Search results for: interface stiffness

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Mohammad Rahman, Guy Burton, Megan Mathias

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Strategic management as an organizational practice was adopted by the public sector in the New Public Management (NPM) era that began in most parts of the world in the 1980s. Strategy as a new public management concept was subscribed by governments in both developed and developing world, as they were persuaded that clearly defined vision, mission and goals, as well as programs and projects - aligned with the goals - could potentially help achieve government vision at the national level and organizational goals at the service-delivery level. The advocates for strategic management in the public sector saw an inherent link between strategy and performance, claiming that the implementation of organizational strategy has an effect on the overall performance of an organization. Arguably, many government entities that have failed in enhancing team and individual performance had poorly-designed strategy or weak strategy implementation. Another key argument about low-level performance is linked with lack of strategic sense-making and orientation by middle managers in particular. Scholars maintain that employees at all levels need to understand strategic management plan in order to facilitate its implementation. Therefore, involving employees (particularly the middle managers) from the beginning potentially helps an organization avoid the drop in performance, and on the contrary would increase their commitment. The United Arab Emirates (UAE) is well known for adopting public sector reform strategies and tools since the 1990s. This observation is contextually pertinent in the case of the Government of Dubai, which has provided a Strategy Execution Guide to all of its entities to achieve high level strategic success in service delivery. The Dubai public sector also adopts road maps for e-Government, Smart Dubai, Expo 2020, investment, environment, education, health and other sectors. Evidently, some of these strategies are bringing tangible (e.g. Smart Dubai transformation) results in a transformational manner. However, the amount of academic research and literature on the strategy process vis-à-vis staff performance in the Government of Dubai is limited. In this backdrop, this study examines how individual performance of public sector employees in Dubai is linked with their sense-making, engagement and orientation with strategy development and implementation processes. Based on a theoretical framework, this study will undertake a sample-based questionnaire survey amongst middle managers in Dubai public sector to (a) measure the level of engagement of middle managers in strategy development and implementation processes as perceived by them; (b) observe the organizational landscape in which role expectations are placed on middle managers; and (c) examine the impact of employee engagement in strategy development process and the conditions for role expectations on individual performance. The paper is expected to provide new insights on the interface between strategic sense-making and performance in order to contribute a better understanding of the current culture/practices of staff engagement in strategic management in the public sector of Dubai.

Keywords: employee performance, government of Dubai, middle managers, strategic sense-making

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Authors: Sundaram Chandrasekaran, Seung Hyun Hur

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Exploring strategies for oxygen vacancy engineering under mild conditions and understanding the relationship between dislocations and photoelectrochemical (PEC) cell performance are challenging issues for designing high performance PEC devices. Therefore, it is very important to understand that how the oxygen vacancies (VO) or other defect states affect the performance of the photocatalyst in photoelectric transfer. So far, it has been found that defects in nano or micro crystals can have two possible significances on the PEC performance. Firstly, an electron-hole pair produced at the interface of photoelectrode and electrolyte can recombine at the defect centers under illumination of light, thereby reducing the PEC performances. On the other hand, the defects could lead to a higher light absorption in the longer wavelength region and may act as energy centers for the water splitting reaction that can improve the PEC performances. Even if the dislocation growth of ZnO has been verified by the full density functional theory (DFT) calculations and local density approximation calculations (LDA), it requires further studies to correlate the structures of ZnO and PEC performances. Exploring the hybrid structures composed of graphene oxide (GO) and ZnO nanostructures offer not only the vision of how the complex structure form from a simple starting materials but also the tools to improve PEC performances by understanding the underlying mechanisms of mutual interactions. As there are few studies for the ZnO growth with other materials and the growth mechanism in those cases has not been clearly explored yet, it is very important to understand the fundamental growth process of nanomaterials with the specific materials, so that rational and controllable syntheses of efficient ZnO-based hybrid materials can be designed to prepare nanostructures that can exhibit significant PEC performances. Herein, we fabricated various ZnO nanostructures such as hollow sphere, bucky bowl, nanorod and triangle, investigated their pH dependent growth mechanism, and correlated the PEC performances with them. Especially, the origin of well-controlled dislocation-driven growth and its transformation mechanism of ZnO nanorods to triangles on the GO surface were discussed in detail. Surprisingly, the addition of GO during the synthesis process not only tunes the morphology of ZnO nanocrystals and also creates more oxygen vacancies (oxygen defects) in the lattice of ZnO, which obviously suggest that the oxygen vacancies be created by the redox reaction between GO and ZnO in which the surface oxygen is extracted from the surface of ZnO by the functional groups of GO. On the basis of our experimental and theoretical analysis, the detailed mechanism for the formation of specific structural shapes and oxygen vacancies via dislocation, and its impact in PEC performances are explored. In water splitting performance, the maximum photocurrent density of GO-ZnO triangles was 1.517mA/cm-2 (under UV light ~ 360 nm) vs. RHE with high incident photon to current conversion Efficiency (IPCE) of 10.41%, which is the highest among all samples fabricated in this study and also one of the highest IPCE reported so far obtained from GO-ZnO triangular shaped photocatalyst.

Keywords: dislocation driven growth, zinc oxide, graphene oxide, water splitting

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Authors: Taha Anjamrooz, Sareh Rajabi, Ayman Alzaatreh

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Smart cities are playing important roles in real life. Integration and automation between different features of modern cities and information technologies improve smart city efficiency, energy management, human and equipment resource management, life quality and better utilization of resources for the customers. One of difficulties in this path, is use, interface and link between software, hardware, and other IT technologies to develop and optimize processes in various business fields such as construction, supply chain management and transportation in parallel to cost-effective and resource reduction impacts. Also, Smart cities are certainly intended to demonstrate a vital role in offering a sustainable and efficient model for smart houses while mitigating environmental and ecological matters. Energy management is one of the most important matters within smart houses in the smart cities and communities, because of the sensitivity of energy systems, reduction in energy wastage and maximization in utilizing the required energy. Specially, the consumption of energy in the smart houses is important and considerable in the economic balance and energy management in smart city as it causes significant increment in energy-saving and energy-wastage reduction. This research paper develops features and concept of smart city in term of overall efficiency through various effective variables. The selected variables and observations are analyzed through data analysis processes to demonstrate the efficiency of smart city and compare the effectiveness of each variable. There are ten chosen variables in this study to improve overall efficiency of smart city through increasing effectiveness of smart houses using an automated solar photovoltaic system, RFID System, smart meter and other major elements by interfacing between software and hardware devices as well as IT technologies. Secondly to enhance aspect of energy management by energy-saving within smart house through efficient variables. The main objective of smart city and smart houses is to reproduce energy and increase its efficiency through selected variables with a comfortable and harmless atmosphere for the customers within a smart city in combination of control over the energy consumption in smart house using developed IT technologies. Initially the comparison between traditional housing and smart city samples is conducted to indicate more efficient system. Moreover, the main variables involved in measuring overall efficiency of system are analyzed through various processes to identify and prioritize the variables in accordance to their influence over the model. The result analysis of this model can be used as comparison and benchmarking with traditional life style to demonstrate the privileges of smart cities. Furthermore, due to expensive and expected shortage of natural resources in near future, insufficient and developed research study in the region, and available potential due to climate and governmental vision, the result and analysis of this study can be used as key indicator to select most effective variables or devices during construction phase and design

