 fs time step, COMPASS27 Force Field and the cut off radios of 12.5 Ȧ was applied for performed runs. It was observed that the adsorption capacity increases in the presence of cations. The sorption isotherms demonstrated the behavior of type I isotherm categories and sorption capacity diminished with increase in temperature whereas an increase was observed at high pressures. Besides, NO sorption showed higher sorption capacity than NH3 in H–ZSM5. In this respect, the energy distributions signified that the molecules could adsorb in just one sorption site at the catalyst and the sorption energy of NO was stronger than the NH3 in H-ZSM5. Furthermore, the isosteric heat of sorption data showed nearly same values for the molecules; however, it indicated stronger interactions of NO molecules with H-ZSM5 zeolite compared to the isosteric heat of NH3 which was low in value.

Keywords: Monte Carlo simulation, adsorption, NOx, ZSM5

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Authors: Mosupi Ratshaa

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Despite years of diligent study, sedimentation is still undoubtedly the most severe technical problem faced by the dam industry. The problem of sedimentation build-up and its removal should be the focus as an approach to remedy this. The world's reservoirs lose about 1% of their storage capacity yearly to sedimentation, what this means is that 1% of water that could be stored is lost the world-over. The increase in population means that the need for water also increases and, therefore, the loss due to sedimentation is of great concern especially to the conservation of water. When it comes to reservoir sedimentation, the thought of water conservation comes with soil conservation since this increasing sediment that takes the volume meant for water is being lost from dry land. For this reason, reservoir sediment control is focused on reducing sediment entering the reservoir and reducing sediment within the reservoir. There are many problems with sediment control such as the difficulty to predict settling patterns, inability to greatly reduce the sediment volume entering the river flow which increases the reservoirs trap efficiency just to mention a few. Notably reservoirs are habitats for flora and fauna, the process of removing sediment from these reservoirs damages this ecosystem so there is an ethical point to be considered in this section. This paper looks at the methods used to control the sedimentation of reservoirs and their effects to the ecosystem in the aim of reducing water losses due to sedimentation. Various control measures which reduce sediment entering the reservoir such as Sabo dams or Check dams along with measures which emphasize the reduction in built-up settled sediment such as flushing will be reviewed all with the prospect of conservation.

Keywords: sedimentation, conservation, ecosystem, flushing

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Mukunda Upadhyay, Rakesh Mishra, Rajni Singh

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This paper is an attempt to understand the abstract concept of space, citizenship and migration in the north-eastern region. In the twentieth century, researchers and thinkers related citizenship and migration on national models. The national models of jus sulis and jus sangunis provide scope of space and rights to only those who are either born in the territory or either share the common descent. Space ensures rights and citizenship ensures space and for many migrants, citizenship is the ultimate goal in the host country. Migrants with the intention of settling down in the destination region, begin to adapt and assimilate in their new homes. In many cases, migrants may also retain the culture and values of the place of origin. In such cases the difference in the degree of retention and assimilation may determine the chances of conflict between the host society and migrants. Such conflicts are fueled by political aspirations of few individuals on both the sides. The North-Eastern part of India is a mixed community with many linguistic and religious groups sharing a common Geo-political space. Every community has its own unique history, culture and identity. Since the last half of the nineteenth century, this region has been experiencing both internal migration from other states and immigration from the neighboring countries which has resulted in the interactions of various cultures and ethnicities. With the span of time, migration has taken bitter form with problems concentrated around acquiring rights through space and citizenship. Political tensions resulted by host hostility and migrants resistance has ruined the social order in few areas. In order to resolve these issues in this area proper intervention has to be carried out by the involvement of the National and International community.

Keywords: space, citizenship, assimilation, migration, rights

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Authors: Shih-Fang Lo, Tzu-Wei Guo, Chih-Hsuan Lee

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Tropical fisheries are vulnerable to the physical and biogeochemical oceanic changes associated with climate change. Warmer temperatures and extreme weather have beendamaging the abundance and growth patterns of aquatic organisms. In recent year, the shrinking of fish stock and labor shortage have increased the threat to global aquacultural production. Thus, building a climate-resilient and sustainable mechanism becomes an urgent, important task for global citizens. To tackle the problem, Taiwanese fishermen applies the artificial intelligence (AI) technology. In brief, the AI system (1) measures real-time water quality and chemical parameters infish ponds; (2) monitors fish stock through segmentation, detection, and classification; and (3) implements fishermen’sprevious experiences, perceptions, and real-life practices. Applying this system can stabilize the aquacultural production and potentially increase the labor force. Furthermore, this AI technology can build up a more resilient and sustainable system for the fishermen so that they can mitigate the influence of extreme weather while maintaining or even increasing their aquacultural production. In the future, when the AI system collected and analyzed more and more data, it can be applied to different regions of the world or even adapt to the future technological or societal changes, continuously providing the most relevant and useful information for fishermen in the world.

