Search results for: hybrid PLD

Authors: Sandra H. Fukurozaki, Andre L. N. Silva, Joao B. F. Neto, Fernando J. G. Landgraf

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Nowadays, the rare earth (RE) metals play an important role in emerging technologies that are crucial for the decarbonisation of the energy sector. Their unique properties have led to increasing clean energy applications, such as wind turbine generators, and hybrid and electric vehicles. Despite the substantial media coverage that has recently surrounded the mining and processing of rare earth metals, very little quantitative information is available concerning their subsequent life stages, especially related to the metallic production of didymium (Nd-Pr) in fluoride molten salt system. Here we investigate a gate to gate scale life cycle assessment (LCA) of the didymium electrolysis based on three different scenarios of operational conditions. The product system is modeled with SimaPro Analyst 8.0.2 software, and IMPACT 2002+ was applied as an impact assessment tool. In order to develop a life cycle inventories built in software databases, patents, and other published sources together with energy/mass balance were utilized. Analysis indicates that from the 14 midpoint impact categories evaluated, the global warming potential (GWP) is the main contributors to the total environmental burden, ranging from 2.7E2 to 3.2E2 kg CO2eq/kg Nd-Pr. At the damage step assessment, the results suggest that slight changes in materials flows associated with enhancement of current efficiency (between 2.5% and 5%), could lead a reduction up to 12% and 15% of human health and climate change damage, respectively. Additionally, this paper highlights the knowledge gaps and future research efforts needing to understand the environmental impacts of Nd-Pr electrolysis process from the life cycle perspective.

Keywords: didymium electrolysis, environmental impacts, life cycle assessment, rare earth metals

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Authors: Shaher Bano, Samia Fida, Asif Israr

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The continuous development and exploitation of materials and designs have diverted the attention of the world towards the use of robust composite materials known as fiber-metal laminates in many high-performance applications. The hybrid structure of fiber metal laminates makes them a material of choice for various applications such as aircraft skin panels, fuselage floorings, door panels and other load bearing applications. The synergistic effect of properties of metals and fibers reinforced laminates are responsible for their high damage tolerance as the metal element provides better fatigue and impact properties, while high stiffness and better corrosion properties are inherited from the fiber reinforced matrix systems. They are mostly used as a layered structure in different joint configurations such as lap and but joints. The FML layers are usually bonded with each other using either mechanical fasteners or adhesive bonds. This research work is also focused on modification of an adhesive bonded joint as a single lap joint of carbon fibers based CARALL FML has been modified to increase interlaminar shear strength and avoid delamination. For this purpose different joint modification techniques such as the introduction of spews and shoulder to modify the bond shape and use of nanofillers such as carbon nano-tubes as a reinforcement in the adhesive materials, have been utilized to improve shear strength of lap joint of the adhesively bonded FML layers. Both the simulation and experimental results showed that lap joint with spews and shoulders configuration have better properties due to stress distribution over a large area at the corner of the joint. The introduction of carbon nanotubes has also shown a positive effect on shear stress and joint strength as they act as reinforcement in the adhesive bond material.

Keywords: adhesive joint, Carbon Reinforced Aluminium Laminate (CARALL), fiber metal laminates, spews

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Authors: Berna Istegun, Erkan Celebi

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The main objective of this experimental study is to assess the shear strength and the crack behavior of the triplets built of perforated brickwork masonry elements. In order to observe the influence of shear resistance and energy dissipating before and after retrofitting applications by using the reinforcing system, static-cyclic shear tests were employed in the structural mechanics laboratory of Sakarya University. The reinforcing system is composed of hybrid multiaxial seismic fabric consisting of alkali resistant glass and polypropylene fibers. The plaster as bonding material used in the specimen’s retrofitting consists of expanded glass granular. In order to acquire exact measuring data about the failure behavior of the two mortar joints under shear stressing, vertical load-controlled cylinder having force capacity of 50 kN and loading rate of 1.5 mm/min. with an internal inductive displacement transducers is carried out perpendicular to the triplet specimens. In this study, a total of six triplet specimens with textile reinforcement were prepared for these shear bond tests. The three of them were produced as single-sided reinforced triplets with seismic fabric, while the others were strengthened on both sides. In addition, three triplet specimens without retrofitting and plaster were also tested as reference samples. The obtained test results were given in the manner of force-displacement relationships, ductility coefficients and shear strength parameters comparatively. It is concluded that two-side seismic textile applications on masonry elements with relevant plaster have considerably increased the sheer force resistance and the ductility capacity.