Keywords: smart city, traditional housing, RFID, photovoltaic system, energy efficiency, energy saving

Procedia PDF Downloads 112

Authors: P. Dubcek, B. Pivac, J. Dasovic, V. Janicki, S. Bernstorff

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When grown only to nanometric sizes, metallic particles (e.g. Ag, Au and Cu) exhibit specific optical properties caused by the presence of plasmon band. The plasmon band represents collective oscillation of the conduction electrons, and causes a narrow band absorption of light in the visible range. When the nanoparticles are embedded in a dielectric, they also cause modifications of dielectrics optical properties. This can be fine-tuned by tuning the particle size. We investigated Cu nanoparticle growth with and without surrounding dielectric (SiO2 capping layer). The morphology and crystallinity were investigated by GISAXS and GIWAXS, respectively. Samples were produced by high vacuum thermal evaporation of Cu onto monocrystalline silicon substrate held at room temperature, 100°C or 180°C. One series was in situ capped by 10nm SiO2 layer. Additionally, samples were annealed at different temperatures up to 550°C, also in high vacuum. The room temperature deposited samples annealed at lower temperatures exhibit continuous film structure: strong oscillations in the GISAXS intensity are present especially in the capped samples. At higher temperatures enhanced surface dewetting and Cu nanoparticles (nanoislands) formation partially destroy the flatness of the interface. Therefore the particle type of scattering is enhanced, while the film fringes are depleted. However, capping layer hinders particle formation, and continuous film structure is preserved up to higher annealing temperatures (visible as strong and persistent fringes in GISAXS), compared to the non- capped samples. According to GISAXS, lateral particle sizes are reduced at higher temperatures, while particle height is increasing. This is ascribed to close packing of the formed particles at lower temperatures, and GISAXS deduced sizes are partially the result of the particle agglomerate dimensions. Lateral maxima in GISAXS are an indication of good positional correlation, and the particle to particle distance is increased as the particles grow with temperature elevation. This coordination is much stronger in the capped and lower temperature deposited samples. The dewetting is much more vigorous in the non-capped sample, and since nanoparticles are formed in a range of sizes, correlation is receding both with deposition and annealing temperature. Surface topology was checked by atomic force microscopy (AFM). Capped sample's surfaces were smoother and lateral size of the surface features were larger compared to the non-capped samples. Altogether, AFM results suggest somewhat larger particles and wider size distribution, and this can be attributed to the difference in probe size. Finally, the plasmonic effect was monitored by UV-Vis reflectance spectroscopy, and relative weak plasmonic effect could be explained by uncomplete dewetting or partial interconnection of the formed particles.

Keywords: coper, GISAXS, nanoparticles, plasmonics

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Authors: Dinara Ikramova, Karin A. Hing, Simon C. F. Rawlinson

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Silicate-substituted hydroxyapatite (SiHA) has been shown to enhance bone regeneration in vivo compared with phase pure stoichiometric hydroxyapatite. Evidence suggests that substrate chemistry dependent formation of a permissive protein layer on the surface of synthetic bone graft substitute materials is key for bioactivity and cell attachment. However, little information is available on whether the substrate chemistry may affect cell migration and recruitment. The aim of this study is to investigate whether or not human Mesenchymal Stem Cells (hMSCs) exhibit a chemotactic response to SiHA porous granules and if it can be linked to either the ion exchange or protein sequestering and enrichment on the surface of the material. 150mg of SiHA granules with 80% total porosity and 20% strut porosity were incubated in 1ml of either Serum Free Media (SFM) or 10% Serum Containing Media (SCM) under static cell culture conditions (37°C, 5% CO2) in absence of cells. Protein sequestering and exchange of calcium, phosphate and silicate ions were analysed at 0.5, 1, 2, 4, 8, 16 and 24 hours with n=12 per time point. Migration of hMSCs in the presence of 150mg of SiHA granules was assessed over 24 hours using a modified transwell migration system in either SFM or SCM (n=6) with 30% serum containing media acting as a positive control. At 24 hours protein sequestering and ionic exchange were analysed, and the number of cells was quantified using a high throughput confocal microscope (IN Cell Analyser 6000). In acellular condition, both calcium and phosphate ion concentrations in media showed a decrease at 24 hours which was greater in SFM than in SCM. This suggests possible formation and precipitation of a bone like apatite on the surface of SiHA. Reduction in this activity observed in SCM indicates that the presence of serum proteins is interfering with the ion exchange at the material and media interface. Adsorbed protein levels showed fluctuation over time followed by sharp decrease at 24 hours, suggesting a possible protein rearrangement on the surface of the material. The ion analysis performed on SFM and SCM after 24-hour incubation with cells in the presence of granules showed a greater reduction in phosphate concentration in both SFM and SCM compared to phosphate levels in acellular condition. Silicate concentration in SCM increased from 1.6mM (absence of cells) to 5.1mM (presence of cells). This indicates that the cells are promoting the uptake of phosphate and release of silicate ions. No significant change was seen in levels of adsorbed proteins in the presence and absence of cells. Further analysis is required to determine whether the species of these proteins change over time. The analysis of cell migration after 24-hour incubation showed more cells migrating towards the granules, 12.7% in SFM and 8.3% in SCM, than in positive control, 4.5% in SFM and 3.6% in SCM respectively. These results suggest that SiHA has a chemotactic activity independent of serum proteins. A property which has not previously been demonstrated for a synthetic bone graft material.

Keywords: cell migration, hMSCs, SiHA, transwell migration system

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Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

Procedia PDF Downloads 121

Authors: K. K. Balavenkatraman, B. Bertschi, K. Bigot, A. Grevot, A. Doelemeyer, S. D. Chibout, A. Wolf, F. Pognan, N. Manevski, O. Kretz, P. Swart, K. Litherland, J. Ashton-Chess, B. Ling, R. Wettstein, D. J. Schaefer

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Skin toxicity is poorly detected during preclinical studies, and drug-induced side effects in humans such as rashes, hyperplasia or more serious events like bullous pemphigus or toxic epidermal necrolysis represent an important hurdle for clinical development. In vitro keratinocyte-based epidermal skin models are suitable for the detection of chemical-induced irritancy, but do not recapitulate the biological complexity of full skin and fail to detect potential serious side-effects. Normal healthy skin explants may represent a valuable complementary tool, having the advantage of retaining the full skin architecture and the resident immune cell diversity. This study investigated several conditions for the maintenance of good morphological structure after several days of culture and the retention of phase II metabolism for 24 hours in skin explants in vitro. Human skin samples were collected with informed consent from patients undergoing plastic surgery and immediately transferred and processed in our laboratory by removing the underlying dermal fat. Punch biopsies of 4 mm diameter were cultured in an air-liquid interface using transwell filters. Different cultural conditions such as the effect of calcium, temperature and cultivation media were tested for a period of 14 days and explants were histologically examined after Hematoxylin and Eosin staining. Our results demonstrated that the use of Williams E Medium at 32°C maintained the physiological integrity of the skin for approximately one week. Upon prolonged incubation, the upper layers of the epidermis become thickened and some dead cells are present. Interestingly, these effects were prevented by addition of EGFR inhibitors such as Afatinib or Erlotinib. Phase II metabolism of the skin such as glucuronidation (4-methyl umbeliferone), sulfation (minoxidil), N-acetyltransferase (p-toluidene), catechol methylation (2,3-dehydroxy naphthalene), and glutathione conjugation (chlorodinitro benzene) were analyzed by using LCMS. Our results demonstrated that the human skin explants possess metabolic activity for a period of at least 24 hours for all the substrates tested. A time course for glucuronidation with 4-methyl umbeliferone was performed and a linear correlation was obtained over a period of 24 hours. Longer-term culture studies will indicate the possible evolution of such metabolic activities. In summary, these results demonstrate that human skin explants maintain a normal structure for several days in vitro and are metabolically active for at least the first 24 hours. Hence, with further characterisation, this model may be suitable for the study of drug-induced toxicity.

