Search results for: neural interface

Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

Procedia PDF Downloads 187

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 81

Authors: Benjamin Bressolette, S´ebastien Denjean, Vincent Roussarie, Mitsuko Aramaki, Sølvi Ystad, Richard Kronland-Martinet

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New sensors and technologies – such as microphones, touchscreens or infrared sensors – are currently making their appearance in the automotive sector, introducing new kinds of Human-Machine Interfaces (HMIs). The interactions with such tools might be cognitively expensive, thus unsuitable for driving tasks. It could for instance be dangerous to use touchscreens with a visual feedback while driving, as it distracts the driver’s visual attention away from the road. Furthermore, new technologies in car cockpits modify the interactions of the users with the central system. In particular, touchscreens are preferred to arrays of buttons for space improvement and design purposes. However, the buttons’ tactile feedback is no more available to the driver, which makes such interfaces more difficult to manipulate while driving. Gestures combined with an auditory feedback might therefore constitute an interesting alternative to interact with the HMI. Indeed, gestures can be performed without vision, which means that the driver’s visual attention can be totally dedicated to the driving task. In fact, the auditory feedback can both inform the driver with respect to the task performed on the interface and on the performed gesture, which might constitute a possible solution to the lack of tactile information. As audition is a relatively unused sense in automotive contexts, gesture sonification can contribute to reducing the cognitive load thanks to the proposed multisensory exploitation. Our approach consists in using a virtual object (VO) to sonify the consequences of the gesture rather than the gesture itself. This approach is motivated by an ecological point of view: Gestures do not make sound, but their consequences do. In this experiment, the aim was to identify efficient sound strategies, to transmit dynamic information of VOs to users through sound. The swipe gesture was chosen for this purpose, as it is commonly used in current and new interfaces. We chose two VO parameters to sonify, the hand-VO distance and the VO velocity. Two kinds of sound parameters can be chosen to sonify the VO behavior: Spectral or temporal parameters. Pitch and brightness were tested as spectral parameters, and amplitude modulation as a temporal parameter. Performances showed a positive effect of sound compared to a no-sound situation, revealing the usefulness of sounds to accomplish the task.

Keywords: auditory feedback, gesture sonification, sound perception, virtual object

Procedia PDF Downloads 302

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 71

Authors: Gopala Krishna Darbha

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Microplastics (MPs) are secondary fragments of large-sized plastic debris released into the environment and fall in the size range of less than 5 mm. Though reports indicate the abundance of MPs in both riverine and soil environments, their fate is still not completely understood due to the complexity of natural conditions. Mineral particles are ubiquitous in the rivers and may play a vital role in accumulating MPs to the riverbed, thus affecting the benthic life and posing a threat to the river's health. Apart, the chemistry (pH, ionic strength, humics) at the interface can be very prominent. The MPs can also act as potential vectors to transport other contaminants in the environment causing secondary water pollution. The present study focuses on understanding the interaction of MPs with weathering sequence of minerals (feldspar, kaolinite and gibbsite) under batch mode under relevant environmental and natural conditions. Simultaneously, we performed stability studies and transport (column) experiments to understand the mobility of MPs under varying soil solutions (SS) chemistry and the influence of contaminants (CuO nanoparticles). Results showed that the charge and morphology of the gibbsite played an significant role in sorption of NPs (108.1 mg/g) compared to feldspar (7.7 mg/g) and kaolinite (11.9 mg/g). The Fourier transform infrared spectroscopy data supports the complexation of NPs with gibbsite particles via hydrogen bonding. In case of feldspar and kaolinite, a weak interaction with NPs was observed which can be due to electrostatic repulsions and low surface area to volume ration of the mineral particles. The study highlights the enhanced mobility in presence of feldspar and kaolinite while gibbsite rich zones can cause entrapment of NPs accumulating in the riverbeds. In the case of soils, in the absence of MPs, a very high aggregation of CuO NPs observed in SS extracted from black, lateritic, and red soils, which can be correlated with ionic strength (IS) and type of ionic species. The sedimentation rate (Ksed(1/h)) for CuO NPs was >0.5 h−1 in the case of these SS. Interestingly, the stability and sedimentation behavior of CuO NPs varied significantly in the presence of MPs. The Ksed for CuO NPs decreased to half and found <0.25 h−1 in the presence of MPs in all SS. C/C0 values in breakthrough curves increased drastically (black < alluvial < laterite < red) in the presence of MPs. Results suggest that the release of MPs in the terrestrial ecosystem is a potential threat leading to increased mobility of metal nanoparticles in the environment.