Keywords: expanded glass granular, perforated brickwork, retrofitting, seismic fabric, triplet shear tests

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: Esraa Mohamed El-Fawal

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A facile solvothermal procedure was applied to fabricate zinc ferrite nanoparticles (ZnFe₂O₄ NPs). Activated carbon (AC) derived from peanut shells is synthesized using a microwave through the chemical activation method. The ZnFe₂O₄-AC composite is then mixed with a cerium-based metal-organic framework (CeMOF) by solid-state adding to formulate ZnFe₂O₄-AC/CeMOF composite. The synthesized photo materials were tested by scanning/transmission electron microscope (SEM/TEM), Photoluminescence (PL), (XRD) X-Ray diffraction, (FTIR) Fourier transform infrared, (UV-Vis/DRS) ultraviolet-visible/diffuse reflectance spectroscopy. The prepared ZnFe₂O₄-AC/CeMOFphotomaterial shows significantly boosted efficiency for photodegradation of methyl orange /methylene blue (MO/MB) compared with the pristine ZnFe₂O₄ and ZnFe₂O₄-AC composite under the irradiation of visible-light. The favorable ZnFe₂O₄-AC/CeMOFphotocatalyst displays the highest photocatalytic degradation efficiency of MB/MO (R: 91.5-88.6%, consecutively) compared with the other as-prepared materials after 30 min of visible-light irradiation. The apparent reaction rate K: 1.94-1.31 min-1 is also calculated. The boosted photocatalytic proficiency is ascribed to the heterojunction at the interface of prepared photo material that assists the separation of the charge carriers. To reach optimization, statistical analysis using response surface methodology was applied. The effect of independent parameters (such as A (pH), B (irradiation time), and (c) initial pollutants concentration on the response function (%)photodegradation of MB/MO dyes (as examples of azodyes) was investigated via using central composite design. At the optimum condition, the photodegradation efficiency (%) of the MB/MO is 99.8-97.8%, respectively. ZnFe2O₄-AC/CeMOF hybrid reveals good stability over four consecutive cycles.

Keywords: azo-dyes, photo-catalysis, zinc ferrite, response surface methodology

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Basanti Ekka, Talis Juhna

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Dairy industrial effluents originated by the typical processing activities are composed of various organic and inorganic constituents, and these include proteins, fats, inorganic salts, antibiotics, detergents, sanitizers, pathogenic viruses, bacteria, etc. These contaminants are harmful to not only human beings but also aquatic flora and fauna. Because consisting of large classes of contaminants, the specific targeted removal methods available in the literature are not viable solutions on the industrial scale. Therefore, in this on-going research, a series of coagulation, electrochemical, and catalytic methods will be employed. The bulk coagulation and electrochemical methods can wash off most of the contaminants, but some of the harmful chemicals may slip in; therefore, specific catalysts designed and synthesized will be employed for the removal of targeted chemicals. In the context of Latvian dairy industries, presently, work is under progress on the characterization of dairy effluents by total organic carbon (TOC), Inductively Coupled Plasma Mass Spectrometry (ICP-MS)/ Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), High-Performance Liquid Chromatography (HPLC), Gas Chromatography-Mass Spectrometry (GC-MS), and Mass Spectrometry. After careful evaluation of the dairy effluents, a cost-effective natural coagulant will be employed prior to advanced electrochemical technology such as electrocoagulation and electro-oxidation as a secondary treatment process. Finally, graphene oxide (GO) based hybrid materials will be used for post-treatment of dairy wastewater as graphene oxide has been widely applied in various fields such as environmental remediation and energy production due to the presence of various oxygen-containing groups. Modified GO will be used as a catalyst for the removal of remaining contaminants after the electrochemical process.

Keywords: catalysis, dairy wastewater, electrochemical method, graphene oxide

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Authors: Alejandro Molina-Villegas, Silvia Fernández-Sabido, Eduardo Mendoza-Vargas, Fátima Miranda-Pestaña

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The automatic detection of indigenous languages ​​in digital texts is essential to promote their inclusion in digital media. Underrepresented languages, such as Maya, are often excluded from language detection tools like Google’s language-detection library, LANGDETECT. This study addresses these limitations by developing a hybrid language detection solution that accurately distinguishes Maya (YUA) from Spanish (ES). Two strategies are employed: the first focuses on creating a profile for the Maya language within the LANGDETECT library, while the second involves training a Naive Bayes classification model with two categories, YUA and ES. The process includes comprehensive data preprocessing steps, such as cleaning, normalization, tokenization, and n-gram counting, applied to text samples collected from various sources, including articles from La Jornada Maya, a major newspaper in Mexico and the only media outlet that includes a Maya section. After the training phase, a portion of the data is used to create the YUA profile within LANGDETECT, which achieves an accuracy rate above 95% in identifying the Maya language during testing. Additionally, the Naive Bayes classifier, trained and tested on the same database, achieves an accuracy close to 98% in distinguishing between Maya and Spanish, with further validation through F1 score, recall, and logarithmic scoring, without signs of overfitting. This strategy, which combines the LANGDETECT profile with a Naive Bayes model, highlights an adaptable framework that can be extended to other underrepresented languages in future research. This fills a gap in Natural Language Processing and supports the preservation and revitalization of these languages.