Keywords: human skin explant, phase II metabolism, epidermal growth factor receptor, toxicity

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Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

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Authors: Nirit Gavish, Rotem Halutz, Liad Neta

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Nowadays, chatbots are gaining more and more attention due to the advent of large language models. One of the important considerations in chatbot design is how to create an interface to achieve high user satisfaction, trust, and acceptance. Since WhatsApp conversations sometimes substitute for face-to-face communication, we studied whether WhatsAppization of the chatbot -making the conversation resemble a WhatsApp conversation more- will improve user satisfaction, trust, and acceptance, or whether the opposite will occur due to the Uncanny Valley (UV) effect. The task was a drive-sharing task, in which participants communicated with a textual chatbot via WhatsApp and could decide whether to participate in a ride to college with a driver suggested by the chatbot. WhatsAppization of the chatbot was done in two ways: By a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing…” (Indicators versus No Indicators). Our 120 participants were randomly assigned to one of the four 2 by 2 design groups, with 30 participants in each. They interacted with the WhatsApp chatbot and then filled out a questionnaire. The results demonstrated that, as expected from the manipulation, the interaction with the chatbot was longer for the dialog condition compared to the no dialog. This extra interaction, however, did not lead to higher acceptance -quite the opposite, since participants in the dialog condition were less willing to implement the decision made at the end of the conversation with the chatbot and continue the interaction with the driver they chose. The results are even more striking when considering the Indicators condition. Both for the satisfaction measures and the trust measures, participants’ ratings were lower in the Indicators condition compared to the No Indicators. Participants in the Indicators condition felt that the ride search process was harder to operate, and slower (even though the actual interaction time was similar). They were less convinced that the chatbot suggested real trips and they trusted the person offering the ride and referred to them by the chatbot less. These effects were more evident for participants who preferred to share their rides using WhatsApp compared to participants who preferred chatbots for that purpose. Considering our findings, we can say that the WhatsAppization of the chatbot was detrimental. This is true for the both chatbot WhatsAppization methods – by making the conversation more a dialog and adding WhatsApp indicators. For the chosen drive-sharing task, the results were, in addition to lower satisfaction, less trust in the chatbot’s suggestion and even in the driver suggested by the chatbot, and lower willingness to actually undertake the suggested ride. In addition, it seems that the most problematic WhatsAppization method was using WhatsApp’s indicators during the interaction with the chatbot. The current study suggests that a conversation with an artificial agent should also not imitate a WhatsApp conversation very closely. With the proliferation of WhatsApp use, the emotional and social aspect of face-to face commination are moving to WhatsApp communication. Based on the current study’s findings, it is possible that the UV effect also occurs in WhatsAppization, and not only in humanization, of the chatbot, with a similar feeling of eeriness, and is more pronounced for people who prefer to use WhatsApp over chatbots. The current research can serve as a starting point to study the very interesting and important topic of chatbots WhatsAppization. More methods of WhatsAppization and other tasks could be the focus of further studies.

Keywords: chatbot, WhatsApp, humanization, Uncanny Valley, drive sharing

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

Procedia PDF Downloads 124

Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: Ayola D. N. Jayamaha, Gihan V. Dias, Surangika Ranathunga

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Currently there are lot of educational tools designed for mathematics. Open source software such as GeoGebra and Octave are bulky in their architectural structure. In addition, there is MathLab software, which facilitates much more than what we ask for. Many of the computer aided online grading and assessment tools require integrating editors to their software. However, there are not exist suitable editors that cater for all their needs in editing equations and geometrical diagrams and graphs. Some of the existing software for editing equations is Alfred’s Equation Editor, Codecogs, DragMath, Maple, MathDox, MathJax, MathMagic, MathFlow, Math-o-mir, Microsoft Equation Editor, MiraiMath, OpenOffice, WIRIS Editor and MyScript. Some of them are commercial, open source, supports handwriting recognition, mobile apps, renders MathML/LaTeX, Flash / Web based and javascript display engines. Some of the diagram editors are GeoKone.NET, Tabulae, Cinderella 1.4, MyScript, Dia, Draw2D touch, Gliffy, GeoGebra, Flowchart, Jgraph, JointJS, J painter Online diagram editor and 2D sketcher. All these software are open source except for MyScript and can be used for editing mathematical diagrams. However, they do not fully cater the needs of a typical computer aided assessment tool or Educational Platform for Mathematics. This solution provides a Web based, lightweight, easy to implement and integrate solution of an html5 canvas that renders on all of the modern web browsers. The scope of the project is an editor that covers equations and mathematical diagrams and drawings on the O/L Mathematical Exam Papers in Sri Lanka. Using the tool the students can enter any equation to the system which can be on an online remote learning platform. The users can also create and edit geometrical drawings, graphs and do geometrical constructions that require only Compass and Ruler from the Editing Interface provided by the Software. The special feature of this software is the geometrical constructions. It allows the users to create geometrical constructions such as angle bisectors, perpendicular lines, angles of 600 and perpendicular bisectors. The tool correctly imitates the functioning of rulers and compasses to create the required geometrical construction. Therefore, the users are able to do geometrical drawings on the computer successfully and we have a digital format of the geometrical drawing for further processing. Secondly, we can create and edit Venn Diagrams, color them and label them. In addition, the students can draw probability tree diagrams and compound probability outcome grids. They can label and mark regions within the grids. Thirdly, students can draw graphs (1st order and 2nd order). They can mark points on a graph paper and the system connects the dots to draw the graph. Further students are able to draw standard shapes such as circles and rectangles by selecting points on a grid or entering the parametric values.