Keywords: microplastics, minerals, sorption, soils

Procedia PDF Downloads 90

Authors: Godwin Dennison, C. E. Boulind, O. Gould, B. de Lacy Costello, J. Allison, P. White, P. Ewings, A. Wicaksono, N. J. Curtis, A. Pullyblank, D. Jayne, J. A. Covington, N. Ratcliffe, N. K. Francis

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Background: Colorectal symptoms are common but only infrequently represent serious pathology, including colorectal cancer (CRC). A large number of invasive tests are presently performed for reassurance. We investigated the feasibility of urinary volatile organic compound (VOC) testing as a potential triage tool in patients fast-tracked for assessment for possible CRC. Methods: A prospective, multi-centre, observational feasibility study was performed across three sites. Patients referred on NHS fast-track pathways for potential CRC provided a urine sample which underwent Gas Chromatography Mass Spectrometry (GC-MS), Field Asymmetric Ion Mobility Spectrometry (FAIMS) and Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) analysis. Patients underwent colonoscopy and/or CT colonography and were grouped as either CRC, adenomatous polyp(s), or controls to explore the diagnostic accuracy of VOC output data supported by an artificial neural network (ANN) model. Results: 558 patients participated with 23 (4.1%) CRC diagnosed. 59% of colonoscopies and 86% of CT colonographies showed no abnormalities. Urinary VOC testing was feasible, acceptable to patients, and applicable within the clinical fast track pathway. GC-MS showed the highest clinical utility for CRC and polyp detection vs. controls (sensitivity=0.878, specificity=0.882, AUROC=0.884). Conclusion: Urinary VOC testing and analysis are feasible within NHS fast-track CRC pathways. Clinically meaningful differences between patients with cancer, polyps, or no pathology were identified therefore suggesting VOC analysis may have future utility as a triage tool. Acknowledgment: Funding: NIHR Research for Patient Benefit grant (ref: PB-PG-0416-20022).

Keywords: colorectal cancer, volatile organic compound, gas chromatography mass spectrometry, field asymmetric ion mobility spectrometry, selected ion flow tube mass spectrometry

Procedia PDF Downloads 93

Authors: Irati Barandiaran, Xabier Velasco-Iza, Galder Kortaberria

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Hybrid inorganic/organic nanostructured materials based on block copolymers are of considerable interest in the field of Nanotechnology, taking into account that these nanocomposites combine the properties of polymer matrix and the unique properties of the added nanoparticles. The use of block copolymers as templates offers the opportunity to control the size and the distribution of inorganic nanoparticles. This research is focused on the surface modification of inorganic nanoparticles to reach a good interface between nanoparticles and polymer matrices which hinders the nanoparticle aggregation. The aim of this work is to obtain a good and selective dispersion of Fe3O4 magnetic nanoparticles into different types of block copolymers such us, poly(styrene-b-methyl methacrylate) (PS-b-PMMA), poly(styrene-b-ε-caprolactone) (PS-b-PCL) poly(isoprene-b-methyl methacrylate) (PI-b-PMMA) or poly(styrene-b-butadiene-b-methyl methacrylate) (SBM) by using different grafting strategies. Fe3O4 magnetic nanoparticles have been surface-modified with polymer or block copolymer brushes following different grafting methods (grafting to, grafting from and grafting through) to achieve a selective location of nanoparticles into desired domains of the block copolymers. Morphology of fabricated hybrid nanocomposites was studied by means of atomic force microscopy (AFM) and with the aim to reach well-ordered nanostructured composites different annealing methods were used. Additionally, nanoparticle amount has been also varied in order to investigate the effect of the nanoparticle content in the morphology of the block copolymer. Nowadays different characterization methods were using in order to investigate magnetic properties of nanometer-scale electronic devices. Particularly, two different techniques have been used with the aim of characterizing synthesized nanocomposites. First, magnetic force microscopy (MFM) was used to investigate qualitatively the magnetic properties taking into account that this technique allows distinguishing magnetic domains on the sample surface. On the other hand, magnetic characterization by vibrating sample magnetometer and superconducting quantum interference device. This technique demonstrated that magnetic properties of nanoparticles have been transferred to the nanocomposites, exhibiting superparamagnetic behavior similar to that of the maghemite nanoparticles at room temperature. Obtained advanced nanostructured materials could found possible applications in the field of dye-sensitized solar cells and electronic nanodevices.

Keywords: atomic force microscopy, block copolymers, grafting techniques, iron oxide nanoparticles