Keywords: indigenous languages, language detection, Maya language, Naive Bayes classifier, natural language processing, low-resource languages

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Authors: Yu. Mateyshina, A. Ulihin, N. Uvarov

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Supercapacitors are one of the most promising devices for energy storage applications as they can provide higher power density than batteries and higher energy density than conventional dielectric capacitors. Carbon materials with various microtextures are considered as main candidates for supercapacitors in terms of high surface area, interconnected pore structure, controlled pore size, high electrical conductivity and environmental friendliness. The specific capacitance (C) of the electrode material of the Electrochemical Double Layer Capacitors (EDLC) is known to depend on the specific surface area (Ss) and the pore structure. Activated carbons are most commonly used in supercapacitors because of their high surface area (Ss ≥ 1000 m2/g), good adhesion to electrolytes and low cost. In this work, electrochemical properties of new microporous and mesoporous carbon electrode materials were studied. The aim of the work was to investigate the relationship between the specific capacitance and specific surface area in a series of materials prepared from different organic precursors.. As supporting matrixes different carbon samples with Ss = 100-2000 m2/g were used. The materials were modified by treatment in acids (H2SO4, HNO3, acetic acid) in order to enable surface hydrophilicity. Then nanoparticles of transition metal oxides (for example NiO) were deposited on the carbon surfaces using methods of salts impregnation, mechanical treatment in ball mills and the precursors decomposition. The electrochemical characteristics of electrode hybrid materials were investigated in a symmetrical two-electrode cell using an impedance spectroscopy, voltammetry in both potentiodynamic and galvanostatic modes. It was shown that the value of C for the materials under study strongly depended on the preparation method of the electrode and the type of electrolyte (1 M H2SO4, 6 M KOH, 1 M LiClO4 in acetonitryl). Specific capacity may be increased by the introduction of nanoparticles from 50-100 F/g for initial carbon materials to 150-300 F/g for nanocomposites which may be used in supercapacitors. The work is supported by the по SC-14.604.21.0013.

Keywords: supercapacitors, carbon electrode, mesoporous carbon, electrochemistry

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Authors: Ali Elshabrawy

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Cloud computing is expected to be important for e Government in near future. Governments need it for solving some of its e Government, financial, infrastructure, legacy systems and integration problems. It reduces information technology (IT) infrastructure needs and support costs, and offers on-demand infrastructure and computational power, improved collaboration capabilities, which are important for e Government projects start up and sustainability. Budget pressures will continue to drive more and more government IT to hybrid and even public clouds, and more cooperation between cloud service providers and governmental agencies are expected, Or developing governmental private, community clouds. Motivation to convince governments to use cloud computing services, will create a pressure on cloud service providers to cope with government's requirements for interoperability, security standards, open data and integration between their cloud systems There will be significant legal action arising out of governmental uses of cloud computing, and legislation addressing both IT and business needs and consumer fears and protections. Cloud computing is a considered a revolution for IT and E business in general and e commerce, e Government in particular. As governments faces increasing challenges regarding IT infrastructure required for e Government projects implementation. As a result of Lack of required financial resources allocated for e Government projects in developed and developing countries. Cloud computing can play a major role to solve some of e Government projects challenges such as, lack of financial resources, IT infrastructure, Human resources trained to manage e Government applications, interoperability, cost efficiency challenges. If we could solve some security issues related to cloud computing usage which considered critical for e Government projects. Pretty sure it’s Just a matter of time before cloud service providers will find out solutions to attract governments as major customers for their business.

Keywords: cloud computing, e-government, adoption, supply side barriers, e-government requirements, challenges

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Authors: Ashish Bhattarai, Bishnu Bhatta, Hem Raj Joshi, Nabin Neupane, Pankaj Yadav

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This report concerns the design, development, and analysis of the combined Darrieus and Savonius wind turbine. Vertical Axis Wind Turbines (VAWT's) are of two type's viz. Darrieus (lift type) and Savonius (drag type). The problem associated with Darrieus is the lack of self-starting while Savonius has low efficiency. There are 3 straight Darrieus blades having the cross-section of NACA(National Advisory Committee of Aeronautics) 0018 placed circumferentially and a helically twisted Savonius blade to get even torque distribution. This unique design allows the use of Savonius as a method of self-starting the wind turbine, which the Darrieus cannot achieve on its own. All the parts of the wind turbine are designed in CAD software, and simulation data were obtained via CFD(Computational Fluid Dynamics) approach. Also, the design was imported to FlashForge Finder to 3D print the wind turbine profile and finally, testing was carried out. The plastic material used for Savonius was ABS(Acrylonitrile Butadiene Styrene) and that for Darrieus was PLA(Polylactic Acid). From the data obtained experimentally, the hybrid VAWT so fabricated has been found to operate at the low cut-in speed of 3 m/s and maximum power output has been found to be 7.5537 watts at the wind speed of 6 m/s. The maximum rpm of the rotor blade is recorded to be 431 rpm(rotation per minute) at the wind velocity of 6 m/s, signifying its potentiality of wind power production. Besides, the data so obtained from both the process when analyzed through graph plots has shown the similar nature slope wise. Also, the difference between the experimental and theoretical data obtained has shown mechanical losses. The objective is to eliminate the need for external motors for self-starting purposes and study the performance of the model. The testing of the model was carried out for different wind velocities.

