Search results for: hybrid hierarchical clustering

Authors: Lubos Rojka

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The common perception of morally responsible behavior is that it presupposes freedom of choice, and that free decisions and actions are not determined by natural events, but by a person. In other words, the moral agent has the ability and the possibility of doing otherwise when making morally responsible decisions, and natural causal determinism cannot fully account for morally significant freedom. The incompatibility between a person’s morally significant freedom and causal determinism appears to be a natural position. Nevertheless, some of the most influential philosophical theories on moral responsibility are compatibilist or semi-compatibilist, and they exclude the requirement of alternative possibilities, which contradicts the claims of classical incompatibilism. The compatibilists often employ Frankfurt-style thought experiments to prove their theory. The goal of this paper is to examine the role of imaginary Frankfurt-style examples in compatibilist accounts. More specifically, the compatibilist accounts defended by John Martin Fischer and Michael McKenna will be inserted into the broader understanding of a person elaborated by Harry Frankfurt, Robert Kane and Walter Glannon. Deeper analysis reveals that the exclusion of alternative possibilities based on Frankfurt-style examples is problematic and misleading. A more comprehensive account of moral responsibility and morally significant (source) freedom requires higher order complex theories of human will and consciousness, in which rational and self-creative abilities and a real possibility to choose otherwise, at least on some occasions during a lifetime, are necessary. Theoretical moral reasons and their logical relations seem to require a sort of higher-order agent-causal incompatibilism. The ability of theoretical or abstract moral reasoning requires complex (strongly emergent) mental and conscious properties, among which an effective free will, together with first and second-order desires. Such a hierarchical theoretical model unifies reasons-responsiveness, mesh theory and emergentism. It is incompatible with physical causal determinism, because such determinism only allows non-systematic processes that may be hard to predict, but not complex (strongly) emergent systems. An agent’s effective will and conscious reflectivity is the starting point of a morally responsible action, which explains why a decision is 'up to the subject'. A free decision does not always have a complete causal history. This kind of an emergentist source hyper-incompatibilism seems to be the best direction of the search for an adequate explanation of moral responsibility in the traditional (merit-based) sense. Physical causal determinism as a universal theory would exclude morally significant freedom and responsibility in the traditional sense because it would exclude the emergence of and supervenience by the essential complex properties of human consciousness.

Keywords: consciousness, free will, determinism, emergence, moral responsibility

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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: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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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: J. Dutton, L. Knight

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Achieving quality and respectful maternal health care is part of the global agenda to improve reproductive health and achieve universal reproductive rights. Barriers to quality of care in South African maternal health facilities exist at both systemic and individual levels. Addition to this, the normalization of gender violence within South Africa has a large impact on people seeking health care as well as those who provide care within health facilities. The hierarchical environment of South Africa’s public health system penalizes both patients and providers who battle to assume any assessable power. This paper explores how systemic and individual level barriers to quality of care affect the midwifery profession within South African maternal health services and create, at times, an environment of enmity rather than care. This paper analyzes and discusses the data collected from in-depth, semi-structured interviews with nurses and midwives at three maternal health facilities in South Africa. This study has taken a holistic approach to understand the realities of nurses and midwives in order to explore the ways in which experience informs their practice and treatment of pregnant women. Through collecting and analyzing narratives, linkages between nurses and midwives day-to-day and historical experiences and disrespectful care have been made. Findings from this study show that barriers to quality of care take form in complex and interrelated ways. The physical structure of the health facility, human resource shortages, and the current model of maternal health care, which often lacks a person-centered approach, is entangled within personal beliefs and attitudes of what it means to be a midwife to create an environment that is often not conducive to a positive birthing experience. This entanglement sits within a society of high rates of violence, inequality, and poverty. Having teased out the nuances of each of these barriers and the multiple ways they reinforce each other, the findings of this paper demonstrate that birth, and the work of a midwife, are situated in a mode of discipline and punishment within this context. For analytical purposes, this paper has broken down the individual barriers to quality care and discusses the current and historical significance before returning to the interrelated forms in which barriers to quality maternal health care manifest. In conclusion this paper questions the role of agency in the ability to subvert systemic barriers to quality care and ideas around shifting attitudes and beliefs of and about midwives. International and local policies and guidelines have a role to play in realizing such shifts, however, as this paper suggests, when policy does not speak to the local context there is the risk of it contributing to frustrations and impeding the path to quality and respectful maternal health care.