Procedia PDF Downloads 262

Authors: Ahmad Alsheikh Kaddour

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Herbal medicine has been a long-standing phenomenon in Arab countries since ancient times because of its breadth and moderate temperament. Therefore, it possesses a vast natural and economic wealth of medicinal and aromatic herbs. This prompted ancient Egyptians and Arabs to discover and exploit them. The economic importance of the plant is not only from medicinal uses; it is a plant of high economic value for its various uses, especially in food, cosmetic and aromatic industries. It is also an ornamental plant and soil stabilization. The main objective of this research is to study the chemical changes that occur in the plant during the growth period, as well as the production of plant buds, which were previously considered unwanted plants. The research was carried out in the period 2021-2022 in the valley of Al-Shaflah (common caper), located in Qumhana village, 7 km north of Hama Governorate, Syria. The results of the research showed a change in the percentage of chemical components in the plant parts. The ratio of protein content and the percentage of fatty substances in fruits and the ratio of oil in the seeds until the period of harvesting of these plant parts improved, but the percentage of essential oils decreased with the progress of the plant growth, while the Glycosides content where improved with the plant aging. The production of buds is small, with dimensions as 0.5×0.5 cm, which is preferred for commercial markets, harvested every 2-3 days in quantities ranging from 0.4 to 0.5 kg in one cut/shrubs with 3 years’ age as average for the years 2021-2022. The monthly production of a shrub is between 4-5 kg per month. The productive period is 4 months approximately. This means that the seasonal production of one plant is 16-20 kg and the production of 16-20 tons per year with a plant density of 1,000 shrubs per hectare, which is the optimum rate of cultivation in the unit of mass, given the price of a kg of these buds is equivalent to 1 US $; however, this means that the annual output value of the locally produced hectare ranges from 16,000 US $ to 20,000 US $ for farmers. The results showed that it is possible to transform the cultivation of this plant from traditional random to typical areas cultivation, with a plant density of 1,000-1,100 plants per hectare according to the type of soil to obtain production of medicinal and nutritious buds, as well as, the need to pay attention to this national wealth and invest in the optimal manner, which leads to the acquisition of hard currency through export to support the national income.

Keywords: common caper, medicinal plants, propagation, medical, economic importance

Procedia PDF Downloads 72

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

Procedia PDF Downloads 219

Authors: Govinda Pathak

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In modern agriculture, the sustainable enhancement of crop productivity while minimizing environmental impacts remains a paramount challenge. Plant Growth Promoting Rhizobacteria (PGPR) have emerged as a promising solution to address this challenge. The rhizosphere, the dynamic interface between plant roots and soil, hosts intricate microbial interactions crucial for plant health and nutrient acquisition. PGPR, a subset of rhizospheric microorganisms, exhibit multifaceted beneficial effects on plants. Their abilities to stimulate growth, confer stress tolerance, enhance nutrient availability, and suppress pathogens make them invaluable contributors to sustainable agriculture. This work examines the pivotal role of free living nitrogen fixer in optimizing agricultural practices. We delve into the intricate mechanisms underlying PGPR-mediated plant-microbe interactions, encompassing quorum sensing, root exudate modulation, and signaling molecule exchange. Furthermore, we explore the diverse strategies employed by PGPR to enhance plant resilience against abiotic stresses such as drought, salinity, and metal toxicity. Additionally, we highlight the role of PGPR in augmenting nutrient acquisition and soil fertility through mechanisms such as nitrogen fixation, phosphorus solubilization, and mineral mobilization. Furthermore, we discuss the potential of PGPR in minimizing the reliance on chemical fertilizers and pesticides, thereby contributing to environmentally friendly agriculture. However, harnessing the full potential of PGPR requires a comprehensive understanding of their interactions with host plants and the surrounding microbial community. We also address challenges associated with PGPR application, including formulation, compatibility, and field efficacy. As the quest for sustainable agriculture intensifies, harnessing the remarkable attributes of PGPR offers a holistic approach to propel agricultural productivity while maintaining ecological balance. This work underscores the promising prospect of free living nitrogen fixer as a panacea for addressing critical agricultural challenges regarding chemical urea in an era of sustainable and resilient food production.

Keywords: PGPR, nitrogen fixer, quorum sensing, Rhizobacteria, pesticides

Procedia PDF Downloads 62

Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

Procedia PDF Downloads 88

Authors: Samaneh Nazeri, Bagher Mojazi Amiri, Hamid Farahmand

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Production of high quality fish eggs with reasonable hatching rate makes a success in aquaculture industries. It is influenced by the environmental stimulators and inhibitors. Diazinon is a widely-used pesticide in Golestan province (Southern Caspian Sea, North of Iran) which is washed to the aquatic environment (3 mg/L in the river). It is little known about the effect of this pesticide on the embryogenesis of sturgeon fish, the valuable species of the Caspian Sea. Hormonal content of the egg is an important factor to guaranty the successful passes of embryonic stages. In this study, the fate of Persian sturgeon embryo to 24, 48, 72, and 96-hours exposure of diazinon (LC₅₀ dose) was tested. Also, the effect of thyroid hormones (T3 and T4) on these embryos was tested concurrently or separately with diazinon LC ₅₀ dose. Fertilized eggs are exposed to T3 (low dose: 1 ng/ml, high dose: 10 ng/ml), T4 (low dose: 1 ng/ml, high dose: 10 ng/ml). Six eggs were randomly selected from each treatment (with three replicates) in five developmental stages (two cell- division, neural, heart present, heart beaten, and hatched larvae). The possibility of changing T3, T4, and cortisol contents of the embryos were determined in all treated groups and in every mentioned embryonic stage. The hatching rate in treated groups was assayed at the end of the embryogenesis to clarify the effect of thyroid hormones and diazinon. The results indicated significant differences in thyroid hormone contents, but no significant differences were recognized in cortisol levels at various early life stages of embryos. There was also significant difference in thyroid hormones in (T3, T4) + diazinon treated embryos (P˂0.05), while no significant difference between control and treatments in cortisol levels was observed. The highest hatching rate was recorded in HT3 treatment, while the lowest hatching rate was recorded for diazinon LC₅₀ treatment. The result confirmed that Persian sturgeon embryo is less sensitive to diazinon compared to teleost embryos, and thyroid hormones may increase hatching rate even in the presence of diazinon.