Keywords: VAWT, Darrieus, Savonius, helical blades, CFD, flash forge finder, ABS, PLA

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Authors: Alexis Thouki

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In our post-Christian societies, ecclesiastical heritage acquired a new extrovert profile aiming to reach out an increasingly diverse audience. In this context, the various motivations, interests, personalities and cultural exchanges, found in the ‘post-modern pilgrimage’, bequeath a hybrid and multidimensional character to religious tourism education. In consequence, churches have acquired the challenging role of enriching visitors cultural and spiritual capital. Despite this promising diversification to relate, reveal and provoke constructive discourses, due to the various ‘conflicting interests’, practitioners attempt to tame the rich in symbolism and meanings religious environment through ‘neutral interpretations’. This paper aims to present the results of an ongoing developing strategy related to the presentation of contentious meanings in English churches. The paper will explore some of the underlying issues related to the capacity of ‘neutrality’ to spark, downplay or eliminate contentious conversations relating to the cultural, religious, and social dimension of Christian cultural heritage thematology. In an effort to understand this issue, the paper examines the concept of neutrality and what it stands for, executing a discourse analysis in the semantic context in which the theological lexicon is interwoven with the cultural and social meanings of sacred sites. Following that, the paper examines whether the preferable interpretive strategies meet the post-modern interpretative framework which is marked by polysemy and critical active engagement. The ultimate aim of the paper is to investigate the hypothesis that the preferable neutral strategies, managing the ‘conflicting’ demands of worshippers and visitors, result in the uneven treatment of both, the religious and historical spirit of the place.

Keywords: contentious dialogue, interpretation, meaning making, religious tourism

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Authors: Rahime Filiz Kiremit

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This study involves investigating the comparisons of both online and face-to-face classes, along with providing their respective differences. The research project contains information pertaining to the two courses, provided with testimony from students and instructors alike. There were a total of 37 participants involved within the study from San Jacinto College; 35 students and the two instructors of their respective courses. The online instructor has a total of four years of teaching experience, while the face-to-face instructor has accrued 11 years of instructional education. The both instructors were interviewed and the samples were collected from three different classes - TECA 1311-702 (Educating Young Children 13 week distance learning), TECA 1311-705 (Educating Young Children 13 week distance learning) and TECA 1354 (Child Growth and Development). Among all three classes, 13 of the 29 students enrolled in either of the online courses considered participation within the survey, while 22 of the 28 students enrolled in the face-to-face course elected to do the same thing. With regards to the students’ prior class enrollment, 25 students had taken online classes previously, 9 students had taken early-childhood courses, 4 students had taken general classes, 11 students had taken both types of classes, 10 students had not yet taken online classes, and only 1 of them had taken a hybrid course. 10 of the participants professed that they like face-to-face classes, because they find that they can interact with their classmates and teachers. They find that online classes have more work to do, because they need to read the chapters and instructions on their own time. They said that during the face-to-face instruction, they could take notes and converse concerns with professors and fellow peers. They can have hands-on activities during face-to-face classes, and, as a result, improve their abilities to retain what they have learned within that particular time. Some of the students even mentioned that they are supposed to discipline themselves, because the online classes require more work. According to the remaining six students, online classes are easier than face-to-face classes. Most of them believe that the easiness of a course is dependent on the types of classes, the instructors, and the respective subjects of which they teach. With considerations of all 35 students, almost 63% of the students agreed that they interact more with their classmates in face-to-face classes.

Keywords: distance education, face-to-face education, online classroom, students' perceptions

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Authors: Karen G. Bastidas Gomez, Hugo R. Zea Ramirez, Manuel F. Ribeiro Pereira, Cesar A. Sierra Avila, Juan A. Clavijo Morales

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The contamination of water sources with heavy metals such as mercury has been an environmental problem; it has generated a high impact on the environment and human health. In countries such as Colombia, mercury contamination due to mining has reached levels much higher than the world average. This work proposes the use of fique fibers as adsorbent in mercury removal. The evaluation of the material was carried out under five different conditions (raw, pretreated by organosolv, functionalized by TEMPO oxidation, fiber functionalized plus MOF-199 and fiber functionalized plus MOF-199-SH). All the materials were characterized using FTIR, SEM, EDX, XRD, and TGA. Regarding the mercury removal, it was done under room pressure and temperature, also pH = 7 for all materials presentations, followed by Atomic Absorption Spectroscopy. The high cellulose content in fique is the main particularity of this lignocellulosic biomass since the degree of oxidation depends on the number of hydroxyl groups on the surface capable of oxidizing into carboxylic acids, a functional group capable of increasing ion exchange with mercury in solution. It was also expected that the impregnation of the MOF would increase the mercury removal; however, it was found that the functionalized fique achieved a greater percentage of removal, resulting in 81.33% of removal, 44% for the fique with the MOF-199 and 72% for the MOF-199-SH with. The pretreated fiber and raw also showed 74% and 56%, respectively, which indicates that fique does not require considerable modifications in its structure to achieve good performances. Even so, the functionalized fiber increases the percentage of removal considerably compared to the pretreated fique, which suggests that the functionalization process is a feasible procedure to apply with the purpose of improving the removal percentage. In addition, this is a procedure that follows a green approach since the reagents involved have low environmental impact, and the contribution to the remediation of natural resources is high.