Keywords: disrespect and abuse in childbirth, midwifery, South African maternal health care, quality of care

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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: Shirley S. Ho

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The advancement and development of social media have inadvertently brought about a new form of bullying – cyberbullying – that transcends across physical boundaries of space. Although extensive research has been conducted in the field of cyberbullying, most of these studies have taken an overwhelmingly empirical angle. Theories guiding cyberbullying research are few. Furthermore, very few studies have explored the association between parental mediation and cyberbullying, with majority of existing studies focusing on cyberbullying victimization rather than perpetration. Therefore, this present study investigates cyberbullying perpetration from a theoretical angle, with a focus on the Theory of Reasoned Action and the Parental Mediation Theory. More specifically, this study examines the direct effects of attitude, subjective norms, descriptive norms, injunctive norms and active mediation and restrictive mediation on cyberbullying perpetration on social media among children and adolescents in Singapore. Furthermore, the moderating role of age on the relationship between parental mediation and cyberbullying perpetration on social media are examined. A self-administered paper-and-pencil nationally-representative survey was conducted. Multi-stage cluster random sampling was used to ensure that schools from all the four (North, South, East, and West) regions of Singapore were equally represented in the sample used for the survey. In all 607 upper primary school children (i.e., Primary 4 to 6 students) and 782 secondary school adolescents participated in our survey. The total average response rates were 69.6% for student participation. An ordinary least squares hierarchical regression analysis was conducted to test the hypotheses and research questions. The results revealed that attitude and subjective norms were positively associated with cyberbullying perpetration on social media. Descriptive norms and injunctive norms were not found to be significantly associated with cyberbullying perpetration. The results also showed that both parental mediation strategies were negatively associated with cyberbullying perpetration on social media. Age was a significant moderator of both parental mediation strategies and cyberbullying perpetration. The negative relationship between active mediation and cyberbullying perpetration was found to be greater in the case of children than adolescents. Children who received high restrictive parental mediation were less likely to perform cyberbullying behaviors, while adolescents who received high restrictive parental mediation were more likely to be engaged in cyberbullying perpetration. The study reveals that parents should apply active mediation and restrictive mediation in different ways for children and adolescents when trying to prevent cyberbullying perpetration. The effectiveness of active parental mediation for reducing cyberbullying perpetration was more in the case of children than for adolescents. Younger children were found to be more likely to respond more positively toward restrictive parental mediation strategies, but in the case of adolescents, overly restrictive control was found to increase cyberbullying perpetration. Adolescents exhibited less cyberbullying behaviors when under low restrictive strategies. Findings highlight that the Theory of Reasoned Action and Parental Mediation Theory are promising frameworks to apply in the examination of cyberbullying perpetration. The findings that different parental mediation strategies had differing effectiveness, based on the children’s age, bring about several practical implications that may benefit educators and parents when addressing their children’s online risk.

Keywords: cyberbullying perpetration, theory of reasoned action, parental mediation, social media, Singapore

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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: Vangmayee V. Subban, Suzan Deelan. Pinto, Somashekara Haralakatta Shivananjappa, Shwetha Prabhu, Jayashree S. Bhat