Keywords: geometrical drawings, html5 canvas, mathematical equations, toolbox

Procedia PDF Downloads 374

Authors: Beatriz Rebocho, Elisabete Valente, Carla Palma, Andreia Guilherme, Filipa Bessa, Paula Sobral

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The global accumulation of plastic in the oceans is a growing problem. Plastic is transported from its source to the oceans via rivers, which are considered the main route for plastic particles from land-based sources to the ocean. These plastics undergo physical and chemical degradation resulting in microplastics. The i-Plastic project aims to understand and predict the dispersion, accumulation and impacts of microplastics (5 mm to 1 µm) and nano plastics (below 1 µm) in marine environments from the tropical and temperate land-ocean interface to the open ocean under distinct flow and climate regimes. Seasonal monitoring of the fluxes of microplastics was carried out in (three) coastal areas in Brazil, Portugal and Spain. The present work shows the first results of in-situ seasonal monitoring and mapping of microplastics in ocean waters between Ovar and Vieira de Leiria (Portugal), in which 43 surface water samples and 43 water column samples were collected in contrasting seasons (spring and autumn). The spring and autumn surface water samples were collected with a 300 µm and 150 µm pore neuston net, respectively. In both campaigns, water column samples were collected using a conical mesh with a 150 µm pore. The experimental procedure comprises the following steps: i) sieving by a metal sieve; ii) digestion with potassium hydroxide to remove the organic matter original from the sample matrix. After a filtration step, the content is retained on a membrane and observed under a stereomicroscope, and physical and chemical characterization (type, color, size, and polymer composition) of the microparticles is performed. Results showed that 84% and 88% of the surface water and water column samples were contaminated with microplastics, respectively. Surface water samples collected during the spring campaign averaged 0.35 MP.m-3, while surface water samples collected during autumn recorded 0.39 MP.m-3. Water column samples from the spring campaign had an average of 1.46 MP.m-3, while those from the autumn recorded 2.54 MP.m-3. In the spring, all microplastics found were fibers, predominantly black and blue. In autumn, the dominant particles found in the surface waters were fibers, while in the water column, fragments were dominant. In spring, the average size of surface water particles was 888 μm, while in the water column was 1063 μm. In autumn, the average size of surface and water column microplastics was 1333 μm and 1393 μm, respectively. The main polymers identified by Attenuated Total Reflectance (ATR) and micro-ATR Fourier Transform Infrared (FTIR) spectroscopy from all samples were low-density polyethylene (LDPE), polypropylene (PP), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The significant difference between the microplastic concentration in the water column between the two campaigns could be due to the remixing of the water masses that occurred that week due to the occurrence of a storm. This work presents preliminary results since the i-Plastic project is still in progress. These results will contribute to the understanding of the spatial and temporal dispersion and accumulation of microplastics in this marine environment.

Keywords: microplastics, Portugal, Atlantic Ocean, water column, surface water

Procedia PDF Downloads 80

Authors: Behnaz Baghaei, Mikael Skrifvars

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Sustainability is today a trend that is seen everywhere, with no exception for the textiles 31 industry. However, there is a rather significant downside regarding how the textile industry currently operates, namely the huge amount of end-of-life textiles coming along with it. Approximately 73% of the 53 million tonnes of fibres used annually for textile production is landfilled or incinerated, while only 12% is recycled as secondary products. Mechanical recycling of end-of-life textile fabrics into yarns and fabrics was before very common, but due to the low costs for virgin man-made fibres, the current textile material composition diversity, the fibre material quality variations and the high recycling costs this route is not feasible. Another way to decrease the ever-growing pile of textile waste is to repurpose the textile. If a feasible methodology can be found to reuse end-of life textiles as secondary market products including a manufacturing process that requires rather low investment costs, then this can be highly beneficial to counteract the increasing textile waste volumes. In structural composites, glass fibre textiles are used as reinforcements, but today there is a growing interest in biocomposites where the reinforcement and/or the resin are from a biomass resource. All-cellulose composites (ACCs) are monocomponent or single polymer composites, and they are entirely made from cellulose, ideally leading to a homogeneous biocomposite. Since the matrix and the reinforcement are both made from cellulose, and therefore chemically identical, they are fully compatible with each other which allow efficient stress transfer and adhesion at their interface. Apart from improving the mechanical performance of the final products, the recycling of the composites will be facilitated. This paper reports the recycling of end-of-life cellulose containing textiles by fabrication of all-cellulose composites (ACCs). Composite laminates were prepared by using an ionic liquid (IL) in a hot process, involving a partial dissolving of the cellulose fibres. Discharged denim fabrics were used as the reinforcement while dissolved cellulose from two different cellulose resources was used as the matrix phase. Virgin cotton staple fibres and recovered cotton from polyester/cotton (polycotton) waste fabrics were used to form the matrix phase. The process comprises the dissolving 6 wt.% cellulose solution in the ionic liquid 1-butyl-3-methyl imidazolium acetate ([BMIM][Ac]), this solution acted as a precursor for the matrix component. The denim fabrics were embedded in the cellulose/IL solution after which laminates were formed, which also involved removal of the IL by washing. The effect of reuse of the recovered IL was also investigated. The mechanical properties of the obtained ACCs were determined regarding tensile, impact and flexural properties. Mechanical testing revealed that there are no clear differences between the values measured for mechanical strength and modulus of the manufactured ACCs from denim/cotton-fresh IL, denim/recovered cotton-fresh IL and denim/cotton-recycled IL. This could be due to the low weight fraction of the cellulose matrix in the final ACC laminates and presumably the denim as cellulose reinforcement strongly influences and dominates the mechanical properties. Fabricated ACC composite laminates were further characterized regarding scanning electron microscopy.

Keywords: all-cellulose composites, denim fabrics, ionic liquid, mechanical properties

Procedia PDF Downloads 117

Authors: Animesh Pan, Geoffrey D. Bothun

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With the development of nanotechnology, research in multifunctional delivery systems has a new pace and dimension. An incipient challenge is to design an all-in-one delivery system that can be used for multiple purposes, including tumor targeting therapy, radio-frequency (RF-), near-infrared (NIR-), light-, or pH-induced controlled release, photothermal therapy (PTT), photodynamic therapy (PDT), and medical diagnosis. In this regard, various inorganic nanoparticles (NPs) are known to show great potential as the 'functional components' because of their fascinating and tunable physicochemical properties and the possibility of multiple theranostic modalities from individual NPs. Magnetic, luminescent, and plasmonic properties are the three most extensively studied and, more importantly biomedically exploitable properties of inorganic NPs. Although successful attempts of combining any two of them above mentioned functionalities have been made, integrating them in one system has remained challenge. Keeping those in mind, controlled designs of complex colloidal nanoparticle system are one of the most significant challenges in nanoscience and nanotechnology. Therefore, systematic and planned studies providing better revelation are demanded. We report a multifunctional delivery platform-based liposome loaded with drug, iron-oxide magnetic nanoparticles (MNPs), and a gold shell on the surface of liposomes, were synthesized using a lipid with polyelectrolyte (layersomes) templating technique. MNPs and the anti-cancer drug doxorubicin (DOX) were co-encapsulated inside liposomes composed by zwitterionic phophatidylcholine and anionic phosphatidylglycerol using reverse phase evaporation (REV) method. The liposomes were coated with positively charge polyelectrolyte (poly-L-lysine) to enrich the interface with gold anion, exposed to a reducing agent to form a gold nanoshell, and then capped with thio-terminated polyethylene glycol (SH-PEG2000). The core-shell nanostructures were characterized by different techniques like; UV-Vis/NIR scanning spectrophotometer, dynamic light scattering (DLS), transmission electron microscope (TEM). This multifunctional system achieves a variety of functions, such as radiofrequency (RF)-triggered release, chemo-hyperthermia, and NIR laser-triggered for photothermal therapy. Herein, we highlight some of the remaining major design challenges in combination with preliminary studies assessing therapeutic objectives. We demonstrate an efficient loading and delivery system to significant cell death of human cancer cells (A549) with therapeutic capabilities. Coupled with RF and NIR excitation to the doxorubicin-loaded core-shell nanostructure helped in securing targeted and controlled drug release to the cancer cells. The present core-shell multifunctional system with their multimodal imaging and therapeutic capabilities would be eminent candidates for cancer theranostics.