Keywords: biomass, nanotechnology, science materials, wastewater treatment

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Authors: Yaping Gao

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With the increasing globalization of education and the continued momentum and wider adoption of online and digital learning all over the world, post pandemic, how could best practices and extensive experience gained from the higher education community over the past few decades be adopted and adapted to benefit international communities, which can be vastly different culturally and pedagogically? How can schools and institutions adopt, adapt and apply these proven practices to develop strategic plans for digital transformation at institutional levels, and to improve or create quality online or digital learning environments at course and program levels to help all students succeed? The presenter will introduce the primary components of the US-based quality assurance process, including : 1) five sets of research-supported standards to guide the design, development and review of online and hybrid courses; 2) professional development offerings and pathways for administrators, faculty and instructional support staff; 3) a peer-review process for course/program reviews resulting in constructive recommendations for continuous improvement, certification of quality and international recognition; and 4) implementation of the quality assurance process on a continuum to program excellence, achievement of institutional goals, and facilitation of accreditation process and success. Regardless language, culture, pedagogical practices, or technological infrastructure, the core elements of quality teaching and learning remain the same across all delivery formats. What is unique is how to ensure quality of teaching and learning in online education and digital learning. No one knows all the answers to everything but no one needs to reinvent the wheel either. Together the international education community can support and learn from each other to achieve institutional goals and ensure all students succeed in the digital learning environments.

Keywords: Online Education, Digital Learning, Quality Assurance, Standards and Best Practices

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Authors: Susmita Roy, Madhavan Nallani

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In recent years' polymersomes, self-assembled polymeric vesicles emerge from block copolymers, have been widely investigated due to their enhance stability and unique advantageous properties compared to their phospholipid counterpart, liposomes, dendrimers, and micelles. It provides a distinctive platform for advanced therapeutics and the creation of complex (bio) catalytically active systems for research in Nanomedicine and synthetic biology. Inspired by nature, where compartmentalization of biological components is all ubiquitous, we are interested in developing a platform technology of self-assembled multifunctional compartments with applications in areas from targeted drug/gene delivery, biosensing, pharmaceutical to cosmetics. Polymersome surfaces can be a proper choice of derivatization with a controlled amount of functional groups. To achieve site-specific targeting of polymersomes, biological recognition motives can be attached to the polymersomes surface by standard bioconjugation techniques, (like esterification, amidation, thiol-maleimide coupling, click-chemistry routes or other coupling methods). Herein, we are developing easy going, one-step bioconjugation strategies for site-specific surface functionalized biodegradable polymeric and/or polymer-lipid hybrid vesicles for targeted drug delivery. Biodegradable polymer, polycaprolactone-b-polyethylene glycol (PCL-PEG), polylactic acid-b-polyethylene glycol (PLA-PEG) and phospholipid, 1-palmitoyl-2- oleoyl-sn-glycero-3-phosphocholine (POPC) has been widely used for numerous vesicle formulations. Some of these drug-loaded formulations are being tested on mice for controlled release. These surface functionalized polymersomes are also appropriate for membrane protein reconstitution/insertion, antibodies conjugation and various bioconjugation with diverse targeted molecules for controlled drug delivery.

Keywords: drug delivery, membrane protein, polymersome, surface modification

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Authors: Mahmoud Abdulhamid, Rifan Hardian, Prashant Bhatt, Shuvo Datta, Adrian Ramirez, Jorge Gascon, Mohamed Eddaoudi, Gyorgy Szekely

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Polybenzimidazole (PBI) is a high-performance polymer that exhibits high thermal and chemical stability. However, it suffers from low porosity and low fractional free volume, which hinder its application as separation material. Herein, we demonstrate the molecular engineering of gas separation materials by manipulating a PBI backbone possessing kinked moieties. PBI was selected as it contains NH groups which increase the affinity towards CO₂, increase sorption capacity, and favors CO₂ over other gasses. We have designed and synthesized an intrinsically microporous polybenzimidazole (iPBI) featuring a spirobisindane structure. Introducing a kinked moiety in conjunction with crosslinking enhanced the polymer properties, markedly increasing the gas separation performance. In particular, the BET surface area of PBI increased 30-fold by replacing a flat benzene ring with a kinked structure. iPBI displayed a good CO₂ uptake of 1.4 mmol g⁻¹ at 1 bar and 3.6 mmol g⁻¹ at 10 bar. Gas sorption uptake and breakthrough experiments were conducted using mixtures of CO₂/CH₄ (50%/50%) and CO₂/N₂ (50%/50%), which revealed the high selectivity of CO₂ over both CH₄ and N₂. The obtained CO₂/N₂ selectivity is attractive for power plant flue gas application requiring CO₂ capturing materials. Energy and process simulations of biogas CO₂ removal demonstrated that up to 70% of the capture energy could be saved when iPBI was used rather than the current amine technology (methyl diethanolamine [MDEA]). Similarly, the combination of iPBI and MDEA in a hybrid system exhibited the highest CO₂ capture yield (99%), resulting in nearly 50% energy saving. The concept of enhancing the porosity of PBI using kinked moieties provides new scope for designing highly porous polybenzimidazoles for various separation processes.

Keywords: polybenzimidazole (PBI), intrinsically microporous polybenzimidazole (iPBI), gas separation, pnergy and process simulations

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Authors: Gabriel Wainer

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Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems, and it is now common to use simulation as a part of the scientific and technological discovery process. M&S advanced thanks to the improvements in computer technology, which, in many cases, resulted in the development of simulation software using ad-hoc techniques. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks; reducing costs and favoring reuse. The DEVS formalism is one of these techniques, which proved to be successful in providing means for modeling while reducing development complexity and costs. DEVS model development is based on a sound theoretical framework. The independence of M&S tasks made possible to run DEVS models on different environments (personal computers, parallel computers, real-time equipment, and distributed simulators) and middleware. We will present a historical perspective of discrete-event M&S methodologies, showing different modeling techniques. We will introduce DEVS origins and general ideas, and compare it with some of these techniques. We will then show the current status of DEVS M&S, and we will discuss a technological perspective to solve current M&S problems (including real-time simulation, interoperability, and model-centered development techniques). We will show some examples of the current use of DEVS, including applications in different fields. We will finally show current open topics in the area, which include advanced methods for centralized, parallel or distributed simulation, the need for real-time modeling techniques, and our view in these fields.

