Search results for: auto tuning

Authors: Katerina Koliou, Scott Parr, Evangelos Kaisar

Abstract:

The surface transportation of freight is particularly vulnerable to storm and hurricane disasters, while at the same time, it is the primary transportation mode for delivering medical supplies, fuel, water, and other essential goods. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The research investigation used Florida's statewide continuous-count station traffic volumes, where then compared between years, to identify locations where traffic was moving differently during the evacuation. The data was then used to identify days on which traffic was significantly different between years. While the literature on auto-based evacuations is extensive, the consideration of freight travel is lacking. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The goal of this research was to investigate the movement of vehicles by classification, with an emphasis on freight during two major evacuation events: hurricanes Irma (2017) and Michael (2018). The methodology of the research was divided into three phases: data collection and management, spatial analysis, and temporal comparisons. Data collection and management obtained continuous-co station data from the state of Florida for both 2017 and 2018 by vehicle classification. The data was then processed into a manageable format. The second phase used geographic information systems (GIS) to display where and when traffic varied across the state. The third and final phase was a quantitative investigation into which vehicle classifications were statistically different and on which dates statewide. This phase used a two-sample, two-tailed t-test to compare sensor volume by classification on similar days between years. Overall, increases in freight movement between years prevented a more precise paired analysis. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm reentry. Of the more significant findings, the research results showed that commercial-use vehicles may have underutilized rest areas during the evacuation, or perhaps these rest areas were closed. This may suggest that truckers are driving longer distances and possibly longer hours before hurricanes. Another significant finding of this research was that changes in traffic patterns for commercial-use vehicles occurred earlier and lasted longer than changes for personal-use vehicles. This finding suggests that commercial vehicles are perhaps evacuating in a fashion different from personal use vehicles. This paper may serve as the foundation for future research into commercial travel during evacuations and explore additional factors that may influence freight movements during evacuations.

Keywords: evacuation, freight, travel time, evacuation

Procedia PDF Downloads 56

Authors: Sh. Sousani, Z. Shadrokh, M. Hofbauerová, J. Kollár, M. Jergel, P. Nádaždy, M. Omastová, E. Majková

Abstract:

Perovskite quantum dots (PQDs) have the potential to increase the performance of the perovskite solar cell (PSCs). The integration of PQDs into PSCs can extend the absorption range and enhance photon harvesting and device efficiency. In addition, PQDs can stabilize the device structure by passivating surface defects and traps in the perovskite layer and enhance its stability. The integration of PQDs into PSCs is strongly affected by the type of ligands on the surface of PQDs. The ligands affect the charge transport properties of PQDs, as well as the formation of well-defined interfaces and stability of PSCs. In this work, the CsPbBr₃ QDs were synthesized by the conventional hot-injection method using cesium oleate, PbBr₂ and two different ligands, namely oleic acid (OA) oleylamine (OAm) and didodecyldimethylammonium bromide (DDAB). The STEM confirmed regular shape and relatively monodisperse cubic structure with an average size of about 10-14 nm of the prepared CsPbBr₃ QDs. Further, the photoluminescent (PL) properties of the PQDs/perovskite bilayer with the ligand OA, OAm and DDAB were studied. For this purpose, ITO/PQDs as well as ITO/PQDs/MAPI perovskite structures were prepared by spin coating and the effect of the ligand and oxygen plasma treatment was analyzed. The plasma treatment of the PQDs layer could be beneficial for the deposition of the MAPI perovskite layer and the formation of a well-defined PQDs/MAPI interface. The absorption edge in UV-Vis absorption spectra for OA, OAm CsPbBr₃ QDs is placed around 513 nm (the band gap 2.38 eV); for DDAB CsPbBr₃ QDs, it is located at 490 nm (the band gap 2.33 eV). The photoluminescence (PL) spectra of CsPbBr₃ QDs show two peaks located around 514 nm (503 nm) and 718 nm (708 nm) for OA, OAm (DDAB). The peak around 500 nm corresponds to the PL of PQDs, and the peak close to 710 nm belongs to the surface states of PQDs for both types of ligands. These surface states are strongly affected by the O₃ plasma treatment. For PQDs with DDAB ligand, the O₃ exposure (5, 10, 15 s) results in the blue shift of the PQDs peak and a non-monotonous change of the amplitude of the surface states' peak. For OA, OAm ligand, the O₃ exposition did not cause any shift of the PQDs peak, and the intensity of the PL peak related to the surface states is lower by one order of magnitude in comparison with DDAB, being affected by O₃ plasma treatment. The PL results indicate the possibility of tuning the position of the PL maximum by the ligand of the PQDs. Similar behavior of the PQDs layer was observed for the ITO/QDs/MAPI samples, where an additional strong PL peak at 770 nm coming from the perovskite layer was observed; for the sample with PQDs with DDAB ligands, a small blue shift of the perovskite PL maximum was observed independently of the plasma treatment. These results suggest the possibility of affecting the PL maximum position and the surface states of the PQDs by the combination of a suitable ligand and the O₃ plasma treatment.

Keywords: perovskite quantum dots, photoluminescence, O₃ plasma., Perovskite Solar Cells

Procedia PDF Downloads 53

Authors: Sh. Sousani, Z. Shadrokh, M. Hofbauerová, J. Kollár, M. Jergel, P. Nádaždy, M. Omastová, E. Majková

Abstract:

Perovskite quantum dots (PQDs) have the potential to increase the performance of the perovskite solar cells (PSCs). The integration of PQDs into PSCs can extend the absorption range and enhance photon harvesting and device efficiency. In addition, PQDs can stabilize the device structure by passivating surface defects and traps in the perovskite layer and enhance its stability. The integration of PQDs into PSCs is strongly affected by the type of ligands on the surface of PQDs. The ligands affect the charge transport properties of PQDs, as well as the formation of well-defined interfaces and stability of PSCs. In this work, the CsPbBr₃ QDs were synthesized by the conventional hot-injection method using cesium oleate, PbBr₂, and two different ligands, namely oleic acid (OA)@oleylamine (OAm) and didodecyldimethylammonium bromide (DDAB). The STEM confirmed regular shape and relatively monodisperse cubic structure with an average size of about 10-14 nm of the prepared CsPbBr₃ QDs. Further, the photoluminescent (PL) properties of the PQDs/perovskite bilayer with the ligand OA@OAm and DDAB were studied. For this purpose, ITO/PQDs, as well as ITO/PQDs/MAPI perovskite structures, were prepared by spin coating, and the effect of the ligand and oxygen plasma treatment was analysed. The plasma treatment of the PQDs layer could be beneficial for the deposition of the MAPI perovskite layer and the formation of a well-defined PQDs/MAPI interface. The absorption edge in UV-Vis absorption spectra for OA@OAm CsPbBr₃ QDs is placed around 513 nm (the band gap 2.38 eV); for DDAB CsPbBr₃ QDs, it is located at 490 nm (the band gap 2.33 eV). The photoluminescence (PL) spectra of CsPbBr₃ QDs show two peaks located around 514 nm (503 nm) and 718 nm (708 nm) for OA@OAm (DDAB). The peak around 500 nm corresponds to the PL of PQDs, and the peak close to 710 nm belongs to the surface states of PQDs for both types of ligands. These surface states are strongly affected by the O₃ plasma treatment. For PQDs with DDAB ligand, the O₃ exposure (5, 10, 15 s) results in the blue shift of the PQDs peak and a non-monotonous change of the amplitude of the surface states' peak. For OA@OAm ligand, the O₃ exposition did not cause any shift of the PQDs peak, and the intensity of the PL peak related to the surface states is lower by one order of magnitude in comparison with DDAB, being affected by O₃ plasma treatment. The PL results indicate the possibility of tuning the position of the PL maximum by the ligand of the PQDs. Similar behaviour of the PQDs layer was observed for the ITO/QDs/MAPI samples, where an additional strong PL peak at 770 nm coming from the perovskite layer was observed; for the sample with PQDs with DDAB ligands, a small blue shift of the perovskite PL maximum was observed independently of the plasma treatment. These results suggest the possibility of affecting the PL maximum position and the surface states of the PQDs by the combination of a suitable ligand and the O₃ plasma treatment.