Keywords: cancer thernostics, multifunctional nanostructure, photothermal therapy, radiofrequency targeting

Procedia PDF Downloads 126

Authors: Tomofumi Kubota, Mitsuhiro Okayasu

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In recent years, environmental problems and energy problems typified by global warming are intensifying, and transportation devices are required to reduce the weight of structural materials from the viewpoint of strengthening fuel efficiency regulations and energy saving. Carbon fiber reinforced plastic (CFRP) used in this research is attracting attention as a structural material to replace metallic materials. Among them, thermoplastic CFRP is expected to expand its application range in terms of recyclability and cost. High formability and weldability of the unidirectional CFRP sheets conducted by a proposed hot stamping process were proposed, in which the carbon fiber reinforced plastic sheets are heated by a designed technique. In this case, the CFRP sheets are heated by the high electric voltage applied through carbon fibers. In addition, the electric voltage was controlled by the area ratio of exposed carbon fiber on the sample surfaces. The lower exposed carbon fiber on the sample surface makes high electric resistance leading to the high sample temperature. In this case, the CFRP sheets can be heated to more than 150 °C. With the sample heating, the stamping and welding technologies can be carried out. By changing the sample temperature, the suitable stamping condition can be detected. Moreover, the proper welding connection of the CFRP sheets was proposed. In this study, we propose a fusion bonding technique using thermoplasticity, high current flow, and heating caused by electrical resistance. This technology uses the principle of resistance spot welding. In particular, the relationship between the carbon fiber exposure rate and the electrical resistance value that affect the bonding strength is investigated. In this approach, the mechanical connection using rivet is also conducted to make a comparison of the severity of welding. The change of connecting strength is reflected by the fracture mechanism. The low and high connecting strength are obtained for the separation of two CFRP sheets and fractured inside the CFRP sheet, respectively. In addition to the two fracture modes, micro-cracks in CFRP are also detected. This approach also includes mechanical connections using rivets to compare the severity of the welds. The change in bond strength is reflected by the destruction mechanism. Low and high bond strengths were obtained to separate the two CFRP sheets, each broken inside the CFRP sheets. In addition to the two failure modes, micro cracks in CFRP are also detected. In this research, from the relationship between the surface carbon fiber ratio and the electrical resistance value, it was found that different carbon fiber ratios had similar electrical resistance values. Therefore, we investigated which of carbon fiber and resin is more influential to bonding strength. As a result, the lower the carbon fiber ratio, the higher the bonding strength. And this is 50% better than the conventional average strength. This can be evaluated by observing whether the fracture mode is interface fracture or internal fracture.

Keywords: CFRP, hot stamping, weliding, deforamtion, mechanical property

Procedia PDF Downloads 124

Authors: R. Tamborrino, F. Rinaudo

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Digital technologies offer possibilities to effectively convert historical archives into instruments of knowledge able to provide a guide for the interpretation of historical phenomena. Digital conversion and management of those documents allow the possibility to add other sources in a unique and coherent model that permits the intersection of different data able to open new interpretations and understandings. Urban history uses, among other sources, the inventories that register human activities in a specific space (e.g. cadastres, censuses, etc.). The geographic localisation of that information inside cartographic supports allows for the comprehension and visualisation of specific relationships between different historical realities registering both the urban space and the peoples living there. These links that merge the different nature of data and documentation through a new organisation of the information can suggest a new interpretation of other related events. In all these kinds of analysis, the use of GIS platforms today represents the most appropriate answer. The design of the related databases is the key to realise the ad-hoc instrument to facilitate the analysis and the intersection of data of different origins. Moreover, GIS has become the digital platform where it is possible to add other kinds of data visualisation. This research deals with the industrial development of Turin at the beginning of the 20th century. A census of factories realized just prior to WWI provides the opportunity to test the potentialities of GIS platforms for the analysis of urban landscape modifications during the first industrial development of the town. The inventory includes data about location, activities, and people. GIS is shaped in a creative way linking different sources and digital systems aiming to create a new type of platform conceived as an interface integrating different kinds of data visualisation. The data processing allows linking this information to an urban space, and also visualising the growth of the city at that time. The sources, related to the urban landscape development in that period, are of a different nature. The emerging necessity to build, enlarge, modify and join different buildings to boost the industrial activities, according to their fast development, is recorded by different official permissions delivered by the municipality and now stored in the Historical Archive of the Municipality of Turin. Those documents, which are reports and drawings, contain numerous data on the buildings themselves, including the block where the plot is located, the district, and the people involved such as the owner, the investor, and the engineer or architect designing the industrial building. All these collected data offer the possibility to firstly re-build the process of change of the urban landscape by using GIS and 3D modelling technologies thanks to the access to the drawings (2D plans, sections and elevations) that show the previous and the planned situation. Furthermore, they access information for different queries of the linked dataset that could be useful for different research and targets such as economics, biographical, architectural, or demographical. By superimposing a layer of the present city, the past meets to the present-industrial heritage, and people meet urban history.

Keywords: digital urban history, census, digitalisation, GIS, modelling, digital humanities

Procedia PDF Downloads 190

Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

Procedia PDF Downloads 128

Authors: J. Martin, A. Nominé, T. Czerwiec, G. Henrion, T. Belmonte

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The plasma electrolytic oxidation (PEO) is a particular electrochemical process to produce protective oxide ceramic coatings on light-weight metals (Al, Mg, Ti). When applied to aluminum alloys, the resulting PEO coating exhibit improved wear and corrosion resistance because thick, hard, compact and adherent crystalline alumina layers can be achieved. Several investigations have been carried out to improve the efficiency of the PEO process and one particular way consists in tuning the suitable electrical regime. Despite the considerable interest in this process, there is still no clear understanding of the underlying discharge mechanisms that make possible metal oxidation up to hundreds of µm through the ceramic layer. A key parameter that governs the PEO process is the numerous short-lived micro-discharges (micro-plasma in liquid) that occur continuously over the processed surface when the high applied voltage exceeds the critical dielectric breakdown value of the growing ceramic layer. By using a bipolar pulsed current to supply the electrodes, we previously observed that micro-discharges are delayed with respect to the rising edge of the anodic current. Nevertheless, explanation of the origin of such phenomena is still not clear and needs more systematic investigations. The aim of the present communication is to identify the relationship that exists between this delay and the mechanisms responsible of the oxide growth. For this purpose, the delay of micro-discharges ignition is investigated as the function of various electrical parameters such as the current density (J), the current pulse frequency (F) and the anodic to cathodic charge quantity ratio (R = Qp/Qn) delivered to the electrodes. The PEO process was conducted on Al2214 aluminum alloy substrates in a solution containing potassium hydroxide [KOH] and sodium silicate diluted in deionized water. The light emitted from micro-discharges was detected by a photomultiplier and the micro-discharge parameters (number, size, life-time) were measured during the process by means of ultra-fast video imaging (125 kfr./s). SEM observations and roughness measurements were performed to characterize the morphology of the elaborated oxide coatings while XRD was carried out to evaluate the amount of corundum -Al203 phase. Results show that whatever the applied current waveform, the delay of micro-discharge appearance increases as the process goes on. Moreover, the delay is shorter when the current density J (A/dm2), the current pulse frequency F (Hz) and the ratio of charge quantity R are high. It also appears that shorter delays are associated to stronger micro-discharges (localized, long and large micro-discharges) which have a detrimental effect on the elaborated oxide layers (thin and porous). On the basis of the results, a model for the growth of the PEO oxide layers will be presented and discussed. Experimental results support that a mechanism of electrical charge accumulation at the oxide surface / electrolyte interface takes place until the dielectric breakdown occurs and thus until micro-discharges appear.