Keywords: modeling and simulation, discrete-event simulation, hybrid systems modeling, parallel and distributed simulation

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Bülent Kantar, Numan Ünaldı

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This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

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Authors: Mohammadreza Salek Faramarzi, Touraj Taghikhany

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In this paper, seismic fragility assessment of a recently developed hybrid structural system, known as the strongback system (SBS) is investigated. In this system, to mitigate the occurrence of the soft-story mechanism and improve the distribution of story drifts over the height of the structure, an elastic vertical truss is formed. The strengthened members of the braced span are designed to remain substantially elastic during levels of excitation where soft-story mechanisms are likely to occur and impose a nearly uniform story drift distribution. Due to the distinctive characteristics of near-field ground motions, it seems to be necessary to study the effect of these records on seismic performance of the SBS. To this end, a set of 56 near-field ground motion records suggested by FEMA P695 methodology is used. For fragility assessment, nonlinear dynamic analyses are carried out in OpenSEES based on the recommended procedure in HAZUS technical manual. Four damage states including slight, moderate, extensive, and complete damage (collapse) are considered. To evaluate each damage state, inter-story drift ratio and floor acceleration are implemented as engineering demand parameters. Further, to extend the evaluation of the collapse state of the system, a different collapse criterion suggested in FEMA P695 is applied. It is concluded that SBS can significantly increase the collapse capacity and consequently decrease the collapse risk of the structure during its life time. Comparing the observing mean annual frequency (MAF) of exceedance of each damage state against the allowable values presented in performance-based design methods, it is found that using the elastic vertical truss, improves the structural response effectively.

Keywords: IDA, near-fault, probabilistic performance assessment, seismic fragility, strongback system, uncertainty

Procedia PDF Downloads 114

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Xingyu Peng, Qingyuan Hu, Xuebin Zhu, Xi Yuan

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Neutron spectrometry has contributed much to the development of nuclear physics since 1932 and has also become an importance tool in several other fields, notably nuclear technology, fusion plasma diagnostics and radiation protection. Compared with neutron fluxes, neutron spectra can provide more detailed information on the internal physical process of neutron sources, such as fast neutron reactors, fusion plasma, fission-fusion hybrid reactors, and so on. However, high performance neutron spectrometer is not so commonly available as it requires the use of large and complex instrumentation. This work describes the development and characterization of a compact magnetic proton recoil (MPR) spectrometer for high-resolution measurements of fast neutron spectra. The compact MPR spectrometer is featured by its large recoil angle, small size permanent analysis magnet, short beam transport line and dual-purpose detector array for both steady state and pulsed neutron spectra measurement. A 3-dimensional electromagnetic particle transport code is developed to simulate the response function of the spectrometer. Simulation results illustrate that the performance of the spectrometer is mainly determined by n-p recoil foil and proton apertures, and an overall energy resolution of 3% is achieved for 14 MeV neutrons. Dedicated experiments using alpha source and mono-energetic neutron beam are employed to verify the simulated response function of the compact MPR spectrometer. These experimental results show a good agreement with the simulated ones, which indicates that the simulation code possesses good accuracy and reliability. The compact MPR spectrometer described in this work is a valuable tool for fast neutron spectra measurements for the fission or fusion devices.

Keywords: neutron spectrometry, magnetic proton recoil spectrometer, neutron spectra, fast neutron

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Authors: Nino Chomakhashvili, Nino Chikhladze, Nato Pitskhelauri, Maia Bitskhinashvili

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The dental practice is associated with occupational health challenges. Ergonomic risks in the workplace can significantly impair a dentist's work capacity and may even result in the premature end of their career. Implementing ergonomic principles in dental practice aims to prevent work-related musculoskeletal disorders. Many studies have been conducted in various countries such as Sweden, Denmark, Germany, Poland, and Australia to examine the prevalence of musculoskeletal disorders among dentists. However, to the best of authors knowledge there have been no studies on the application of ergonomic principles in dental practice in Georgia. This study focused on evaluating the ergonomic conditions of dental practice in Georgia and determining how common musculoskeletal disorders are among them. The survey was conducted using a random sampling method in selected dental clinics. A tailored questionnaire consisting of 40 questions, created using insights from international practices, was utilized for the study. Two hundred ninety-one filled questionnaires were used for the analysis. Most respondents reported that their workplaces adhered to ergonomic standards. However, 53.6% experienced frequent back pain, with 50.9% suffering from neck pain, 47.9% from shoulder pain, and 47.1% from lower back pain. Many noted that pain had caused them to reduce their working hours. Nearly all respondents expressed a desire to enhance their knowledge about ergonomics and the prevention of occupational diseases. They indicated a preference for participating in continuous professional development programs (61.5%), receiving information through leaflets (12.0%), and attending online webinars (26.6%). Integrating ergonomic principles into the dental practice is crucial for preventing work-related musculoskeletal disorders. It is essential to offer continuous professional development programs and provide information to dentists, via leaflets, thematic online or hybrid webinars.