Keywords: Persian sturgeon, diazinon, thyroid hormones, cortisol, embryo

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Authors: Parya Tabei, Maryam Habibifar

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Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

Procedia PDF Downloads 53

Authors: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

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Australia is a country of some 7,700 million square kilometres with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban storm-water and treated wastewater. But till now it is not widely practiced in Australia, and particularly storm-water is neglected. In Australia, only 4% of storm-water and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As storm-water is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing storm-water recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of storm-water harvesting and reuse. Numerical modelling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes storm-water quantity to design the system components, and the hydraulic model helps to route the flow through storm-water infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a storm-water harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of storm-water harvesting and reuse such as available guidelines of storm-water harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of storm-water harvesting and reuse.

Keywords: storm-water management, storm-water harvesting and reuse, numerical modelling, geographic information system, decision support system, database

Procedia PDF Downloads 373

Authors: James Britton, Vijaya Krishna, Manus Biggs, Abhay Pandit

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Regeneration of the spinal cord after injury remains a great challenge due to the complexity of this organ. Inflammation and gliosis at the injury site hinder the outgrowth of axons and hence prevent synaptic reconnection and reinnervation. Hyaluronic acid (HA) is the main component of the spinal cord extracellular matrix and plays a vital role in cell proliferation and axonal guidance. In this study, we have synthesized and characterized a photo-cross-linkable HA-tyramine (tyr) hydrogel from a chemical, mechanical, electrical, biological and structural perspective. From our experimentation, we have found that HA-tyr can be synthesized with controllable degrees of tyramine substitution using click chemistry. The complex modulus (G*) of HA-tyr can be tuned to mimic the mechanical properties of the native spinal cord via optimization of the photo-initiator concentration and UV exposure. We have examined the degree of tyramine-tyramine covalent bonding (polymerization) as a function of UV exposure and photo-initiator use via Photo and Nuclear magnetic resonance spectroscopy. Both swelling and enzymatic degradation assays were conducted to examine the resilience of our 3D printed hydrogel constructs in-vitro. Using a femtosecond 780nm laser, the two-photon polymerization of HA-tyr hydrogel in the presence of riboflavin photoinitiator was optimized. A laser power of 50mW and scan speed of 30,000 μm/s produced high-resolution spatial patterning within the hydrogel with sustained mechanical integrity. Using dorsal root ganglion explants, the cytocompatibility of photo-crosslinked HA-tyr was assessed. Using potentiometry, the electrical conductivity of photo-crosslinked HA-tyr was assessed and compared to that of native spinal cord tissue as a function of frequency. In conclusion, we have developed a biocompatible hydrogel that can be used for photolithographic 3D printing to fabricate tissue engineered constructs for neural tissue regeneration applications.

Keywords: 3D printing, hyaluronic acid, photolithography, spinal cord injury

Procedia PDF Downloads 152

Authors: Surbhi Surbhi, Andrea Erni, Gunter Meister, Harold Cremer, Christophe Beclin

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MicroRNAs (miRNAs) are short 20-23 nucleotide long non-coding RNAs; there are 2605 miRNA in humans and 1936 miRNA in mouse in total (miRBase). The nervous system expresses the most abundant miRNA and most diverse. MiRNAs play a role in many steps during neurogenesis, like cell proliferation, differentiation, neural patterning, axon pathfinding, etc. Moreover, in vitro studies suggested a role in the regulation of local translation at the synapse, thus controlling neuronal plasticity. However, due to the specific structure of miRNA molecules, an in-vivo confirmation of the general role of miRNAs in the control of neuronal plasticity is still pending. For example, their small size and their high level of sequence homology make difficult the analysis of their cellular and sub-cellular localization in-vivo by in-situ hybridization. Moreover, it was found that only 40% of the expressed miRNA molecules in a cell are included in RNA-Induced Silencing Complexes (RISC) and, therefore, involved in inhibitory interactions while the rest is silent. Definitively, the development of new tools is needed to have a better understanding of the cellular function of miRNAs, in particular their role in neuronal plasticity. Here we describe a new technique called in-vivo AGO-APP designed to investigate miRNA expression and function in-vivo. This technique is based on the expression of a small peptide derived from the human RISC-complex protein TNRC6B, called T6B, which binds all known Argonaute (Ago) proteins with high affinity allowing the efficient immunoprecipitation of AGO-bound miRNAs. We have generated two transgenic mouse lines conditionally expressing T6B either ubiquitously in the cell or targeted at the synapse. A comparison of the repertoire of miRNAs immuno-precipitated from mature neurons of both mouse lines will provide us with a list of miRNAs showing a specific activity at the synapse. The physiological role of these miRNAs will be subsequently addressed through gain and loss of function experiments.