Keywords: aluminium, micro-discharges, oxidation mechanisms, plasma electrolytic oxidation

Procedia PDF Downloads 262

Authors: Hari Krishan Sharma, Sanjay Kumar Sharma, Sushil Kumar Swar

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Inadequate transverse reinforcement is considered as the main reason for the beam column joint shear failure observed during recent earthquakes. DSP matrix consists of cement and high content of micro-silica with low water to cement ratio while the aggregates are graded quartz sand. The use of reinforcing fibres leads not only to the increase of tensile/bending strength and specific fracture energy, but also to reduction of brittleness and, consequently, to production of non-explosive ruptures. Besides, fibre-reinforced materials are more homogeneous and less sensitive to small defects and flaws. Recent works on the freeze-thaw durability (also in the presence of de-icing salts) of fibre-reinforced DSP confirm the excellent behaviour in the expected long term service life.DSP materials, including fibre-reinforced DSP and CRC (Compact Reinforced Composites) are obtained by using high quantities of super plasticizers and high volumes of micro-silica. Steel fibres with high tensile yield strength of smaller diameter and short length in different fibre volume percentage and aspect ratio tilized to improve the performance by reducing the brittleness of matrix material. In the case of High Performance Densified Small Particle Concrete (HPDSPC), concrete is dense at the micro-structure level, tensile strain would be much higher than that of the conventional SFRC, SIFCON & SIMCON. Beam-column sub-assemblages used as moment resisting constructed using HPDSPC in the joint region with varying quantities of steel fibres, fibre aspect ratio and fibre orientation in the critical section. These HPDSPC in the joint region sub-assemblages tested under cyclic/earthquake loading. Besides loading measurements, frame displacements, diagonal joint strain and rebar strain adjacent to the joint will also be measured to investigate stress-strain behaviour, load deformation characteristics, joint shear strength, failure mechanism, ductility associated parameters, stiffness and energy dissipated parameters of the beam column sub-assemblages also evaluated. Finally a design procedure for the optimum design of HPDSPC corresponding to moment, shear forces and axial forces for the reinforced concrete beam-column joint sub-assemblage proposed. The fact that the implementation of material brittleness measure in the design of RC structures can improve structural reliability by providing uniform safety margins over a wide range of structural sizes and material compositions well recognized in the structural design and research. This lead to the development of high performance concrete for the optimized combination of various structural ratios in concrete for the optimized combination of various structural properties. The structural applications of HPDSPC, because of extremely high strength, will reduce dead load significantly as compared to normal weight concrete thereby offering substantial cost saving and by providing improved seismic response, longer spans, and thinner sections, less reinforcing steel and lower foundation cost. These cost effective parameters will make this material more versatile for use in various structural applications like beam-column joints in industries, airports, parking areas, docks, harbours, and also containers for hazardous material, safety boxes and mould & tools for polymer composites and metals.

Keywords: high performance densified small particle concrete (HPDSPC), steel fibre reinforced concrete (SFRC), slurry infiltrated concrete (SIFCON), Slurry infiltrated mat concrete (SIMCON)

Procedia PDF Downloads 301

Authors: Ashish Thakur

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This technical paper was written in view of focusing the biomaterials and its various applications in modern industries. Author tires to elaborate not only the medical, infect plenty of application in other industries. The scope of the research area covers the wide range of physical, biological and chemical sciences that underpin the design of biomaterials and the clinical disciplines in which they are used. A biomaterial is now defined as a substance that has been engineered to take a form which, alone or as part of a complex system, is used to direct, by control of interactions with components of living systems, the course of any therapeutic or diagnostic procedure. Biomaterials are invariably in contact with living tissues. Thus, interactions between the surface of a synthetic material and biological environment must be well understood. This paper reviews the benefits and challenges associated with surface modification of the metals in biomedical applications. The paper also elaborates how the surface characteristics of metallic biomaterials, such as surface chemistry, topography, surface charge, and wettability, influence the protein adsorption and subsequent cell behavior in terms of adhesion, proliferation, and differentiation at the biomaterial–tissue interface. The chapter also highlights various techniques required for surface modification and coating of metallic biomaterials, including physicochemical and biochemical surface treatments and calcium phosphate and oxide coatings. In this review, the attention is focused on the biomaterial-associated infections, from which the need for anti-infective biomaterials originates. Biomaterial-associated infections differ markedly for epidemiology, aetiology and severity, depending mainly on the anatomic site, on the time of biomaterial application, and on the depth of the tissues harbouring the prosthesis. Here, the diversity and complexity of the different scenarios where medical devices are currently utilised are explored, providing an overview of the emblematic applicative fields and of the requirements for anti-infective biomaterials. In addition to this, chapter introduces nanomedicine and the use of both natural and synthetic polymeric biomaterials, focuses on specific current polymeric nanomedicine applications and research, and concludes with the challenges of nanomedicine research. Infection is currently regarded as the most severe and devastating complication associated to the use of biomaterials. Osteoporosis is a worldwide disease with a very high prevalence in humans older than 50. The main clinical consequences are bone fractures, which often lead to patient disability or even death. A number of commercial biomaterials are currently used to treat osteoporotic bone fractures, but most of these have not been specifically designed for that purpose. Many drug- or cell-loaded biomaterials have been proposed in research laboratories, but very few have received approval for commercial use. Polymeric nanomaterial-based therapeutics plays a key role in the field of medicine in treatment areas such as drug delivery, tissue engineering, cancer, diabetes, and neurodegenerative diseases. Advantages in the use of polymers over other materials for nanomedicine include increased functionality, design flexibility, improved processability, and, in some cases, biocompatibility.

Keywords: nanomedicine, tissue, infections, biomaterials

Procedia PDF Downloads 263

Authors: Ramesh P., Aby Joseph

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Micro Inverters provide Module Embedded Solution for harvesting energy from small-scale solar photovoltaic (PV) panels. In addition to higher modularity & reliability (25 years of life), the MicroInverter has inherent advantages such as avoidance of long DC cables, eliminates module mismatch losses, minimizes partial shading effect, improves safety and flexibility in installations etc. Due to the above-stated benefits, the renewable energy technology with Solar Photovoltaic (PV) Micro Inverter becomes more widespread in Village Nano Grid application ensuring grid independence for rural communities and areas without access to electricity. While the primary objective of this paper is to discuss the problems related to rural electrification, this concept can also be extended to urban installation with grid connectivity. This work presents a comprehensive analysis of the power circuit design, control methodologies and prototyping of 300Wₚ Single Phase PV Micro Inverter. This paper investigates two different topologies for PV Micro Inverters, based on the first hand on Single Stage Flyback/ Forward PV Micro-Inverter configuration and the other hand on the Double stage configuration including DC-DC converter, H bridge DC-AC Inverter. This work covers Power Decoupling techniques to reduce the input filter capacitor size to buffer double line (100 Hz) ripple energy and eliminates the use of electrolytic capacitors. The propagation of the double line oscillation reflected back to PV module will affect the Maximum Power Point Tracking (MPPT) performance. Also, the grid current will be distorted. To mitigate this issue, an independent MPPT control algorithm is developed in this work to reject the propagation of this double line ripple oscillation to PV side to improve the MPPT performance and grid side to improve current quality. Here, the power hardware topology accepts wide input voltage variation and consists of suitably rated MOSFET switches, Galvanically Isolated gate drivers, high-frequency magnetics and Film capacitors with a long lifespan. The digital controller hardware platform inbuilt with the external peripheral interface is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the PV Micro Inverter is written in C language and was developed using code composer studio Integrated Development Environment (IDE). In this work, the prototype hardware for the Single Phase Photovoltaic Micro Inverter with Double stage configuration was developed and the comparative analysis between the above mentioned configurations with experimental results will be presented.