Keywords: dental practice, ergonomic risks, musculoskeletal disorders, occupational health

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Authors: Intisar Al Busaidi, Rashid Al Maamari, Daowoud Al Mahroqi, Mahvash Karimi

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In recent years, some research studies have been performed on the hybrid application of polymer and low salinity water flooding (LSWF). Numerous technical and economic benefits of low salinity polymer flooding (LSPF) have been reported. However, as with any EOR technology, there are various risks involved in using LSPF. Ions exchange between porous media and brine is one of the Crude oil/ brine/ rocks (COBR) reactions that is identified as a potential risk in LSPF. To the best of our knowledge, this conclusion was drawn based on bulk rheology measurements, and no explanation was provided on how water chemistry changed in the presence of polymer. Therefore, this study aimed to understand rock/ brine interactions with high and low salinity brine in the absence and presence of polymer with Omani reservoir core plugs. Many single-core flooding experiments were performed with low and high salinity polymer solutions to investigate the influence of partially hydrolyzed polyacrylic amide with different brine salinities on cation exchange reactions. Ion chromatography (IC), total organic carbon (TOC), rheological, and pH measurements were conducted for produced aqueous phase. A higher increase in pH and lower polymer adsorption was observed in LSPF compared with conventional polymer flooding. In addition, IC measurements showed that all produced fluids in the absence and presence of polymer showed elevated Ca²⁺, Mg²⁺, K+, Cl- and SO₄²⁻ ions compared to the injected fluids. However, the divalent cations levels, mainly Ca²⁺, were the highest and remained elevated for several pore volumes in the presence of LSP. The results are in line with rheological measurements where the highest viscosity reduction was recorded with the highest level of Ca²⁺ production. Despite the viscosity loss due to cation exchange reactions, LSP can be an attractive alternative to conventional polymer flooding in the Marmul field.

Keywords: polymer, ions, exchange, recovery, low salinity

Procedia PDF Downloads 114

Authors: Calvin A. Omolo, Rahul S. Kalhapure, Mahantesh Jadhav, Sanjeev Rambharose, Chunderika Mocktar, Thirumala Govender

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Treatment of infections is compromised by limitations of conventional dosage forms and drug resistance. Nanocarrier system is a strategy to overcome these challenges and improve therapy. Thus, the development of novel materials for drug delivery via nanocarriers is essential. The aim of the study was to synthesize a multi-arm polymer (6-mPEPEA) for enhanced activity of vancomycin (VM) against susceptible and resistant Staphylococcus aureus (MRSA). The synthesis steps of the star polymer followed reported procedures. The synthesized 6-mPEPEA was characterized by FTIR, ¹H and ¹³CNMR and MTT assays. VM loaded micelles were prepared from 6-mPEPEA and characterized for size, polydispersity index (PI) and surface charge (ZP) (Dynamic Light Scattering), morphology by TEM, drug loading (UV Spectrophotometry), drug release (dialysis bag), in vitro and in vivo efficacy against sensitive and resistant S. aureus. 6-mPEPEA was synthesized, and its structure was confirmed. MTT assays confirmed its nontoxic nature with a high cell viability (77%-85%). Unimolecular spherical micelles were prepared. Size, PI, and ZP was 52.48 ± 2.6 nm, 0.103 ± 0.047, -7.3 ± 1.3 mV, respectively and drug loading was 62.24 ± 3.8%. There was a 91% drug release from VCM-6-mPEPEA after 72 hours. In vitro antibacterial test revealed that VM-6-mPEPEA had 8 and 16-fold greater activity against S. aureus and MRSA when compared to bare VM. Further investigations using flow cytometry showed that VM-6-mPEPEA had 99.5% killing rate of MRSA at the MIC concentration. In vivo antibacterial activity revealed that treatment with VM-6-mPEPEA had a 190 and a 15-fold reduction in the MRSA load in untreated and VM treated respectively. These findings confirmed the potential of 6-mPEPEA as a promising bio-degradable nanocarrier for antibiotic delivery to improve treatment of bacterial infections.

Keywords: biosafe, MRSA, nanocarrier, resistance, unimolecular-micelles

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Authors: Keerthi Katam, Abhinav B. Tirunaghari, Vinod Vadithya, Toshiyuki Shimizu, Satoshi Soda, Debraj Bhattacharyya