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Introduction and Need: During early years of schooling, the instruction in the schools mainly focus on children’s word decoding abilities. However, the skilled readers should master all the components of reading such as word decoding, reading fluency and comprehension. Nevertheless, the relationship between each component during the process of learning to read is less clear. The studies conducted in alphabetical languages have mixed opinion on relative contribution of word decoding and reading fluency on reading comprehension. However, the scenarios in alphasyllabary languages are unexplored. Aim and Objectives: The aim of the study was to explore the role of word decoding, reading fluency on reading comprehension abilities in children learning to read Kannada between the age ranges of 5.6 to 8.6 years. Method: In this cross sectional study, a total of 60 typically developing children, 20 each from Grade I, Grade II, Grade III maintaining equal gender ratio between the age range of 5.6 to 6.6 years, 6.7 to 7.6 years and 7.7 to 8.6 years respectively were selected from Kannada medium schools. The reading fluency and reading comprehension abilities of the children were assessed using Grade level passages selected from the Kannada text book of children core curriculum. All the passages consist of five questions to assess reading comprehension. The pseudoword decoding skills were assessed using 40 pseudowords with varying syllable length and their Akshara composition. Pseudowords are formed by interchanging the syllables within the meaningful word while maintaining the phonotactic constraints of Kannada language. The assessment material was subjected to content validation and reliability measures before collecting the data on the study samples. The data were collected individually, and reading fluency was assessed for words correctly read per minute. Pseudoword decoding was scored for the accuracy of reading. Results: The descriptive statistics indicated that the mean pseudoword reading, reading comprehension, words accurately read per minute increased with the Grades. The performance of Grade III children found to be higher, Grade I lower and Grade II remained intermediate of Grade III and Grade I. The trend indicated that reading skills gradually improve with the Grades. Pearson’s correlation co-efficient showed moderate and highly significant (p=0.00) positive co-relation between the variables, indicating the interdependency of all the three components required for reading. The hierarchical regression analysis revealed 37% variance in reading comprehension was explained by pseudoword decoding and was highly significant. Subsequent entry of reading fluency measure, there was no significant change in R-square and was only change 3%. Therefore, pseudoword-decoding evolved as a single most significant predictor of reading comprehension during early Grades of reading acquisition. Conclusion: The present study concludes that the pseudoword decoding skills contribute significantly to reading comprehension than reading fluency during initial years of schooling in children learning to read Kannada language.

Keywords: alphasyllabary, pseudo-word decoding, reading comprehension, reading fluency

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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: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Xiaochen Mu

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Data rights confirmation, as a key legal issue in the development of the digital economy, is undergoing a transition from a traditional rights paradigm to a more complex private-economic paradigm. In this process, data rights confirmation has evolved from a simple claim of rights to a complex structure encompassing multiple dimensions of personality rights and property rights. Current data rights confirmation practices are primarily reflected in two models: holistic rights confirmation and process rights confirmation. The holistic rights confirmation model continues the traditional "one object, one right" theory, while the process rights confirmation model, through contractual relationships in the data processing process, recognizes rights that are more adaptable to the needs of data circulation and value release. In the design of the data property rights system, there is a hierarchical characteristic aimed at decoupling from raw data to data applications through horizontal stratification and vertical staging. This design not only respects the ownership rights of data originators but also, based on the usufructuary rights of enterprises, constructs a corresponding rights system for different stages of data processing activities. The subjects of data property rights include both data originators, such as users, and data producers, such as enterprises, who enjoy different rights at different stages of data processing. The intellectual property rights system, with the mission of incentivizing innovation and promoting the advancement of science, culture, and the arts, provides a complete set of mechanisms for protecting innovative results. However, unlike traditional private property rights, the granting of intellectual property rights is not an end in itself; the purpose of the intellectual property system is to balance the exclusive rights of the rights holders with the prosperity and long-term development of society's public learning and the entire field of science, culture, and the arts. Therefore, the intellectual property granting mechanism provides both protection and limitations for the rights holder. This perfectly aligns with the dual attributes of data. In terms of achieving the protection of data property rights, the granting of intellectual property rights is an important institutional choice that can enhance the effectiveness of the data property exchange mechanism. Although this is not the only path, the granting of data property rights within the framework of the intellectual property rights system helps to establish fundamental legal relationships and rights confirmation mechanisms and is more compatible with the classification and grading system of data. The modernity of the intellectual property rights system allows it to adapt to the needs of big data technology development through special clauses or industry guidelines, thus promoting the comprehensive advancement of data intellectual property rights legislation. This paper analyzes data protection under the virtual property layer theory and two-fold virtual property rights system. Based on the “bundle of right” theory, this paper establishes specific three-level data rights. This paper analyzes the cases: Google v. Vidal-Hall, Halliday v Creation Consumer Finance, Douglas v Hello Limited, Campbell v MGN and Imerman v Tchenquiz. This paper concluded that recognizing property rights over personal data and protecting data under the framework of intellectual property will be beneficial to establish the tort of misuse of personal information.