Keywords: double line oscillation, micro inverter, MPPT, nano grid, power decoupling

Procedia PDF Downloads 133

Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein

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Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.

Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes

Procedia PDF Downloads 244

Authors: Anwar Beg, Sireetorn Kuharat, Rashid Mehmood, Rabil Tabassum, Meisam Babaie

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Nano-polymeric solar paints and sol-gels have emerged as a major new development in solar cell/collector coatings offering significant improvements in durability, anti-corrosion and thermal efficiency. They also exhibit substantial viscosity variation with temperature which can be exploited in solar collector designs. Modern manufacturing processes for such nano-rheological materials frequently employ stagnation flow dynamics under high temperature which invokes radiative heat transfer. Motivated by elaborating in further detail the nanoscale heat, mass and momentum characteristics of such sol gels, the present article presents a mathematical and computational study of the steady, two-dimensional, non-aligned thermo-fluid boundary layer transport of copper metal-doped water-based nano-polymeric sol gels under radiative heat flux. To simulate real nano-polymer boundary interface dynamics, thermal slip is analysed at the wall. A temperature-dependent viscosity is also considered. The Tiwari-Das nanofluid model is deployed which features a volume fraction for the nanoparticle concentration. This approach also features a Maxwell-Garnet model for the nanofluid thermal conductivity. The conservation equations for mass, normal and tangential momentum and energy (heat) are normalized via appropriate transformations to generate a multi-degree, ordinary differential, non-linear, coupled boundary value problem. Numerical solutions are obtained via the stable, efficient Runge-Kutta-Fehlberg scheme with shooting quadrature in MATLAB symbolic software. Validation of solutions is achieved with a Variational Iterative Method (VIM) utilizing Langrangian multipliers. The impact of key emerging dimensionless parameters i.e. obliqueness parameter, radiation-conduction Rosseland number (Rd), thermal slip parameter (α), viscosity parameter (m), nanoparticles volume fraction (ϕ) on non-dimensional normal and tangential velocity components, temperature, wall shear stress, local heat flux and streamline distributions is visualized graphically. Shear stress and temperature are boosted with increasing radiative effect whereas local heat flux is reduced. Increasing wall thermal slip parameter depletes temperatures. With greater volume fraction of copper nanoparticles temperature and thermal boundary layer thickness is elevated. Streamlines are found to be skewed markedly towards the left with positive obliqueness parameter.

Keywords: non-orthogonal stagnation-point heat transfer, solar nano-polymer coating, MATLAB numerical quadrature, Variational Iterative Method (VIM)

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Authors: Antonia Egli, Theo Lynn, Pierangelo Rosati, Gary Sinclair

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The World Health Organization (WHO) defines vaccine hesitancy as the postponement or complete denial of vaccines and estimates a direct linkage to approximately 1.5 million avoidable deaths annually. This figure is not immune to public health developments, as has become evident since the global spread of COVID-19 from Wuhan, China in early 2020. Since then, the proliferation of influential, but oftentimes inaccurate, outdated, incomplete, or false vaccine-related information on social media has impacted hesitancy levels to a degree described by the WHO as an infodemic. The COVID-19 pandemic and related vaccine hesitancy levels have in 2022 resulted in the largest drop in childhood vaccinations of the 21st century, while the prevalence of online stigma towards vaccine hesitant consumers continues to grow. Simultaneously, a second disease has risen to global importance: Monkeypox is an infection originating from west and central Africa and, due to racially motivated online hate, was in August 2022 set to be renamed by the WHO. To better understand public reactions towards two viral infections that became global threats to public health no two years apart, this research examines user replies to threads published by the WHO on Twitter. Replies to two Tweets from the @WHO account declaring COVID-19 and Monkeypox as ‘public health emergencies of international concern’ on January 30, 2020, and July 23, 2022, are gathered using the Twitter application programming interface and user mention timeline endpoint. Research methodology is unique in its analysis of stigmatizing, racist, and hateful content shared on social media within the vaccine discourse over the course of two disease outbreaks. Three distinct analyses are conducted to provide insight into (i) the most prevalent topics and sub-topics among user reactions, (ii) changes in sentiment towards the spread of the two diseases, and (iii) the presence of stigma, racism, and online hate. Findings indicate an increase in hesitancy to accept further vaccines and social distancing measures, the presence of stigmatizing content aimed primarily at anti-vaccine cohorts and racially motivated abusive messages, and a prevalent fatigue towards disease-related news overall. This research provides value to non-profit organizations or government agencies associated with vaccines and vaccination programs in emphasizing the need for public health communication fitted to consumers' vaccine sentiments, levels of health information literacy, and degrees of trust towards public health institutions. Considering the importance of addressing fears among the vaccine hesitant, findings also illustrate the risk of alienation through stigmatization, lead future research in probing the relatively underexamined field of online, vaccine-related stigma, and discuss the potential effects of stigma towards vaccine hesitant Twitter users in their decisions to vaccinate.

Keywords: social marketing, social media, public health communication, vaccines

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Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

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Authors: António J. Gano, Carmen Rangel

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Currently, electric energy storage systems for stationary applications have known an increasing interest, namely with the integration of local renewable energy power sources into energy communities. Li-ion batteries are considered the leading electric storage devices to achieve this integration, and Battery Management Systems (BMS) are decisive for their control and optimum performance. In this work, the advancement of a smart BMS (sBMS) prototype with a modular distributed topology is described. The system, still under development, has a distributed architecture with modular characteristics to operate with different battery pack topologies and charge capacities, integrating adaptive algorithms for functional state real-time monitoring and management of multicellular Li-ion batteries, and is intended for application in the context of a local energy community fed by renewable energy sources. This sBMS system includes different developed hardware units: (1) Cell monitoring units (CMUs) for interfacing with each individual cell or module monitoring within the battery pack; (2) Battery monitoring and switching unit (BMU) for global battery pack monitoring, thermal control and functional operating state switching; (3) Main management and local control unit (MCU) for local sBMS’s management and control, also serving as a communications gateway to external systems and devices. This architecture is fully expandable to battery packs with a large number of cells, or modules, interconnected in series, as the several units have local data acquisition and processing capabilities, communicating over a standard CAN bus and will be able to operate almost autonomously. The CMU units are intended to be used with Li-ion cells but can be used with other cell chemistries, with output voltages within the 2.5 to 5 V range. The different unit’s characteristics and specifications are described, including the different implemented hardware solutions. The developed hardware supports both passive and active methods for charge equalization, considered fundamental functionalities for optimizing the performance and the useful lifetime of a Li-ion battery package. The functional characteristics of the different units of this sBMS system, including different process variables data acquisition using a flexible set of sensors, can support the development of custom algorithms for estimating the parameters defining the functional states of the battery pack (State-of-Charge, State-of-Health, etc.) as well as different charge equalizing strategies and algorithms. This sBMS system is intended to interface with other systems and devices using standard communication protocols, like those used by the Internet of Things. In the future, this sBMS architecture can evolve to a fully decentralized topology, with all the units using Wi-Fi protocols and integrating a mesh network, making unnecessary the MCU unit. The status of the work in progress is reported, leading to conclusions on the system already executed, considering the implemented hardware solution, not only as fully functional advanced and configurable battery management system but also as a platform for developing custom algorithms and optimizing strategies to achieve better performance of electric energy stationary storage devices.