Keywords: RNA-induced silencing complexes, TNRC6B, miRNA, argonaute, synapse, neuronal plasticity, neurogenesis

Procedia PDF Downloads 134

Authors: Wedad Albalawi

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The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is defined as a closed subset contains real numbers. Then the inequalities of time scales version have received a lot of attention and has had a major field in both pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on double integrals to obtain new time-scale inequalities of Copson driven by Steklov operator. They will be applied in the solution of the Cauchy problem for the wave equation. The proof can be done by introducing restriction on the operator in several cases. In addition, the obtained inequalities done by using some concepts in time scale version such as time scales calculus, theorem of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of Hardy, inequality of Coposon, Steklov operator

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Authors: Helene Jacobson Pettersson, Linda Lill

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Demographic changes and globalization in society provide new opportunities for social work and social work education in Sweden. There has been an ambition to include these aspects into the Swedish social work education. However, the Swedish welfare state standard continued to be as affectionate as invisible starting point in discussions about people’s way of life and social problems. The aim of this study is to explore content given to ethnic relations in social work in the social work education in Sweden. Our standpoint is that the subject can be understood both from individual and structural levels, it changes over time, varies in different steering documents and differs from the perspectives of teachers and students. Our question is what content is given to ethnic relations in social work by the teachers in their strategies and teaching material. The study brings together research in the interface between education science, social work and research of international migration and ethnic relations. The presented narratives are from longer interviews with a total of 17 university teachers who teach in social work program at four different universities in Sweden. The universities have in different ways a curriculum that involves the theme of ethnic relations in social work, and the interviewed teachers are teaching and grading social workers on specific courses related to ethnic relations at undergraduate and graduate levels. Overall assesses these 17 teachers a large number of students during a semester. The questions were concerned on how the teachers handle ethnic relations in education in social work. The particular focus during the interviews has been the teacher's understanding of the documented learning objectives and content of literature and how this has implications for their teaching. What emerges is the teachers' own stories about the educational work and how they relate to the content of teaching, as well as the teaching strategies they use to promote the theme of ethnic relations in social work education. The analysis of this kind of pedagogy is that the teaching ends up at an individual level with a particular focus on the professional encounter with individuals. We can see the shortage of a critical analysis of the construction of social problems. The conclusion is that individual circumstance precedes theoretical perspective on social problems related to migration, transnational relations, globalization and social. This result has problematic implications from the perspective of sustainability in terms of ethnic diversity and integration in society. Thus these aspects have most relevance for social workers’ professional acting in social support and empowerment related activities, in supporting the social status and human rights and equality for immigrants.

Keywords: ethnic relations in Swedish social work education, teaching content, teaching strategies, educating for change, human rights and equality

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Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

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Authors: Hammad Majeed, Hanna Knuutila, Magne Hilestad, Hallvard Svendsen

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Formation of aerosols can cause serious complications in industrial exhaust gas CO2 capture processes. SO3 present in the flue gas can cause aerosol formation in an absorption based capture process. Small mist droplets and fog formed can normally not be removed in conventional demisting equipment because their submicron size allows the particles or droplets to follow the gas flow. As a consequence of this aerosol based emissions in the order of grams per Nm3 have been identified from PCCC plants. In absorption processes aerosols are generated by spontaneous condensation or desublimation processes in supersaturated gas phases. Undesired aerosol development may lead to amine emissions many times larger than what would be encountered in a mist free gas phase in PCCC development. It is thus of crucial importance to understand the formation and build-up of these aerosols in order to mitigate the problem.Rigorous modelling of aerosol dynamics leads to a system of partial differential equations. In order to understand mechanics of a particle entering an absorber an implementation of the model is created in Matlab. The model predicts the droplet size, the droplet internal variable profiles and the mass transfer fluxes as function of position in the absorber. The Matlab model is based on a subclass method of weighted residuals for boundary value problems named, orthogonal collocation method. The model comprises a set of mass transfer equations for transferring components and the essential diffusion reaction equations to describe the droplet internal profiles for all relevant constituents. Also included is heat transfer across the interface and inside the droplet. This paper presents results describing the basic simulation tool for the characterization of aerosols formed in CO2 absorption columns and gives examples as to how various entering droplets grow or shrink through an absorber and how their composition changes with respect to time. Below are given some preliminary simulation results for an aerosol droplet composition and temperature profiles. Results: As an example a droplet of initial size of 3 microns, initially containing a 5M MEA, solution is exposed to an atmosphere free of MEA. Composition of the gas phase and temperature is changing with respect to time throughout the absorber.