Keywords: data protection, property rights, intellectual property, Big data

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Authors: Lidiia Nazarenko, Henryk Stolarski, Holm Altenbach

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In the paper, a (hierarchical) approach to analysis of thermo-elastic properties of random composites with interphases is outlined and illustrated. It is based on the statistical homogenization method – the method of conditional moments – combined with recently introduced notion of the energy-equivalent inhomogeneity which, in this paper, is extended to include thermal effects. After exposition of the general principles, the approach is applied in the investigation of the effective thermo-elastic properties of a material with randomly distributed nanoparticles. The basic idea of equivalent inhomogeneity is to replace the inhomogeneity and the surrounding it interphase by a single equivalent inhomogeneity of constant stiffness tensor and coefficient of thermal expansion, combining thermal and elastic properties of both. The equivalent inhomogeneity is then perfectly bonded to the matrix which allows to analyze composites with interphases using techniques devised for problems without interphases. From the mechanical viewpoint, definition of the equivalent inhomogeneity is based on Hill’s energy equivalence principle, applied to the problem consisting only of the original inhomogeneity and its interphase. It is more general than the definitions proposed in the past in that, conceptually and practically, it allows to consider inhomogeneities of various shapes and various models of interphases. This is illustrated considering spherical particles with two models of interphases, Gurtin-Murdoch material surface model and spring layer model. The resulting equivalent inhomogeneities are subsequently used to determine effective thermo-elastic properties of randomly distributed particulate composites. The effective stiffness tensor and coefficient of thermal extension of the material with so defined equivalent inhomogeneities are determined by the method of conditional moments. Closed-form expressions for the effective thermo-elastic parameters of a composite consisting of a matrix and randomly distributed spherical inhomogeneities are derived for the bulk and the shear moduli as well as for the coefficient of thermal expansion. Dependence of the effective parameters on the interphase properties is included in the resulting expressions, exhibiting analytically the nature of the size-effects in nanomaterials. As a numerical example, the epoxy matrix with randomly distributed spherical glass particles is investigated. The dependence of the effective bulk and shear moduli, as well as of the effective thermal expansion coefficient on the particle volume fraction (for different radii of nanoparticles) and on the radius of nanoparticle (for fixed volume fraction of nanoparticles) for different interphase models are compared to and discussed in the context of other theoretical predictions. Possible applications of the proposed approach to short-fiber composites with various types of interphases are discussed.

Keywords: effective properties, energy equivalence, Gurtin-Murdoch surface model, interphase, random composites, spherical equivalent inhomogeneity, spring layer model

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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

Procedia PDF Downloads 535

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

Procedia PDF Downloads 59

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

Procedia PDF Downloads 188

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

Procedia PDF Downloads 129

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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Authors: Felice De Luca, Vincenzo Galdi, Piera Stella, Vito Calderaro, Adriano Campagna, Antonio Piccolo