Keywords: perovskite quantum dots, photoluminescence, O₃ plasma., perovskite solar cells

Procedia PDF Downloads 56

Authors: Shayan Mohajer Hamidi

Abstract:

Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

Procedia PDF Downloads 57

Authors: Mehmet Sinan Erguven

Abstract:

A number of authorities argue that radio is an outdated medium for advertising and does not have the same impact on consumers as it did in the past. This grim outlook on the future of radio has its basis in the audio-visual world that consumers now live in and the popularity of Internet-based marketing tools among advertising professionals. Nonetheless, consumers still appear to overwhelmingly prefer radio as an entertainment tool. Today, in Canada, 90% of all adults (18+) tune into the radio on a weekly basis, and they listen for 17 hours. Teens are the most challenging group for radio to capture as an audience, but still, almost 75% tune in weekly. One online radio station reaches more than 250 million registered listeners worldwide, and revenues from radio advertising in Australia are expected to grow at an annual rate of 3% for the foreseeable future. Radio is also starting to become popular again in Turkey, with a 5% increase in the listening rates compared to 2014. A major matter of concern always affecting radio advertising is creativity. As radio generally serves as a background medium for listeners, the creativity of the radio commercials is important in terms of attracting the attention of the listener and directing their focus on the advertising message. This cannot simply be done by using audio tools like sound effects and jingles. This study aims to identify the creative elements (execution formats appeals and approaches) and creativity factors of radio commercials in Turkey. As part of the study, all of the award winning radio commercials produced throughout the history of the Kristal Elma Advertising Festival were analyzed using the content analysis technique. Two judges (an advertising agency copywriter and an academic) coded the commercials. The reliability was measured according to the proportional agreement. The results showed that sound effects, jingles, testimonials, slices of life and announcements were the most common execution formats in creative Turkish radio ads. Humor and excitement were the most commonly used creative appeals while award-winning ads featured various approaches, such as surprise musical performances, audio wallpaper, product voice, and theater of the mind. Some ads, however, were found to not contain any creativity factors. In order to be accepted as creative, an ad must have at least one divergence factor, such as originality, flexibility, unusual/empathic perspective, and provocative questions. These findings, as well as others from the study, hold great value for the history of creative radio advertising in Turkey. Today, the nature of radio and its listeners is changing. As more and more people are tuning into online radio channels, brands will need to focus more on this relatively cheap advertising medium in the very near future. This new development will require that advertising agencies focus their attention on creativity in order to produce radio commercials for their customers that will differentiate them from their competitors.

Keywords: advertising, creativity, radio, Turkey

Procedia PDF Downloads 381

Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

Procedia PDF Downloads 109

Authors: Andrey A. Lipovskii, Alexey V. Redkov, Vyacheslav V. Rusan, Dmitry K. Tagantsev, Valentina V. Zhurikhina

Abstract:

The presented research is related to the development of recently proposed technique of the formation of composite materials, like optical glass-ceramics, with predetermined structure and properties of the crystalline component. The technique is based on the control of the size and concentration of the crystalline grains using the phenomenon of glass-ceramics decrystallization (vitrification) induced by ion-exchange. This phenomenon was discovered and explained in the beginning of the 2000s, while related theoretical description was given in 2016 only. In general, the developed theory enables one to model the process and optimize the conditions of ion-exchange processing of glass-ceramics, which provide given properties of crystalline component, in particular, profile of the average size of the crystalline grains. The optimization is possible if one knows two dimensionless parameters of the theoretical model. One of them (β) is the value which is directly related to the solubility of crystalline component of the glass-ceramics in the glass matrix, and another (γ) is equal to the ratio of characteristic times of ion-exchange diffusion and crystalline grain dissolution. The presented study is dedicated to the development of experimental technique and simulation which allow determining these parameters. It is shown that these parameters can be deduced from the data on the space distributions of diffusant concentrations and average size of crystalline grains in the glass-ceramics samples subjected to ion-exchange treatment. Measurements at least at two temperatures and two processing times at each temperature are necessary. The composite material used was a silica-based glass-ceramics with crystalline grains of Li2OSiO2. Cubical samples of the glass-ceramics (6x6x6 mm3) underwent the ion exchange process in NaNO3 salt melt at 520 oC (for 16 and 48 h), 540 oC (for 8 and 24 h), 560 oC (for 4 and 12 h), and 580 oC (for 2 and 8 h). The ion exchange processing resulted in the glass-ceramics vitrification in the subsurface layers where ion-exchange diffusion took place. Slabs about 1 mm thick were cut from the central part of the samples and their big facets were polished. These slabs were used to find profiles of diffusant concentrations and average size of the crystalline grains. The concentration profiles were determined from refractive index profiles measured with Max-Zender interferometer, and profiles of the average size of the crystalline grains were determined with micro-Raman spectroscopy. Numerical simulation were based on the developed theoretical model of the glass-ceramics decrystallization induced by ion exchange. The simulation of the processes was carried out for different values of β and γ parameters under all above-mentioned ion exchange conditions. As a result, the temperature dependences of the parameters, which provided a reliable coincidence of the simulation and experimental data, were found. This ensured the adequate modeling of the process of the glass-ceramics decrystallization in 520-580 oC temperature interval. Developed approach provides a powerful tool for fine tuning of the glass-ceramics structure, namely, concentration and average size of crystalline grains.

Keywords: diffusion, glass-ceramics, ion exchange, vitrification

Procedia PDF Downloads 260

Authors: Fuseina Mahama, Lieselot Vanhaverbeke

Abstract:

This research investigates the impact of patronage determinants on the distance consumers are willing to travel to patronize a tire shop. Although store patronage has been acknowledged as an important domain and has received substantial research interest, most of the studies so far conducted focus on grocery retail, leaving other categories of goods widely unexplored. In this study, we focus on car tires and provide a new perspective to the specific factors that influence tire shop patronage. An online survey of consumers’ tyre purchasing behaviour was conducted among private car owners in Belgium. A sample of 864 respondents was used in the study, with almost four out of five of them being male. 84% of the respondents had purchased a car tyre in the last 24 months and on average travelled 22.4kms to patronise a tyre shop. We tested the direct and mediated effects of store choice determinants on distance consumers are willing to travel. All hypotheses were tested using Structural Equation Modelling (SEM). Our findings show that with an increase in the consumer’s age the distance they were willing to travel to a tire shop decreased. Similarly, consumers who deemed proximity an important determinant of a tire shop our findings confirmed a negative effect on willingness to travel. On the other hand, the determinants price, personal contact and professionalism all had a positive effect on distance. This means that consumers actively sought out tire shops with these characteristics and were willing to travel longer distances in order to visit them. The indirect effects of the determinants flexible opening hours, family recommendation, dealer reputation, receiving auto service at home and availability of preferred brand on distance are mediated by dealer trust. Gender had a minimal effect on distance, with females exhibiting a stronger relation in terms of dealer trust as compared to males. Overall, we found that market relevant factors were better predictors of distance; and proximity, dealer trust and professionalism have the most profound effects on distance that consumers are willing to travel. This is related to the fact that the nature of shopping goods (among which are car tires) typically reinforces consumers to be more engaged in the shopping process, therefore factors that have to do with the store (e.g. location) and shopping process play a key role in store choice decision. These findings are very specific to shopping goods and cannot be generalized to other categories of goods. For marketers and retailers these findings can have direct implications on their location strategies. The factors found to be relevant to tire shop patronage will be used in our next study to calibrate a location model to be utilised to identify the optimum location for siting new tyre shop outlets and service centres.