Keywords: Li-ion battery, smart BMS, stationary electric storage, distributed BMS

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Authors: Aleksandra Boldyreva, Alexander Golubnichiy, Artem Abakumov

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Various perovskite materials have surprisingly high resistance towards high-energy electrons, protons, and hard ionization, such as X-rays and gamma-rays. Superior radiation hardness makes a family of perovskite semiconductors an attractive candidate for single- and multijunction solar cells for the space environment and as X-ray and gamma-ray detectors. One of the methods to study the radiation hardness of different materials is by exposing them to gamma photons with high energies (above 500 keV) Herein, we have explored the recombination dynamics and defect concentration of a mixed cation mixed halide perovskite Cs0.17FA0.83PbI1.8Br1.2 with 1.74 eV bandgap after exposure to a gamma-ray source (2.5 Gy/min). We performed an advanced STEM EDX analysis to reveal different types of defects formed during gamma exposure. It was found that 10 kGy dose results in significant improvement of perovskite crystallinity and homogeneous distribution of I ions. While the absorber layer withstood gamma exposure, the hole transport layer (PTAA) as well as indium tin oxide (ITO) were significantly damaged, which increased the interface recombination rate and reduction of fill factor in solar cells. Thus, STEM analysis is a powerful technique that can reveal defects formed by gamma exposure in perovskite solar cells. Methods: Data will be collected from perovskite solar cells (PSCs) and thin films exposed to gamma ionisator. For thin films 50 μL of the Cs0.17FA0.83PbI1.8Br1.2 solution in DMF was deposited (dynamically) at 3000 rpm followed by quenching with 100 μL of ethyl acetate (dropped 10 sec after perovskite precursor) applied at the same spin-coating frequency. The deposited Cs0.17FA0.83PbI1.8Br1.2 films were annealed for 10 min at 100 °C, which led to the development of a dark brown color. For the solar cells, 10% suspension of SnO2 nanoparticles (Alfa Aesar) was deposited at 4000 rpm, followed by annealing on air at 170 ˚C for 20 min. Next, samples were introduced into a nitrogen glovebox for the deposition of all remaining layers. Perovskite film was applied in the same way as in thin films described earlier. Solution of poly-triaryl amine PTAA (Sigma Aldrich) (4 mg in chlorobenzene) was applied at 1000 rpm atop of perovskite layer. Next, 30 nm of VOx was deposited atop the PTAA layer on the whole sample surface using the physical vapor deposition (PVD) technique. Silver electrodes (100 nm) were evaporated in a high vacuum (10-6 mbar) through a shadow mask, defining the active area of each device as ~0.16 cm2. The prepared samples (thin films and solar cells) were packed in Al lamination foil inside the argon glove box. The set of samples consisted of 6 thin films and 6 solar cells, which were exposed to 6, 10, and 21 kGy (2 samples per dose) with 137Cs gamma-ray source (E = 662 keV) with a dose rate of 2.5 Gy/min. The exposed samples will be studied on a focused ion beam (FIB) on a dual-beam scanning electron microscope from ThermoFisher, the Helios G4 Plasma FIB Uxe, operating with a xenon plasma.

Keywords: perovskite solar cells, transmission electron microscopy, radiation hardness, gamma irradiation

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Authors: Md. Samsuddin Ansari, Ashish Arora

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Every year 10 million people fall ill with one of the oldest diseases known as tuberculosis, caused by Mycobacterium tuberculosis. The success of M. tuberculosis as a pathogen is because of its ability to persist in host tissues. Multidrug resistance (MDR) mycobacteria cases increase every day, which is associated with efflux pumps controlled at the level of transcription. The transcription regulators of MDR transporters in bacteria belong to one of the following four regulatory protein families: AraC, MarR, MerR, and TetR. Phenolic acid decarboxylase repressor (PadR), like a family of transcription regulators, is closely related to the MarR family. Phenolic acid decarboxylase repressor (PadR) was first identified as a transcription factor involved in the regulation of phenolic acid stress response in various microorganisms (including Mycobacterium tuberculosis H37Rv). Recently research has shown that the PadR family transcription factors are global, multifunction transcription regulators. Rv0047c is a PadR subfamily-1 protein. We are exploring the biophysical and structural characterization of Rv0047c. The Rv0047 gene was amplified by PCR using the primers containing EcoRI and HindIII restriction enzyme sites cloned in pET-NH6 vector and overexpressed in DH5α and BL21 (λDE3) cells of E. coli following purification with Ni2+-NTA column and size exclusion chromatography. We did DSC to know the thermal stability; the Tm (transition temperature) of protein is 55.29ºC, and ΔH (enthalpy change) of 6.92 kcal/mol. Circular dichroism to know the secondary structure and conformation and fluorescence spectroscopy for tertiary structure study of protein. To understand the effect of pH on the structure, function, and stability of Rv0047c we employed spectroscopy techniques such as circular dichroism, fluorescence, and absorbance measurements in a wide range of pH (from pH-2.0 to pH-12). At low and high pH, it shows drastic changes in the secondary and tertiary structure of the protein. EMSA studies showed the specific binding of Rv0047c with its own 30-bp promoter region. To determine the effect of complex formation on the secondary structure of Rv0047c, we examined the CD spectra of the complex of Rv0047c with promoter DNA of rv0047. The functional role of Rv0047c was characterized by over-expressing the Rv0047c gene under the control of hsp60 promoter in Mycobacterium tuberculosis H37Rv. We have predicted the three-dimensional structure of Rv0047c using the Swiss Model and Modeller, with validity checked by the Ramachandra plot. We did molecular docking of Rv0047c with dnaA, through PatchDock following refinement through FireDock. Through this, it is possible to easily identify the binding hot-stop of the receptor molecule with that of the ligand, the nature of the interface itself, and the conformational change undergone by the protein pattern. We are using X-crystallography to unravel the structure of Rv0047c. Overall the studies show that Rv0047c may have transcription regulation along with providing an insight into the activity of Rv0047c in the pH range of subcellular environment and helps to understand the protein-protein interaction, a novel target to kill dormant bacteria and potential strategy for tuberculosis control.

Keywords: mycobacterium tuberculosis, phenolic acid decarboxylase repressor, Rv0047c, Circular dichroism, fluorescence spectroscopy, docking, protein-protein interaction

Procedia PDF Downloads 119