Keywords: amine solvents, emissions, global climate change, simulation and modelling, aerosol generation

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Authors: Sudip Mondal, Biswanath Mondal, Sudit S. Mukhopadhyay, Apurba Dey

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Bioactive materials improve devices for a long lifespan but have mechanical limitations. Mechanical characterization is one of the very important characteristics to evaluate the life span and functionality of the scaffold material. After implantation of scaffold material the primary stage rejection of scaffold occurs due to non biocompatible effect of host body system. The second major problems occur due to the effect of mechanical failure. The mechanical and biocompatibility failure of the scaffold materials can be overcome by the prior evaluation of the scaffold materials. In this study chemically treated Labeo rohita scale is used for synthesizing hydroxyapatite (HAp) biomaterial. Thermo-gravimetric and differential thermal analysis (TG-DTA) is carried out to ensure thermal stability. The chemical composition and bond structures of wet ball-milled calcined HAp powder is characterized by Fourier Transform Infrared spectroscopy (FTIR), X-ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy (TEM), Energy Dispersive X-ray (EDX) analysis. Fish scale derived apatite materials consists of nano-sized particles with Ca/P ratio of 1.71. The biocompatibility through cytotoxicity evaluation and MTT assay are carried out in MG63 osteoblast cell lines. In the cell attachment study, the cells are tightly attached with HAp scaffolds developed in the laboratory. The result clearly suggests that HAp material synthesized in this study do not have any cytotoxic effect, as well as it has a natural binding affinity for mammalian cell lines. The synthesized HAp powder further successfully used to develop porous scaffold material with suitable mechanical property of ~0.8GPa compressive stress, ~1.10 GPa a hardness and ~ 30-35% porosity which is acceptable for implantation in trauma region for animal model. The histological analysis also supports the bio-affinity of processed HAp biomaterials in Wistar rat model for investigating the contact reaction and stability at the artificial or natural prosthesis interface for biomedical function. This study suggests the natural sourced fish scale-derived HAp material could be used as a suitable alternative biomaterial for tissue engineering application in near future.

Keywords: biomaterials, hydroxyapatite, scaffold, mechanical property, tissue engineering

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Authors: Samuel J. Ahmad, Michael Zhu, Andrew J. Kobets

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Segmentation tools continue to advance, evolving from manual methods to automated contouring technologies utilizing convolutional neural networks. These techniques have evaluated ventricular and hemorrhagic volumes in the past but may be applied in novel ways to assess posterior fossa-associated pathologies such as Chiari malformations. Herein, we summarize literature pertaining to segmentation in the context of this and other posterior fossa-based diseases such as trigeminal neuralgia, hemifacial spasm, and posterior fossa syndrome. A literature search for volumetric analysis of the posterior fossa identified 27 papers where semi-automated, automated, manual segmentation, linear measurement-based formulas, and the Cavalieri estimator were utilized. These studies produced superior data than older methods utilizing formulas for rough volumetric estimations. The most commonly used segmentation technique was semi-automated segmentation (12 studies). Manual segmentation was the second most common technique (7 studies). Automated segmentation techniques (4 studies) and the Cavalieri estimator (3 studies), a point-counting method that uses a grid of points to estimate the volume of a region, were the next most commonly used techniques. The least commonly utilized segmentation technique was linear measurement-based formulas (1 study). Semi-automated segmentation produced accurate, reproducible results. However, it is apparent that there does not exist a single semi-automated software, open source or otherwise, that has been widely applied to the posterior fossa. Fully-automated segmentation via such open source software as FSL and Freesurfer produced highly accurate posterior fossa segmentations. Various forms of segmentation have been used to assess posterior fossa pathologies and each has its advantages and disadvantages. According to our results, semi-automated segmentation is the predominant method. However, atlas-based automated segmentation is an extremely promising method that produces accurate results. Future evolution of segmentation technologies will undoubtedly yield superior results, which may be applied to posterior fossa related pathologies. Medical professionals will save time and effort analyzing large sets of data due to these advances.

Keywords: chiari, posterior fossa, segmentation, volumetric

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Authors: Mahmoud Moawad Mohamed Osman

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The Egyptian civilization was and still is an inspiration for many human civilizations and modern sciences. For this reason, there is still a passion for the ancient Egyptian civilization. Due to the breadth and abundance of the outputs of the ancient Egyptian civilization, many museums have been established that contribute to displaying and demonstrating the splendor of the ancient Egyptian civilization, and among those museums is the Grand Egyptian Museum (Egypt's gift to the whole world). The idea of establishing the Grand Egyptian Museum began in the nineties of the last century, and in 2002 the foundation stone was laid for the museum project to be built in a privileged location overlooking the eternal pyramids of Giza, where the Egyptian state was declared, and under the auspices of the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the International Union of Architects. , for an international architectural competition for the best design for the museum. The current design submitted by Heneghan Peng Architects in Ireland won, and its design was based on the rays of the sun extending from the tops of the three pyramids when they meet to represent a conical mass, which is the Grand Egyptian Museum. The construction of the museum project began in May 2005, when the site was paved and prepared, and in 2006, the largest antiquities restoration center in the Middle East was established, dedicated to the restoration, preservation, maintenance and rehabilitation of the antiquities scheduled to be displayed in the museum halls, which was opened in 2010. The construction of the museum building, which has an area of more than 300,000 square meters, was completed during the year 2021, and includes a number of exhibition halls, each of which is considered larger than many current museums in Egypt and the world. The museum is considered one of the most important and greatest achievements of modern Egypt. It was created to be an integrated global civilizational, cultural and entertainment edifice, and to be the first destination for everyone interested in ancient Egyptian heritage, as the largest museum in the world that tells the story of the history of ancient Egyptian civilization, as it contains a large number of distinctive and unique artifacts, including the treasures of the golden king Tutankhamun, which... It is displayed for the first time in its entirety since the discovery of his tomb in November 1922, in addition to the collection of Queen Hetepheres, the guard of the mother of King Khufu, the builder of the Great Pyramid in Giza, as well as the Museum of King Khufu’s Boats, as well as various archaeological collectibles from the pre-dynastic era until the Greek and Roman eras.