Keywords: dealer trust, distance to store, tire store patronage, willingness to travel

Procedia PDF Downloads 243

Authors: Patrícia T. Souza, Marina Ansolin, Eduardo A. C. Batista, Antonio J. A. Meirelles, Matthieu Tubino

Abstract:

Lipid oxidation is a major cause of the deterioration of the quality of the biodiesel, because the waste generated damages the engines. Among the main undesirable effects are the increase of viscosity and acidity, leading to the formation of insoluble gums and sediments which cause the blockage of fuel filters. The auto-oxidation is defined as the spontaneous reaction of atmospheric oxygen with lipids. Unsaturated fatty acids are usually the components affected by such reactions. They are present as free fatty acids, fatty esters and glycerides. To determine the oxidative stability of biodiesels, through the induction period, IP, the Rancimat method is used, which allows continuous monitoring of the induced oxidation process of the samples. During the oxidation of the lipids, volatile organic acids are produced as byproducts, in addition, other byproducts, including alcohols and carbonyl compounds, may be further oxidized to carboxylic acids. By the methodology developed in this work using ion chromatography, IC, analyzing the water contained in the conductimetric vessel, were quantified organic anions of carboxylic acids in samples subjected to oxidation induced by Rancimat. The optimized chromatographic conditions were: eluent water:acetone (80:20 v/v) with 0.5 mM sulfuric acid; flow rate 0.4 mL min-1; injection volume 20 µL; eluent suppressor 20 mM LiCl; analytical curve from 1 to 400 ppm. The samples studied were methyl biodiesel from soybean oil and unsaturated fatty acids standards: oleic, linoleic and linolenic. The induced oxidation kinetics curves were constructed by analyzing the water contained in the conductimetric vessels which were removed, each one, from the Rancimat apparatus at prefixed intervals of time. About 3 g of sample were used under the conditions of 110 °C and air flow rate of 10 L h-1. The water of each conductimetric Rancimat measuring vessel, where the volatile compounds were collected, was filtered through a 0.45 µm filter and analyzed by IC. Through the kinetic data of the formation of the organic anions of carboxylic acids, the formation rates of the same were calculated. The observed order of the rates of formation of the anions was: formate >>> acetate > hexanoate > valerate for the oleic acid; formate > hexanoate > acetate > valerate for the linoleic acid; formate >>> valerate > acetate > propionate > butyrate for the linolenic acid. It is possible to suppose that propionate and butyrate are obtained mainly from linolenic acid and that hexanoate is originated from oleic and linoleic acid. For the methyl biodiesel the order of formation of anions was: formate >>> acetate > valerate > hexanoate > propionate. According to the total rate of formation these anions produced during the induced degradation of the fatty acids can be assigned the order of reactivity: linolenic acid > linoleic acid >>> oleic acid.

Keywords: anions of carboxylic acids, biodiesel, ion chromatography, oxidation

Procedia PDF Downloads 460

Authors: Syed Asif Hassan, Tabrej Khan

Abstract:

Tuberculosis (TB) caused by bacillus Mycobacterium tuberculosis (Mtb) continues to take a disturbing toll on human life and healthcare facility worldwide. The global burden of TB remains enormous. The alarming rise of multi-drug resistant strains of Mycobacterium tuberculosis calls for an increase in research efforts towards the development of new target specific therapeutics against diverse strains of M. tuberculosis. Therefore, the discovery of new molecular scaffolds targeting new drug sites should be a priority for a workable plan for fighting resistance in Mycobacterium tuberculosis (Mtb). Mtb non-acylated lipoprotein LprG (Rv1411c) has a Toll-like receptor 2 (TLR2) agonist actions that depend on its association with triacylated glycolipids binding specifically with the hydrophobic pocket of Mtb LprG lipoprotein. The detection of a glycolipid carrier function has important implications for the role of LprG in Mycobacterial physiology and virulence. Therefore, considering the pivotal role of glycolipids in mycobacterial physiology and host-pathogen interactions, designing competitive antagonist (chemotherapeutics) ligands that competitively bind to glycolipid binding domain in LprG lipoprotein, will lead to inhibition of tuberculosis infection in humans. In this study, a unified approach involving ligand-based virtual screening protocol USRCAT (Ultra Shape Recognition) software and molecular docking studies using Auto Dock Vina 1.1.2 using the X-ray crystal structure of Mtb LprG protein was implemented. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the Ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has the higher hypothetical affinity, also has greater negative value. Based on the USRCAT, Lipinski’s values and molecular docking results, [(2R)-2,3-di(hexadecanoyl oxy)propyl][(2S,3S,5S,6R)-3,4,5-trihydroxy-2,6-bis[[(2R,3S,4S,5R,6S)-3,4,5-trihydroxy-6 (hydroxymethyl)tetrahydropyran-2-yl]oxy]cyclohexyl] phosphate (XPX) was confirmed as a promising drug-like lead compound (antagonist) binding specifically to the hydrophobic domain of LprG protein with affinity greater than that of PIM2 (agonist of LprG protein) with a free binding energy of -9.98e+006 Kcal/mol and binding affinity of -132 Kcal/mol, respectively. A further, in vitro assay of this compound is required to establish its potency in inhibiting molecular evasion mechanism of MTB within the infected host macrophages. These results will certainly be helpful in future anti-TB drug discovery efforts against Multidrug-Resistance Tuberculosis (MDR-TB).

Keywords: antagonist, agonist, binding affinity, chemotherapeutics, drug-like, multi drug resistance tuberculosis (MDR-TB), RV1411c protein, toll-like receptor (TLR2)

Procedia PDF Downloads 260

Authors: Shilpee Jain, Sachin Latiyan, Kaushik Suneet

Abstract:

Unlike traditional robots, medical microbots are not only smaller in size, but they also possess various unique properties, for example, biocompatibility, stability in the biological fluids, navigation opposite to the bloodstream, wireless control over locomotion, etc. The idea behind their usage in the medical field was to build a minimally invasive method for addressing the post-operative complications, including longer recovery time, infection eruption and pain. Herein, the present study demonstrates the fabrication of dual nature magneto-conducting Fe3O4 magnetic nanoparticles (MNPs) and SU8 derived carbon-based Janus microbots for the efficient intracellular delivery of biomolecules. The low aspect ratio with feature size 2-5 μm microbots were fabricated by using a photolithography technique. These microbots were pyrolyzed at 900°C, which converts SU8 into amorphous carbon. The pyrolyzed microbots have dual properties, i.e., the half part is magneto-conducting and another half is only conducting for sufficing the therapeutic payloads efficiently with the application of external electric/magnetic field stimulations. For the efficient intracellular delivery of the microbots, the size and aspect ratio plays a significant role. However, on a smaller scale, the proper control over movement is difficult to achieve. The dual nature of Janus microbots allowed to control its maneuverability in the complex fluids using external electric as well as the magnetic field. Interestingly, Janus microbots move faster with the application of an external electric field (44 µm/s) as compared to the magnetic field (18 µm/s) application. Furthermore, these Janus microbots exhibit auto-fluorescence behavior that will help to track their pathway during navigation. Typically, the use of MNPs in the microdevices enhances the tendency to agglomerate. However, the incorporation of Fe₃O₄ MNPs in the pyrolyzed carbon reduces the chances of agglomeration of the microbots. The biocompatibility of the medical microbots, which is the essential property of any biosystems, was determined in vitro using HeLa cells. The microbots were found to compatible with HeLa cells. Additionally, the intracellular uptake of microbots was higher in the presence of an external electric field as compared to without electric field stimulation. In summary, the cytocompatible Janus microbots were fabricated successfully. They are stable in the biological fluids, wireless controllable navigation with the help of a few Guess external magnetic fields, their movement can be tracked because of autofluorescence behavior, they are less susceptible to agglomeration and higher cellular uptake could be achieved with the application of the external electric field. Thus, these carriers could offer a versatile platform to suffice the therapeutic payloads under wireless actuation.