Keywords: aquaculture, artificial intelligence (AI), real-time system, sustainable fishery

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Authors: Konstantinos Pikos, Dimitrios Kaimaris

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Although designing building blocks is a procedure used by many planners around the world, there isn’t an automated tool that will help planners and designers achieve their goals with lesser effort. The difficulty of the subject lies in the repeating process of manually drawing lines, while not only it is mandatory to maintain the desirable offset but to also achieve a lesser impact to the existing building stock. In this paper, using Geographical Information Systems (GIS) and the Python programming language, an automated tool integrated into ArcGIS PRO, is being presented. Despite its simplistic enviroment and the lack of specialized building legislation due to the complex state of the field, a planner who is aware of such technical information can use the tool to draw an initial approach of the final building blocks in an area with pre-existing buildings in an attempt to organize the usually sprawling suburbs of a city or any continuously developing area. The tool uses ESRI’s ArcPy library to handle the spatial data, while interactions with the user is made throught Tkinter. The main process consists of a modification of building edgescoordinates, using NumPy library, in an effort to draw the line of best fit, so the user can get the optimal results per block’s side. Finally, after the tool runs successfully, a table of primary planning information is shown, such as the area of the building block and its coverage rate. Regardless of the primary stage of the tool’s development, it is a solid base where potential planners with programming skills could invest, so they can make the tool adapt to their individual needs. An example of the entire procedure in a test area is provided, highlighting both the strengths and weaknesses of the final results.

Keywords: arcPy, GIS, python, building blocks

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Almas Rajguru, Archana Kamath, Rachana Singh

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The study aims to determine the depositional facies, high-resolution sequence stratigraphy, and diagenetic processes of Early Oligocene carbonates in N & N-W of Heera, Mumbai Offshore. Foraminiferal assemblage and microfacies from cores of Well A, B, C, D and E are indicative of facies association related to four depositional environments, i.e., restricted inner lagoons-tidal flats, shallow open lagoons, high energy carbonate bars-shoal complex and deeper mid-ramps of a westerly dipping homoclinal carbonate ramp. Two high-frequency (4th Order) depositional sequences bounded by sequence boundary, DS1 and DS2, displaying hierarchical stacking patterns, are identified and correlated across wells. Vadose zone diagenesis effect during short diastem/ subaerial exposure has rendered good porosity due to dissolution in HST carbonates and occasionally affected underlying TST sediments (Well D, C and E). On mapping and correlating the sequences, the presence of thin carbonate bars that can be potential reservoirs are envisaged along NW-SE direction, towards north and south of Wells E, D and C. A more pronounced development of these bars in the same orientation can be anticipated towards the west of the study area.

Keywords: sequence stratigraphy, depositional facies, diagenesis petrography, early Oligocene, Mumbai offshore

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Authors: Oshin Anand, Atanu Rakshit

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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

Procedia PDF Downloads 385

Authors: R. S. Yadav, J. Havlica, I. Kuřitka, Z. Kozakova, J. Masilko, L. Kalina, M. Hajdúchová, V. Enev, J. Wasserbauer

Abstract:

Nickel spinel ferrite NiFe2O4 nanoparticles with different particle size at different annealing temperature were synthesized using the starch-assisted sol-gel auto-combustion method. The synthesized nanoparticles were characterized by conventional powder X-ray diffraction (XRD) spectroscopy, Raman Spectroscopy, Fourier Transform Infrared Spectroscopy, Field-Emission Scanning Electron Microscopy, X-ray Photoelectron Spectroscopy and Vibrating Sample Magnetometer. The XRD patterns confirmed the formation of NiFe2O4 spinel ferrite nanoparticles. Field-Emission Scanning Electron Microscopy revealed that particles are of spherical morphology with particle size 5-20 nm at lower annealing temperature. An infrared spectroscopy study showed the presence of two principal absorption bands in the frequency range around 525 cm-1 (ν1) and around 340 cm-1 (ν2); which indicate the presence of tetrahedral and octahedral group complexes, respectively, within the spinel ferrite nanoparticles. Raman spectroscopy study also indicated the change in octahedral and tetrahedral site related Raman modes in nickel ferrite nanoparticles with change of particle size. This change in magnetic behavior with change of particle size of NiFe2O4 nanoparticles was observed.

Keywords: nickel ferrite, nanoparticles, magnetic property, NiFe2O4

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Authors: Vagolu S. Krishna, Shan Zheng, Estharla M. Rekha, Luke W. Guddat, Dharmarajan Sriram

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Tuberculosis (TB) remains a major threat to human health. This due to the fact that current drug treatments are less than optimal as well as the rising occurrence of multi drug-resistant and extensively drug-resistant strains of the etiological agent, Mycobacterium tuberculosis (Mt). Given the wide-spread significance of this disease, we have undertaken a design and evaluation program to discover new anti-TB drug leads. Here, our attention is focused on ketol-acid reductoisomerase (KARI), the second enzyme in the branched-chain amino acid biosynthesis pathway. Importantly, this enzyme is present in bacteria but not in humans, making it an attractive proposition for drug discovery. In the present work, we used high-throughput virtual screening to identify seventeen potential inhibitors of KARI using the Birla Institute of Technology and Science in-house database. Compounds were selected based on high docking scores, which were assigned as the result of favourable interactions between the compound and the active site of KARI. The Ki values for two leads, compounds 14 and 16 are 3.71 and 3.06 µM, respectively for Mt KARI. To assess the mode of binding, 100 ns molecular dynamics simulations for these two compounds in association with Mt KARI were performed and showed that the complex was stable with an average RMSD of less than 2.5 Å for all atoms. Compound 16 showed an MIC of 2.06 ± 0.91 µM and a 1.9 fold logarithmic reduction in the growth of Mt in an infected macrophage model. The two compounds exhibited low toxicity against murine macrophage RAW 264.7 cell lines. Thus, both compounds are promising candidates for development as an anti-TB drug leads.

Keywords: ketol-acid reductoisomerase, macrophage, molecular docking and dynamics, tuberculosis

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Authors: Naoki Yamamoto, Hidenobu Ozaki, Taiichiro Ookawa, Youming Liu, Kazunori Okada, Aiping Zheng

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Rice sheath blight is one of the destructive fungal diseases in rice. We have thought that rice sheath blight resistance is a polygenic trait. Host-pathogen interactions and secondary metabolites such as lignin and phytoalexins are likely to be involved in defense against R. solani. However, to our knowledge, it is still unknown how sheath blight resistance can be enhanced in rice breeding. To seek for an alternative genetic factor that contribute to sheath blight resistance, we mined relevant allelic variations from rice core collections created in Japan. Based on disease lesion length on detached leaf sheath, we selected 30 varieties of the top tail-end and the bottom tail-end, respectively, from the core collections to perform genome-wide association mapping. Re-sequencing reads for these varieties were used for calling single nucleotide polymorphisms among the 60 varieties to create a SNP panel, which contained 1,137,131 homozygous variant sites after filitering. Association mapping highlighted a locus on the long arm of chromosome 11, which is co-localized with three sheath blight QTLs, qShB11-2-TX, qShB11, and qSBR-11-2. Based on the localization of the trait-associated alleles, we identified an ankyryn repeat-containing protein gene (ANK-M) as an uncharacterized candidate factor for rice sheath blight resistance. Allelic distributions for ANK-M in the whole rice population supported the reliability of trait-allele associations. Gene expression characteristics were checked to evaluiate the functionality of ANK-M. Since an ANK-M homolog (OsPIANK1) in rice seems a basal defense regulator against rice blast and bacterial leaf blight, ANK-M may also play a role in the rice immune system.

Keywords: allele mining, GWAS, QTL, rice sheath blight

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Authors: Gaurav Kumar Sinha

Abstract:

The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

Procedia PDF Downloads 29