Keywords: grand egyptian museum, egyptian civilization, education, museology

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Authors: V. A. Dubovsky, V. V. Savchenko, A. A. Baryskevich

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The current trend in the automotive industry towards automatic vehicles is creating new challenges related to human factors. This occurs due to the fact that the driver is increasingly relieved of the need to be constantly involved in driving the vehicle, which can negatively impact his/her situation awareness when manual control is required, and decrease driving skills and abilities. These new problems need to be studied in order to provide road safety during the transition towards self-driving vehicles. For this purpose, it is important to develop an appropriate conceptual model of the interaction between the driver and the automated vehicle, which could serve as a theoretical basis for the development of mathematical and simulation models to explore different aspects of driver behaviour in different road situations. Well-known driver behaviour models describe the impact of different stages of the driver's cognitive process on driving performance but do not describe how the driver controls and adjusts his actions. A more complete description of the driver's cognitive process, including the evaluation of the results of his/her actions, will make it possible to more accurately model various aspects of the human factor in different road situations. This paper presents a conceptual model of the 'driver – highly automated vehicle' system based on the P.K. Anokhin's theory of functional systems, which is a theoretical framework for describing internal processes in purposeful living systems based on such notions as goal, desired and actual results of the purposeful activity. A central feature of the proposed model is a dynamic coupling mechanism between the decision-making of a driver to perform a particular action and changes of road conditions due to driver’s actions. This mechanism is based on the stage by stage evaluation of the deviations of the actual values of the driver’s action results parameters from the expected values. The overall functional structure of the highly automated vehicle in the proposed model includes a driver/vehicle/environment state analyzer to coordinate the interaction between driver and vehicle. The proposed conceptual model can be used as a framework to investigate different aspects of human factors in transitions between automated and manual driving for future improvements in driving safety, and for understanding how driver-vehicle interface must be designed for comfort and safety. A major finding of this study is the demonstration that the theory of functional systems is promising and has the potential to describe the interaction of the driver with the vehicle and the environment.

Keywords: automated vehicle, driver behavior, human factors, human-machine system

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Authors: Jineetkumar Gawad, Chandrakant Bonde

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Tuberculosis (TB) is a major worldwide concern whose control has been exacerbated by HIV, the rise of multidrug-resistance (MDR-TB) and extensively drug resistance (XDR-TB) strains of Mycobacterium tuberculosis. The interest for newer and faster acting antitubercular drugs are more remarkable than any time. To search potent compounds is need and challenge for researchers. Here, we tried to design lead for inhibition of Decaprenyl phosphoryl-β-D-ribose 2′-epimerase (DprE1) enzyme. Arabinose is an essential constituent of mycobacterial cell wall. DprE1 is a flavoenzyme that converts decaprenylphosphoryl-D-ribose into decaprenylphosphoryl-2-keto-ribose, which is intermediate in biosynthetic pathway of arabinose. Latter, DprE2 converts keto-ribose into decaprenylphosphoryl-D-arabinose. We had a selection of 23 compounds from azaindole series for computational study, and they were drawn using marvisketch. Ligands were prepared using Maestro molecular modeling interface, Schrodinger, v10.5. Common pharmacophore hypotheses were developed by applying dataset thresholds to yield active and inactive set of compounds. There were 326 hypotheses were developed. On the basis of survival score, ADRRR (Survival Score: 5.453) was selected. Selected pharmacophore hypotheses were subjected to virtual screening results into 1000 hits. Hits were prepared and docked with protein 4KW5 (oxydoreductase inhibitor) was downloaded in .pdb format from RCSB Protein Data Bank. Protein was prepared using protein preparation wizard. Protein was preprocessed, the workspace was analyzed using force field OPLS 2005. Glide grid was generated by picking single atom in molecule. Prepared ligands were docked with prepared protein 4KW5 using Glide docking. After docking, on the basis of glide score top-five compounds were selected, (5223, 5812, 0661, 0662, and 2945) and the glide docking score (-8.928, -8.534, -8.412, -8.411, -8.351) respectively. There were interactions of ligand and protein, specifically HIS 132, LYS 418, TRY 230, ASN 385. Pi-pi stacking was observed in few compounds with basic Imidazo [4,5-b] pyridine ring. We had basic azaindole ring in parent compounds, but after glide docking, we received compounds with Imidazo [4,5-b] pyridine as a basic ring. That might be the new lead in the process of drug discovery.