Keywords: amorphous carbon, electric/magnetic stimulations, Janus microbots, magnetic nanoparticles, minimally invasive procedures

Procedia PDF Downloads 112

Authors: Roy B. Clariana, Ryan L. Solnosky

Abstract:

Structural feedback is any form of feedback that aims to improve the quality of students’ domain-normative conceptual interrelationships. Research with structural feedback points to the potential mediating role of network graphs as feedback for tuning students’ conceptual understanding; for example, improved content knowledge and motivation were observed for undergraduate students who accessed the instructor’s networks of course content. This exploratory study uses a one-group pretest-posttest design to examine the effects of instructor-provided network feedback during lectures on students’ knowledge structure measured using a concept sorting task at the pretest and posttest. Undergraduate students in an architectural engineering course (n = 32) completed a lesson module and then an end-of-unit quiz on building with wood and wood framing. Three weeks later, as a review, students completed a sorting task that used 26 terms from that lesson, then a week later, the sorting task data were used to create a group-average network, this network along with the instructor’s expert network were added to that week’s lecture slides and were compared and discussed during class time. A week later, students completed the sorting task again. The pre and post-sorting data were rendered into pathfinder networks, and then these students’ networks were compared to five referent networks, specifically the textbook chapter network, the lecture slides network, a network of the end-of-unit quiz, the actual expert network that served as the feedback intervention, and the group-average network. Inspection of means shows that knowledge structure measures improved for all five measures from pre-to-post, becoming more like the lesson content and like the expert. Repeated measures analysis with follow-up paired samples t-tests showed pre-to-post significant increases for both the end-of-unit quiz and the expert network referents. The findings show that instructor presentation of structural feedback as networks improved or ‘tuned’ students’ knowledge structure of the lesson content. This approach only takes a few extra minutes of class time and is fairly simple to implement in ordinary classrooms, and so it has wide potential to support classroom instruction and student learning. Further research is needed to determine how critical it is to present both the group-average network along with the expert network for comparison in order to highlight group-level misconceptions, or is presenting only the expert network sufficient? If a group-level network is necessary, then a simple clicker-like classroom tool could be developed to collect sorting task data during lectures that could then immediately provide the group-average network for class discussion and reflection.

Keywords: classroom instruction, engineering education, knowledge structure, pathfinder networks, structural feedback

Procedia PDF Downloads 54

Authors: N. Renuka, R. Ramesh Babu, N. Vijayan

Abstract:

Ion beams play a significant role in the process of tuning the properties of materials. Based on the radiation behavior, the engineering materials are categorized into two different types. The first one comprises organic solids which are sensitive to the energy deposited in their electronic system and the second one comprises metals which are insensitive to the energy deposited in their electronic system. However, exposure to swift heavy ions alters this general behavior. Depending on the mass, kinetic energy and nuclear charge, an ion can produce modifications within a thin surface layer or it can penetrate deeply to produce long and narrow distorted area along its path. When a high energetic ion beam impinges on a material, it causes two different types of changes in the material due to the columbic interaction between the target atom and the energetic ion beam: (i) inelastic collisions of the energetic ion with the atomic electrons of the material; and (ii) elastic scattering from the nuclei of the atoms of the material, which is extremely responsible for relocating the atoms of matter from their lattice position. The exposure of the heavy ions renders the material return to equilibrium state during which the material undergoes surface and bulk modifications which depends on the mass of the projectile ion, physical properties of the target material, its energy, and beam dimension. It is well established that electronic stopping power plays a major role in the defect creation mechanism provided it exceeds a threshold which strongly depends on the nature of the target material. There are reports available on heavy ion irradiation especially on crystalline materials to tune their physical and chemical properties. L-Arginine Acetate [LAA] is a potential semi-organic nonlinear optical crystal and its optical, mechanical and thermal properties have already been reported The main objective of the present work is to enhance or tune the structural and optical properties of LAA single crystals by heavy ion irradiation. In the present study, a potential nonlinear optical single crystal, L-arginine acetate (LAA) was grown by slow evaporation solution growth technique. The grown LAA single crystal was irradiated with oxygen ions at the dose rate of 600 krad and 1M rad in order to tune the structural and optical properties. The structural properties of pristine and oxygen ions irradiated LAA single crystals were studied using Powder X- ray diffraction and Fourier Transform Infrared spectral studies which reveal the structural changes that are generated due to irradiation. Optical behavior of pristine and oxygen ions irradiated crystals is studied by UV-Vis-NIR and photoluminescence analyses. From this investigation we can concluded that oxygen ions irradiation modifies the structural and optical properties of LAA single crystals.

Keywords: heavy ion irradiation, NLO single crystal, photoluminescence, X-ray diffractometer

Procedia PDF Downloads 244

Authors: Belinda du Plooy, Ruth Albertyn, Christel Troskie-De Bruin, Ella Belcher

Abstract:

In the academy, scholarliness or intellectual craftsmanship is considered the highest level of achievement, culminating in being consistently successfully published in impactful, peer-reviewed journals and books. Scholarliness implies rigorous methods, systematic exposition, in-depth analysis and evaluation, and the highest level of critical engagement and reflexivity. However, being a scholar does not happen automatically when one becomes an academic or completes graduate studies. A graduate qualification is an indication of one’s level of research competence but does not necessarily prepare one for the type of scholarly writing for publication required after a postgraduate qualification has been conferred. Scholarly writing for publication requires a high-level skillset and a specific mindset, which must be intentionally developed. The rite of passage to become a scholar is an iterative process with liminal spaces, thresholds, transitions, and transformations. The journey from researcher to published author is often fraught with rejection, insecurity, and disappointment and requires resilience and tenacity from those who eventually triumph. It cannot be achieved without support, guidance, and mentorship. In this article, the authors use collective auto-ethnography (CAE) to describe the phases and types of liminality encountered during the liminal journey toward scholarship. The authors speak as long-time facilitators of Writing for Academic Publication (WfAP) capacity development events (training workshops and writing retreats) presented at South African universities. Their WfAP facilitation practice is structured around experiential learning principles that allow them to act as critical reading partners and reflective witnesses for the writer-participants of their WfAP events. They identify three essential facilitation features for the effective holding of a generative, liminal, and transformational writing space for novice academic writers in order to enable their safe passage through the various liminal spaces they encounter during their scholarly development journey. These features are that facilitators should be agents of disruption and liminality while also guiding writers through these liminal spaces; that there should be a sense of mutual trust and respect, shared responsibility and accountability in order for writers to produce publication-worthy scholarly work; and that this can only be accomplished with the continued application of high levels of sensitivity and discernment by WfAP facilitators. These are key features for successful WfAP scholarship training events, where focused, individual input triggers personal and professional transformational experiences, which in turn translate into high-quality scholarly outputs.