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Researchers worldwide are increasingly focusing on the removal of carbon and nutrient from wastewater using algal-bacterial hybrid systems. Algae produce oxygen during photosynthesis, which is taken up by heterotrophic bacteria for mineralizing organic carbon to carbon dioxide. This phenomenon reduces the net mechanical aeration requirement of aerobic biological wastewater treatment processes. Consequently, the treatment cost is also reduced. Microalgae also participate in the treatment process by taking up nutrient (N, P) from wastewater. Algal biomass, if harvested, can generate value-added by-products. The aim of the present study was to compare the performance of two systems - System A (mixed microalgae and bacteria) and System B (diatoms and bacteria) in treating kitchen wastewater (KWW). The test reactors were operated at five different solid retention times (SRTs) -2, 4, 6, 8, and 10-days in draw-and-fill mode. The KWW was collected daily from the dining hall-kitchen area of the Indian Institute of Technology Hyderabad. The influent and effluent samples were analyzed for total organic carbon (TOC), total nitrogen (TN) using TOC-L analyzer. A colorimetric method was used to analyze anionic surfactant. Phosphorus (P) and chlorophyll were measured by following standard methods. The TOC, TN, and P of KWW were in the range of 113.5 to 740 mg/L, 2 to 22.8 mg/L, and 1 to 4.5 mg/L, respectively. Both the systems gave similar results with 85% of TOC removal and 60% of TN removal at 10-d SRT. However, the anionic surfactant removal in System A was 99% and 60% in System B. The chlorophyll concentration increased with an increase in SRT in both the systems. At 2-d SRT, no chlorophyll was observed in System B, whereas 0.5 mg/L was observed in System A. At 10-d SRT, the chlorophyll concentration in System A was 7.5 mg/L, whereas it was 4.5 mg/L in System B. Although both the systems showed similar performance in treatment, the increase in chlorophyll concentration suggests that System A demonstrated a better algal-bacterial symbiotic relationship in treating KWW than System B.

Keywords: diatoms, microalgae, retention time, wastewater treatment

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Authors: Arun Prasad, Abhishek Tiwari, Rekha Jaiswal, Vivek Chaudhary

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Background: Robotic Roux en Y gastric bypass is being done for some time but is technically difficult, requiring operating in both the sub diaphragmatic and infracolic compartments of the abdomen. This can mean a dual docking of the robot or a hybrid partial laparoscopic and partial robotic surgery. The Mini /One anastomosis /omega loop gastric bypass (MGB) has the advantage of having all dissection and anastomosis in the supracolic compartment and is therefore suitable technically for robotic surgery. Methods: We have done 208 robotic mini gastric bypass surgeries. The robot is docked above the head of the patient in the midline. Camera port is placed supra umbilically. Two ports are placed on the left side of the patient and one port on the right side of the patient. An assistant port is placed between the camera port and right sided robotic port for use of stapler. Distal stomach is stapled from the lesser curve followed by a vertical sleeve upwards leading to a long sleeve pouch. Jejunum is taken at 200 cm from the duodenojejunal junction and brought up to do a side to side gastrojejunostomy. Results: All patients had a successful robotic procedure. Mean time taken was 85 minutes. There were major intraoperative or post operative complications. No patient needed conversion or re-explorative surgery. Mean excess weight loss over a period of 2 year was about 75%. There was no mortality. Patient satisfaction score was high and was attributed to the good weight loss and minimal dietary modifications that were needed after the procedure. Long term side effects were anemia and bile reflux in a small number of patients. Conclusions: MGB / OAGB is gaining worldwide interest as a short simple procedure that has been shown to very effective and safe bariatric surgery. The purpose of this study was to report on the safety and efficacy of robotic surgery for this procedure. This is the first report of totally robotic mini gastric bypass.

Keywords: MGB, mini gastric bypass, OAGB, robotic bariatric surgery

Procedia PDF Downloads 297

Authors: Mohamed S. Selim, Nesreen A. Fatthallah, Shimaa A. Higazy, Zhifeng Hao, Ping Jing Mo

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As marine fouling-release (FR) surfaces, two new superhydrophobic nanocomposite series of polydimethylsiloxane (PDMS) loaded with reduced graphene oxide (RGO) and graphene oxide/boehmite nanorods (GO-γ-AlOOH) nanofillers were created. The self-cleaning and antifouling capabilities were modified by controlling the nanofillers' shapes and distribution in the silicone matrix. With an average diameter of 10-20 nm and a length of 200 nm, γ-AlOOH nanorods showed a single crystallinity. RGO was made using a hydrothermal process, whereas GO-γ-AlOOH nanocomposites were made using a chemical deposition method for use as fouling-release coating materials. These nanofillers were disseminated in the silicone matrix using the solution casting method to explore the synergetic effects of graphene-based materials on the surface, mechanical, and FR characteristics. Water contact angle (WCA), scanning electron, and atomic force microscopes were used to investigate the surface's hydrophobicity and antifouling capabilities (SEM and AFM). The roughness, superhydrophobicity, and surface mechanical characteristics of coatings all increased the homogeneity of the nanocomposite dispersion. To examine the antifouling effects of the coating systems, laboratory tests were conducted for 30 days using specified bacteria.PDMS/GO-γ-AlOOH nanorod composite demonstrated superior antibacterial efficacy against several bacterial strains than PDMS/RGO nanocomposite. The high surface area and stabilizing effects of the GO-γ-AlOOH hybrid nanofillers are to blame for this. The biodegradability percentage of the PDMS/GO-γ-AlOOH nanorod composite (3 wt.%) was the lowest (1.6%), while the microbial endurability percentages for gram-positive, gram-negative, and fungi were 86.42%, 97.94%, and 85.97%, respectively. The homogeneity of the GO-γ-AlOOH (3 wt.%) dispersion, which had a WCA of 151° and a rough surface, was the most profound superhydrophobic antifouling nanostructured coating.

Keywords: superhydrophobic nanocomposite, fouling release, nanofillers, surface coating

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