Keywords: DprE1 inhibitors, in silico drug designing, imidazo [4, 5-b] pyridine, lead, tuberculosis

Procedia PDF Downloads 156

Authors: A. Rezaei, M. Huisman, W. Van Paepegem

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Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

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Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

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Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

Procedia PDF Downloads 119

Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

Abstract:

Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

Procedia PDF Downloads 88

Authors: Magdalena Diaka, Paweł Mazierski, Joanna Żebrowska, Michał Winiarski, Tomasz Klimczuk, Adriana Zaleska-Medynska

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During the last years, TiO2 nanotubes have been widely studied due to their unique highly ordered array structure, unidirectional charge transfer and higher specific surface area compared to conventional TiO2 powder. These photoactive materials, in the form of thin layer, can be activated by low powered and low cost irradiation sources (such as LEDs) to remove VOCs, microorganism and to deodorize air streams. This is possible due to their directly growth on a support material and high surface area, which guarantee enhanced photon absorption together with an extensive adsorption of reactant molecules on the photocatalyst surface. TiO2 nanotubes exhibit also lots of other attractive properties, such as potential enhancement of electron percolation pathways, light conversion, and ion diffusion at the semiconductor-electrolyte interface. Pure TiO2 nanotubes were previously used to remove organic compounds from the gas phase as well as in water splitting reaction. The major factors limiting the use of TiO2 nanotubes, which have not been fully overcome, are their relatively large band gap (3-3,2 eV) and high recombination rate of photogenerated electron–hole pairs. Many different strategies were proposed to solve this problem, however titania nanostructures containing incorporated metal oxides like Ag2O shows very promising, new optical and photocatalytic properties. Unfortunately, there is still very limited number of reports regarding application of TiO2/MxOy nanostructures. In the present work, we prepared TiO2/Ag2O nanotubes obtained by anodization of Ti-Ag alloys containing 5, 10 and 15 wt. % Ag. Photocatalysts prepared in this way were characterized by X-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), luminescence spectroscopy and UV-Vis spectroscopy. The activities of new TiO2/Ag2O were examined by photocatalytic degradation of toluene in gas phase reaction and phenol in aqueous phase using 1000 W Xenon lamp (Oriel) and light emitting diodes (LED) as a irradiation sources. Additionally efficiency of bacteria (Pseudomonas aeruginosa) removal from the gas phase was estimated. The number of surviving bacteria was determined by the serial twofold dilution microtiter plate method, in Tryptic Soy Broth medium (TSB, GibcoBRL).

Keywords: photocatalysis, antibacterial properties, titania nanotubes, new TiO2/MxOy nanostructures

Procedia PDF Downloads 293

Authors: Román Rodríguez Echegoyen, Fernando Carlos López Hernández, José Manuel López Ujaque

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Interactive management of energy certification ratings has remained on the sidelines of the evolution of virtual reality (VR) despite related advances in architecture in other areas such as BIM and real-time working programs. This research studies to what extent VR software can help the stakeholders to better understand energy efficiency parameters in order to obtain reliable ratings assigned to the parts of the building. To evaluate this hypothesis, the methodology has included the construction of a software prototype. Current energy certification systems do not follow an intuitive data entry system; neither do they provide a simple or visual verification of the technical values included in the certification by manufacturers or other users. This software, by means of real-time visualization and a graphical user interface, proposes different improvements to the current energy certification systems that ease the understanding of how the certification parameters work in a building. Furthermore, the difficulty of using current interfaces, which are not friendly or intuitive for the user, means that untrained users usually get a poor idea of the grounds for certification and how the program works. In addition, the proposed software allows users to add further information, such as financial and CO₂ savings, energy efficiency, and an explanatory analysis of results for the least efficient areas of the building through a new visual mode. The software also helps the user to evaluate whether or not an investment to improve the materials of an installation is worth the cost of the different energy certification parameters. The evaluated prototype (named VEE-IS) shows promising results when it comes to representing in a more intuitive and simple manner the energy rating of the different elements of the building. Users can also personalize all the inputs necessary to create a correct certification, such as floor materials, walls, installations, or other important parameters. Working in real-time through VR allows for efficiently comparing, analyzing, and improving the rated elements, as well as the parameters that we must enter to calculate the final certification. The prototype also allows for visualizing the building in efficiency mode, which lets us move over the building to analyze thermal bridges or other energy efficiency data. This research also finds that the visual representation of energy efficiency certifications makes it easy for the stakeholders to examine improvements progressively, which adds value to the different phases of design and sale.

Keywords: energetic certification, virtual reality, augmented reality, sustainability

Procedia PDF Downloads 188