Keywords: academic writing, liminality, scholarship, scholarliness, threshold experience, writing for publication

Procedia PDF Downloads 36

Authors: Rowan P. Martnishn

Abstract:

During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.

Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding

Procedia PDF Downloads 10

Authors: Dorottya Guban, Irina Borbath, Istvan Bakos, Peter Nemeth, Andras Tompos

Abstract:

One of the greatest challenges of the implementation of polymer electrolyte membrane fuel cells (PEMFCs) is to find active and durable electrocatalysts. The cell performance is always limited by the oxygen reduction reaction (ORR) on the cathode since it is at least 6 orders of magnitude slower than the hydrogen oxidation on the anode. Therefore high loading of Pt is required. Catalyst corrosion is also more significant on the cathode, especially in case of mobile applications, where rapid changes of loading have to be tolerated. Pt-Sn bulk alloys and SnO2-decorated Pt3Sn nanostructures are among the most studied bimetallic systems for fuel cell applications. Exclusive formation of supported Sn-Pt alloy phases with different Pt/Sn ratios can be achieved by using controlled surface reactions (CSRs) between hydrogen adsorbed on Pt sites and tetraethyl tin. In this contribution our results for commercial and a home-made 20 wt.% Pt/C catalysts modified by tin anchoring via CSRs are presented. The parent Pt/C catalysts were synthesized by modified NaBH4-assisted ethylene-glycol reduction method using ethanol as a solvent, which resulted either in dispersed and highly stable Pt nanoparticles or evenly distributed raspberry-like agglomerates according to the chosen synthesis parameters. The 20 wt.% Pt/C catalysts prepared that way showed improved electrocatalytic performance in the ORR and stability in comparison to the commercial 20 wt.% Pt/C catalysts. Then, in order to obtain Sn-Pt/C catalysts with Pt/Sn= 3 ratio, the Pt/C catalysts were modified with tetraethyl tin (SnEt4) using three and five consecutive tin anchoring periods. According to in situ XPS studies in case of catalysts with highly dispersed Pt nanoparticles, pre-treatment in hydrogen even at 170°C resulted in complete reduction of the ionic tin to Sn0. No evidence of the presence of SnO2 phase was found by means of the XRD and EDS analysis. These results demonstrate that the method of CSRs is a powerful tool to create Pt-Sn bimetallic nanoparticles exclusively, without tin deposition onto the carbon support. On the contrary, the XPS results revealed that the tin-modified catalysts with raspberry-like Pt agglomerates always contained a fraction of non-reducible tin oxide. At the same time, they showed increased activity and long-term stability in the ORR than Pt/C, which was assigned to the presence of SnO2 in close proximity/contact with Pt-Sn alloy phase. It has been demonstrated that the content and dispersion of the fcc Pt3Sn phase within the electrocatalysts can be controlled by tuning the reaction conditions of CSRs. The bimetallic catalysts displayed an outstanding performance in the ORR. The preparation of a highly dispersed 20Pt/C catalyst permits to decrease the Pt content without relevant decline in the electrocatalytic performance of the catalysts.

Keywords: anode catalyst, cathode catalyst, controlled surface reactions, oxygen reduction reaction, PtSn/C electrocatalyst

Procedia PDF Downloads 219

Authors: M. Lehtihet, S. Rosado, C. Pradère, J. Leng

Abstract:

Poly(3,4-ethylene dioxythiophene) polystyrene sulfonate (PEDOT: PSS), is a polymer mixture well-known for its semiconducting properties and is widely used in the coating industry for its visible transparency and high electronic conductivity (up to 4600 S/cm) as a transparent non-metallic electrode and in organic light-emitting diodes (OLED). It also possesses strong absorption properties in the Near Infra-Red (NIR) range (λ ranging between 900 nm to 2.5 µm). In the present work, we take advantage of this absorption to explore its potential use as a transparent light-to-heat converter. PEDOT: PSS aqueous dispersions are deposited onto a glass substrate using a blade-coating technique in order to produce uniform coatings with controlled thicknesses ranging in ≈ 400 nm to 2 µm. Blade-coating technique allows us good control of the deposit thickness and uniformity by the tuning of several experimental conditions (blade velocity, evaporation rate, temperature, etc…). This liquid coating technique is a well-known, non-expensive technique to realize thin film coatings on various substrates. For coatings on glass substrates destined to solar insulation applications, the ideal coating would be made of a material able to transmit all the visible range while reflecting the NIR range perfectly, but materials possessing similar properties still have unsatisfactory opacity in the visible too (for example, titanium dioxide nanoparticles). NIR absorbing thin films is a more realistic alternative for such an application. Under solar illumination, PEDOT: PSS thin films heat up due to absorption of NIR light and thus act as planar heaters while maintaining good transparency in the visible range. Whereas they screen some NIR radiation, they also generate heat which is then conducted into the substrate that re-emits this energy by thermal emission in every direction. In order to quantify the heating power of these coatings, a sample (coating on glass) is placed in a black enclosure and illuminated with a solar simulator, a lamp emitting a calibrated radiation very similar to the solar spectrum. The temperature of the rear face of the substrate is measured in real-time using thermocouples and a black-painted Peltier sensor measures the total entering flux (sum of transmitted and re-emitted fluxes). The heating power density of the thin films is estimated from a model of the thin film/glass substrate describing the system, and we estimate the Solar Heat Gain Coefficient (SHGC) to quantify the light-to-heat conversion efficiency of such systems. Eventually, the effect of additives such as dimethyl sulfoxide (DMSO) or optical scatterers (particles) on the performances are also studied, as the first one can alter the IR absorption properties of PEDOT: PSS drastically and the second one can increase the apparent optical path of light within the thin film material.

Keywords: PEDOT: PSS, blade-coating, heat, thin-film, Solar spectrum

Procedia PDF Downloads 148

Authors: Dechao Meng, Yongqi Dong, Qiyuan Feng, Zhangzhang Cui, Xiang Hu, Haoliang Huang, Genhao Liang, Huanhua Wang, Hua Zhou, Hawoong Hong, Jinghua Guo, Qingyou Lu, Xiaofang Zhai, Yalin Lu

Abstract:

Great efforts have been taken to reveal the intrinsic origins of emerging ferromagnetism (FM) in strained LaCoO₃ (LCO) films. However, some macro magnetic performances of LCO are still not well understood and even controversial, such as magnetic anisotropy. Determining and understanding magnetic anisotropy might help to find the true causes of FM in turn. Perpendicular magnetic anisotropy (PMA) was the first time to be directly observed in high-quality LCO films with different thickness. The in-plane (IP) and out of plane (OOP) remnant magnetic moment ratio of 30 unit cell (u.c.) films is as large as 20. The easy axis lays in the OOP direction with an IP/OOP coercive field ratio of 10. What's more, the PMA could be simply tuned by changing the thickness. With the thickness increases, the IP/OOP magnetic moment ratio remarkably decrease with magnetic easy axis changing from OOP to IP. Such a huge and tunable PMA performance exhibit strong potentials in fundamental researches or applications. What causes PMA is the first concern. More OOP orbitals occupation may be one of the micro reasons of PMA. A cluster-like magnetic domain pattern was found in 30 u.c. with no obvious color contrasts, similar to that of LaAlO₃/SrTiO₃ films. And the nanosize domains could not be totally switched even at a large OOP magnetic field of 23 T. It indicates strong IP characters or none OOP magnetism of some clusters. The IP magnetic domains might influence the magnetic performance and help to form PMA. Meanwhile some possible nonmagnetic clusters might be the reason why the measured moments of LCO films are smaller than the calculated values 2 μB/Co, one of the biggest confusions in LCO films.What tunes PMA seems much more interesting. Totally different magnetic domain patterns were found in 180 u.c. films with cluster magnetic domains surrounded by < 110 > cross-hatch lines. These lines were regarded as structure domain walls (DWs) determined by 3D reciprocal space mapping (RSM). Two groups of in-plane features with fourfold symmetry were observed near the film diffraction peaks in (002) 3D-RSM. One is along < 110 > directions with a larger intensity, which is well match the lines on the surfaces. The other is much weaker and along < 100 > directions, which is from the normal lattice titling of films deposited on cubic substrates. The < 110 > domain features obtained from (103) and (113) 3D-RSMs exhibit similar evolution of the DWs percentages and magnetic behavior. Structure domains and domain walls are believed to tune PMA performances by transform more IP magnetic moments to OOP. Last but not the least, thick films with lots of structure domains exhibit different electrical transport behaviors. A metal-to-insulator transition (MIT) and an angular dependent negative magnetic resistivity were observed near 150 K, higher than FM transition temperature but similar to that of spin-orbital coupling related 1/4 order diffraction peaks.

Keywords: structure domain, magnetic anisotropy, magnetic domain, domain wall, 3D-RSM, strain

Procedia PDF Downloads 142

Authors: Venus Torabi

Abstract:

ISIS, the terrorist organization, modified two videogames, ARMA III and Grand Theft Auto 5 (2013) as means of online recruitment and ideological propaganda. The urge to study the mechanism at work, whether it has been successful or not, derives (Digital) Humanities experts to explore how codes of terror, Islamic ideology and recruitment strategies are incorporated into the ludic mechanics of videogames. Another aspect of the significance lies in the fact that this is a latent problem that has not been fully addressed in an interdisciplinary framework prior to this study, to the best of the researcher’s knowledge. Therefore, due to the complexity of the subject, the present paper entangles with game studies, philosophical and religious poles to form the methodology of conducting the research. As a contextualized epistemology of such exploitation of videogames, the core argument is building on the notion of “Culture Industry” proposed by Theodore W. Adorno and Max Horkheimer in Dialectic of Enlightenment (2002). This article posits that the ideological underpinnings of ISIS’s cause corroborated by the action-bound mechanics of the videogames are in line with adhering to the Islamic Eschatology as a furnishing ground and an excuse in exercising terrorism. It is an account of ISIS’s modification of the videogames, a tool of technological progression to practice online radicalization. Dialectically, this practice is packed up in rhetoric for recognizing a religious myth (the advent of a savior), as a hallmark of regression. The study puts forth that ISIS’s wreaking havoc on the world, both in reality and within action videogames, is negotiating the process of self-assertion in the players of such videogames (by assuming one’s self a member of terrorists) that leads to self-annihilation. It tries to unfold how ludic Mod videogames are misused as tools of mass deception towards ethnic cleansing in reality and line with the distorted Eschatological myth. To conclude, this study posits videogames to be a new avenue of mass deception in the framework of the Culture Industry. Yet, this emerges as a two-edged sword of mass deception in ISIS’s modification of videogames. It shows that ISIS is not only trying to hijack the minds through online/ludic recruitment, it potentially deceives the Muslim communities or those prone to radicalization into believing that it's terrorist practices are preparing the world for the advent of a religious savior based on Islamic Eschatology. This is to claim that the harsh actions of the videogames are potentially breeding minds by seeds of terrorist propaganda and numbing them to violence. The real world becomes an extension of that harsh virtual environment in a ludic/actual continuum, the extension that is contributing to the mass deception mechanism of the terrorists, in a clandestine trend.

Keywords: culture industry, dialectic, ISIS, islamic eschatology, mass deception, video games

Procedia PDF Downloads 129

Authors: Sujan Barua

Abstract:

Buddhism relies upon natural events which are appeared from the four auto-elements of nature. It has seemed to be an authentic proof of mono-actions that have chronically been existing through our lives circles into the action and reaction that can produce more and more suffering in entire beings. Religion is called such politic through giving up on worthy concerns. Birth, aging, getting sick, lamentation, and death are just a politic of four conditions that depend upon one mind. Those are greed, hatred, and delusion, which are the first fueling to fall into a worthy realm again and again. It is because of having numerous ways of sense faculties, six senses, and five aggregates. These are all defaults of the deluded mind’s conditions and total ignorance covered by not understanding through the emancipating religion. Buddhism is dependent upon the threefold morality, which is the basic politic of giving up birth, aging, getting sick, lamentation, and death. Morality is the primordial theme of reach at ultimate happiness called “Nirvana”. It is a politic of one’s non-understanding ignorance. In Buddhism, the Buddha emphasizes that to understand the politic of the samsara, one must profoundly understand the own action that appears from the threefold ways. One must need authentically verify the own karma and reflection from the self-mind. The worthy concerns are the cause of political suffering to fall in samsara. By avoiding the entire, one can attain ultimate happiness. To attain Nirvana is not like an achievement of worthy happiness and proper understanding of functionality as we comfort in our daily lives. There is no virtue or non-virtual deeds to rebirth, no gripes, no upsetting, no greed, no hatred, no aging, no sickness, no death. It is totally uprooted from 31 types of states of worthy concerns. Nirvana is the stability of ultimate realization, but worthy states are the levels of grasping impurities in life span that make us fall into one clan according to our actions. By profoundly observing, the Buddha crucially founds that the source of rebirth is ignorance. Ignorance drives physical, verbal, and mental, which makes us reborn into the 31 types of realms in cycling existence. It is believed that the best knowledge of how many beings are in this world except the Enlightenment one. The enlightened one knows everything while he thinks about when it is causally necessary for demonstrating someone or verifying the truth of the relational way. It is a political view for entire beings that are chronic because covering by ignorance. It is tremendously toxic, and the person who truly understands this politic of turning here to there is a person who wishes to have eager to find the truth and way to leave those massive toxicities to discover the fixed state of nonexistence. The word non-existence is known as “Suiyata” or emptiness. One can able to find the ultimate truth with the effort of achieving the arch truth of leaving suffering from the cycling system.

Keywords: ultimate realization, nirvana, the easiest way policy to give up worthily concerns, profound understanding of 31 types of cosmology, four noble truths

Procedia PDF Downloads 57

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

Abstract:

Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

Procedia PDF Downloads 128

Authors: Saheli Mitra, Ramesh Karri, Praveen K. Mylapalli, Arka. B. Dey, Gourav Bhattacharya, Gouriprasanna Roy, Syed M. Kamil, Surajit Dhara, Sunil K. Sinha, Sajal K. Ghosh

Abstract:

The most well-known structures of lyotropic liquid crystalline systems are the two dimensional hexagonal phase of cylindrical micelles with a positive interfacial curvature and the lamellar phase of flat bilayers with zero interfacial curvature. In aqueous solution of surfactants, the concentration dependent phase transitions have been investigated extensively. However, instead of changing the surfactant concentrations, the local curvature of an aggregate can be altered by tuning the electrostatic interactions among the constituent molecules. Intermediate phases with non-uniform interfacial curvature are still unexplored steps to understand the route of phase transition from hexagonal to lamellar. Understanding such structural evolution in lyotropic liquid crystalline systems is important as it decides the complex rheological behavior of the system, which is one of the main interests of the soft matter industry. Sodium dodecyl sulfate (SDS) is an anionic surfactant and can be considered as a unique system to tune the electrostatics by cationic additives. In present study, imidazolium-based ionic liquids (ILs) with different number of carbon atoms in their single hydrocarbon chain were used as the additive in the aqueous solution of SDS. At a fixed concentration of total non-aqueous components (SDS and IL), the molar ratio of these components was changed, which effectively altered the electrostatic interactions between the SDS molecules. As a result, the local curvature is observed to modify, and correspondingly, the structure of the hexagonal liquid crystalline phases are transformed into other phases. Polarizing optical microscopy of SDS and imidazole-based-IL systems have exhibited different textures of the liquid crystalline phases as a function of increasing concentration of the ILs. The small angle synchrotron x-ray diffraction (SAXD) study has indicated the hexagonal phase of direct cylindrical micelles to transform to a rectangular phase at the presence of short (two hydrocarbons) chain IL. However, the hexagonal phase is transformed to a lamellar phase at the presence of long (ten hydrocarbons) chain IL. Interestingly, at the presence of a medium (four hydrocarbons) chain IL, the hexagonal phase is transformed to another hexagonal phase of direct cylindrical micelles through the lamellar phase. To the best of our knowledge, such a phase sequence has not been reported earlier. Even though the small angle x-ray diffraction study has revealed the lattice parameters of these phases to be similar to each other, their rheological behavior has been distinctly different. These rheological studies have shed lights on how these phases differ in their viscoelastic behavior. Finally, the packing parameters, calculated for these phases based on the geometry of the aggregates, have explained the formation of the self-assembled aggregates.

Keywords: lyotropic liquid crystals, polarizing optical microscopy, rheology, surfactants, small angle x-ray diffraction

Procedia PDF Downloads 126

Authors: Nutthan Inkhong, Sutthiphong Ruangchante

Abstract:

Chiang Rai province is located at the northern border of Thailand. Most of the geography there is the northern continental highlands, and the population has many types of inhabitants, including Thai people, immigrants and ethnic groups such as Akha, Lahu, Lisu, Yao, etc. Most of these ethnic groups migrated from neighbouring countries such as Myanmar, Laos, China, etc. and settled in the mountains. Each ethnic group has their unique traditions, culture, and ways of life, including the musical culture that the ancestors of each ethnic group brought with them. In the present, the Akha have the largest population in the region and still live together in numerous villages in many districts. Thus, Akha musical culture still appears in the community traditions and cultural events of Chiang Rai province regularly. This article presents the situations of Akha musical culture in the present and the predictions for the future. The study method involves the analysis of music information and the related social contexts, which were collected from the fieldwork of ethnomusicological methodology by in-depth interviews, observations, audio and visual recordings, and related documents. The results found that the important persons who are related with Akha musical culture include (1) a musical instrument maker (lives in Mae Chan district) who produces various Akha musical instruments, including gourd mouth organs, Akha drums, two-way flutes, three-hole flutes, Jew’s harps (the sound of teenage love), buffalo horns (the sound symbol of hunting) and bird call instruments (the imitation of bird sounds), (2) a folk philosopher (lives in Mae Pha Luang district) who can teach music to the new generation of Akha people as well as lecture and demonstrate music to academics and tourists, and (3) a community leader (lives in Mae Chan district) who conserves Akha performances, singing and music through various activities of the students in an informal school. Because of the changes to the social contexts and ways of life of the Akha people, such as the educational system, religion, social media, etc., including the popularity of both Thai and international popular music among the new generation of Akha people, changes to and the fading away of Akha musical culture in the future may likely occur. Therefore, the conservation and inheritance of Akha music is an issue that should be resolved quickly. This primary study leads to the next step of the ethnomusicological work and plays a part in preventing or reducing the problems impacting Akha musical culture survival by the recording of Akha music in all of its dimensions, such as producing musical instruments, playing musical instruments, analysis of tuning systems, recording Akha music as musical notation using symbols, researching related social contexts, etc. and the transcription of this information to create lessons that can be returned to the Akha community.

Keywords: Akha music, Chiang Rai, ethnic music in Thailand, ethnomusicology

Procedia PDF Downloads 145

Authors: Yohanna Panshak

Abstract:

The impact of macroeconomic instability on economic growth and prosperity has been at forefront in many discourses among researchers and policy makers and has generated a lot of controversies over the years. This has generated series of research efforts towards understanding the remote causes of this phenomenon; its nature, determinants and how it can be targeted and mitigated. While others have opined that the root cause of macroeconomic flux in Nigeria is attributed to Oil-Price volatility, others viewed the issue as resulting from some constellation of structural constraints both within and outside the shores of the country. Research works of scholars such as [Akpan (2009), Aliyu (2009), Olomola (2006), etc] argue that oil volatility can determine economic growth or has the potential of doing so. On the contrary, [Darby (1982), Cerralo (2005) etc] share the opinion that it can slow down growth. The earlier argument rest on the understanding that for a net balance of oil exporting economies, price upbeat directly increases real national income through higher export earnings, whereas, the latter allude to the case of net-oil importing countries (which experience price rises, increased input costs, reduced non-oil demand, low investment, fall in tax revenues and ultimately an increase in budget deficit which will further reduce welfare level). Therefore, assessing the precise impact of oil price volatility on virtually any economy is a function of whether it is an oil-exporting or importing nation. Research on oil price volatility and its outcome on the growth of the Nigerian economy are evolving and in a march towards resolving Nigeria’s macroeconomic instability as long as oil revenue still remain the mainstay and driver of socio-economic engineering. Recently, a major importer of Nigeria’s oil- United States made a historic breakthrough in more efficient source of energy for her economy with the capacity of serving significant part of the world. This undoubtedly suggests a threat to the exchange earnings of the country. The need to understand fluctuation in its major export commodity is critical. This paper leans on the Renaissance growth theory with greater focus on theoretical work of Lee (1998); a leading proponent of this school who makes a clear cut of difference between oil price changes and oil price volatility. Based on the above background, the research seeks to empirically examine the impact oil-price volatility on government expenditure using quarterly time series data spanning 1986:1 to 2014:4. Vector Auto Regression (VAR) econometric approach shall be used. The structural properties of the model shall be tested using Augmented Dickey-Fuller and Phillips-Perron. Relevant diagnostics tests of heteroscedasticity, serial correlation and normality shall also be carried out. Policy recommendation shall be offered on the empirical findings and believes it assist policy makers not only in Nigeria but the world-over.

Keywords: oil-price, volatility, prosperity, budget, expenditure

Procedia PDF Downloads 259

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

Abstract:

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

Procedia PDF Downloads 114

Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

Abstract:

Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

Procedia PDF Downloads 49

Authors: Tianyu Wang, Nikita Karandikar

Abstract:

The uncertainty around cost, safety, and feasibility of the decarbonized shipping fuels has made it increasingly complex for the shipping companies to set pricing strategies and forecast their freight revenues going forward. The increase in the green fuel surcharges will ultimately influence the automobile’s consumer prices. The auto shipping demand (ton-miles) has been gradually shifting from long-haul to short-sea trade over the past years following the relocation of the original equipment manufacturer (OEM) manufacturing to regions such as South America and Southeast Asia. The objective of this paper is twofold: 1) to investigate the car-carriers freight revenue development over the years when the trade pattern is gradually shifting towards short-sea exports 2) to empirically identify the quantitative impact of such trade pattern shifting to mainly freight rate, but also vessel size, fleet size as well as Green House Gas (GHG) emission in Roll on-Roll Off (Ro-Ro) shipping. In this paper, a model of analyzing and forecasting ton-miles and freight revenues for the trade routes of AS-NA (Asia to North America), EU-NA (Europe to North America), and SA-NA (South America to North America) is established by deploying Automatic Identification System (AIS) data and the financial results of a selected car carrier company. More specifically, Wallenius Wilhelmsen Logistics (WALWIL), the Norwegian Ro-Ro carrier listed on Oslo Stock Exchange, is selected as the case study company in this paper. AIS-based ton-mile datasets of WALWIL vessels that are sailing into North America region from three different origins (Asia, Europe, and South America), together with WALWIL’s quarterly freight revenues as reported in trade segments, will be investigated and compared for the past five years (2018-2022). Furthermore, ordinary‐least‐square (OLS) regression is utilized to construct the ton-mile demand and freight revenue forecasting. The determinants of trade pattern shifting, such as import tariffs following the China-US trade war and fuel prices following the 0.1% Emission Control Areas (ECA) zone requirement after IMO2020 will be set as key variable inputs to the machine learning model. The model will be tested on another newly listed Norwegian Car Carrier, Hoegh Autoliner, to forecast its 2022 financial results and to validate the accuracy based on its actual results. GHG emissions on the three routes will be compared and discussed based on a constant emission per mile assumption and voyage distances. Our findings will provide important insights about 1) the trade-off evaluation between revenue reduction and energy saving with the new ton-mile pattern and 2) how the trade flow shifting would influence the future need for the vessel and fleet size.

Keywords: AIS, automobile exports, maritime big data, trade flows

Procedia PDF Downloads 108

Authors: Federico Capra, Emanuele Martelli, Matteo Gazzani, Marco Mazzotti, Maurizio Notaro

Abstract:

Natural gas is a major energy source in the current global economy, contributing to roughly 21% of the total primary energy consumption. Production of natural gas starting from renewable energy sources is key to limit the related CO2 emissions, especially for those sectors that heavily rely on natural gas use. In this context, biomethane produced via biogas upgrading represents a good candidate for partial substitution of fossil natural gas. The upgrading process of biogas to biomethane consists in (i) the removal of pollutants and impurities (e.g. H2S, siloxanes, ammonia, water), and (ii) the separation of carbon dioxide from methane. Focusing on the CO2 removal process, several technologies can be considered: chemical or physical absorption with solvents (e.g. water, amines), membranes, adsorption-based systems (PSA). However, none emerged as the leading technology, because of (i) the heterogeneity in plant size, ii) the heterogeneity in biogas composition, which is strongly related to the feedstock type (animal manure, sewage treatment, landfill products), (iii) the case-sensitive optimal tradeoff between purity and recovery of biomethane, and iv) the destination of the produced biomethane (grid injection, CHP applications, transportation sector). With this contribution, we explore the use of a technology for biogas upgrading and we compare the resulting performance with benchmark technologies. The proposed technology makes use of a chemical sorbent, which is engineered by RSE and consists of Di-Ethanol-Amine deposited on a solid support made of γ-Alumina, to chemically adsorb the CO2 contained in the gas. The material is packed into fixed beds that cyclically undergo adsorption and regeneration steps. CO2 is adsorbed at low temperature and ambient pressure (or slightly above) while the regeneration is carried out by pulling vacuum and increasing the temperature of the bed (vacuum-temperature swing adsorption - VTSA). Dynamic adsorption tests were performed by RSE and were used to tune the mathematical model of the process, including material and transport parameters (i.e. Langmuir isotherms data and heat and mass transport). Based on this set of data, an optimal VTSA cycle was designed. The results enabled a better understanding of the interplay between material and cycle tuning. As exemplary application, the upgrading of biogas for grid injection, produced by an anaerobic digester (60-70% CO2, 30-40% CH4), for an equivalent size of 1 MWel was selected. A plant configuration is proposed to maximize heat recovery and minimize the energy consumption of the process. The resulting performances are very promising compared to benchmark solutions, which make the VTSA configuration a valuable alternative for biomethane production starting from biogas.

Keywords: biogas upgrading, biogas upgrading energetic cost, CO2 adsorption, VTSA process modelling

Procedia PDF Downloads 265

Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

Abstract:

Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

Procedia PDF Downloads 124

Authors: Poojan Gharat, Haridas Pal, Sharmistha Dutta Choudhury

Abstract:

Tuning photophysical properties of guest dyes through host-guest interactions involving macrocyclic hosts are the attractive research areas since past few decades, as these changes can directly be implemented in chemical sensing, molecular recognition, fluorescence imaging and dye laser applications. Excited state intramolecular proton transfer (ESIPT) is an intramolecular prototautomerization process display by some specific dyes. The process is quite amenable to tunability by the presence of different macrocyclic hosts. The present study explores the interesting effect of p-sulfonatocalix[n]arene (SCXn) and cyclodextrin (CD) hosts on the excited-state prototautomeric equilibrium of Chrysazine (CZ), a model antitumour drug. CZ exists exclusively in its normal form (N) in the ground state. However, in the excited state, the excited N* form undergoes ESIPT along with its pre-existing intramolecular hydrogen bonds, giving the excited state prototautomer (T*). Accordingly, CZ shows a single absorption band due to N form, but two emission bands due to N* and T* forms. Facile prototautomerization of CZ is considerably inhibited when the dye gets bound to SCXn hosts. However, in spite of lower binding affinity, the inhibition is more profound with SCX6 host as compared to SCX4 host. For CD-CZ system, while prototautomerization process is hindered by the presence of β-CD, it remains unaffected in the presence of γCD. Reduction in the prototautomerization process of CZ by SCXn and βCD hosts is unusual, because T* form is less dipolar in nature than the N*, hence binding of CZ within relatively hydrophobic hosts cavities should have enhanced the prototautomerization process. At the same time, considering the similar chemical nature of two CD hosts, their effect on prototautomerization process of CZ would have also been similar. The atypical effects on the prototautomerization process of CZ by the studied hosts are suggested to arise due to the partial inclusion or external binding of CZ with the hosts. As a result, there is a strong possibility of intermolecular H-bonding interaction between CZ dye and the functional groups present at the portals of SCXn and βCD hosts. Formation of these intermolecular H-bonds effectively causes the pre-existing intramolecular H-bonding network within CZ molecule to become weak, and this consequently reduces the prototautomerization process for the dye. Our results suggest that rather than the binding affinity between the dye and host, it is the orientation of CZ in the case of SCXn-CZ complexes and the binding stoichiometry in the case of CD-CZ complexes that play the predominant role in influencing the prototautomeric equilibrium of the dye CZ. In the case of SCXn-CZ complexes, the results obtained through experimental findings are well supported by quantum chemical calculations. Similarly for CD-CZ systems, binding stoichiometries obtained through geometry optimization studies on the complexes between CZ and CD hosts correlate nicely with the experimental results. Formation of βCD-CZ complexes with 1:1 stoichiometry while formation of γCD-CZ complexes with 1:1, 1:2 and 2:2 stoichiometries are revealed from geometry optimization studies and these results are in good accordance with the observed effects by the βCD and γCD hosts on the ESIPT process of CZ dye.

Keywords: intermolecular proton transfer, macrocyclic hosts, quantum chemical studies, photophysical studies

Procedia PDF Downloads 111