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Sustainable mobility has become one of the major issues of recent years. The challenge in reducing polluting emissions as much as possible has led to the production and diffusion of vehicles with internal combustion engines that are less polluting and to the adoption of green energy vectors, such as vehicles powered by natural gas or LPG and, more recently, with hybrid and electric ones. While on the one hand, the spread of electric vehicles for private use is becoming a reality, albeit rather slowly, not the same is happening for vehicles used for public transport, especially those that operate in the congested areas of the cities. Even if the first electric buses are increasingly being offered on the market, it remains central to the problem of autonomy for battery fed vehicles with high daily routes and little time available for recharging. In fact, at present, solid-state batteries are still too large in size, heavy, and unable to guarantee the required autonomy. Therefore, in order to maximize the energy management on the vehicle, the optimization of driving profiles offer a faster and cheaper contribution to improve vehicle autonomy. In this paper, following the authors’ precedent works on electric vehicles in public transport and energy management strategies in the electric mobility area, an eco-driving strategy for electric bus is presented and validated. Particularly, the characteristics of the prototype bus are described, and a general-purpose eco-drive methodology is briefly presented. The model is firstly simulated in MATLAB™ and then implemented on a mobile device installed on-board of a prototype bus developed by the authors in a previous research project. The solution implemented furnishes the bus-driver suggestions on the guide style to adopt. The result of the test in a real case will be shown to highlight the effectiveness of the solution proposed in terms of energy saving.

Keywords: eco-drive, electric bus, energy management, prototype

Procedia PDF Downloads 141

Authors: Samuel Abraham Berhane, Lingbing Bu

Abstract:

This paper presents the spatiotemporal variability of aerosols, clouds, and precipitation within the major cities in Eritrea and it investigates the relationship between aerosols, clouds, and precipitation concerning the presence of aerosols over the study region. In Eritrea, inadequate water supplies will have both direct and indirect adverse impacts on sustainable development in areas such as health, agriculture, energy, communication, and transport. Besides, there exists a gap in the knowledge on suitable and potential areas for cloud seeding. Further, the inadequate understanding of aerosol-cloud-precipitation (ACP) interactions limits the success of weather modification aimed at improving freshwater sources, storage, and recycling. Spatiotemporal variability of aerosols, clouds, and precipitation involve spatial and time series analysis based on trend and anomaly analysis. To find the relationship between aerosols and clouds, a correlation coefficient is used. The spatiotemporal analysis showed larger variations of aerosols within the last two decades, especially in Assab, indicating that aerosol optical depth (AOD) has increased over the surrounding Red Sea region. Rainfall was significantly low but AOD was significantly high during the 2011 monsoon season. Precipitation was high during 2007 over most parts of Eritrea. The correlation coefficient between AOD and rainfall was negative over Asmara and Nakfa. Cloud effective radius (CER) and cloud optical thickness (COT) exhibited a negative correlation with AOD over Nakfa within the June–July–August (JJA) season. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model that is used to find the path and origin of the air mass of the study region showed that the majority of aerosols made their way to the study region via the westerly and the southwesterly winds.

Keywords: aerosol-cloud-precipitation, aerosol optical depth, cloud effective radius, cloud optical thickness, HYSPLIT

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Authors: Helen Potkin

Abstract:

This paper presents a practice-based case study of a project in which the student group designed and planned the curriculum content, classroom activities and assessment briefs in collaboration with the tutor. It focuses on the co-creation of the curriculum within a history and theory module, Researching the Contemporary, which runs for BA (Hons) Fine Art and Art History and for BA (Hons) Art Design History Practice at Kingston University, London. The paper analyses the potential of collaborative approaches to engender students’ investment in their own learning and to encourage reflective and self-conscious understandings of themselves as learners. It also addresses some of the challenges of working in this way, attending to the risks involved and feelings of uncertainty produced in experimental, fluid and open situations of learning. Alongside this, it acknowledges the tensions inherent in adopting such practices within the framework of the institution and within the wider of context of the commodification of higher education in the United Kingdom. The concept underpinning the initiative was to test out co-creation as a creative process and to explore the possibilities of altering the traditional hierarchical relationship between teacher and student in a more active, participatory environment. In other words, the project asked about: what kind of learning could be imagined if we were all in it together? It considered co-creation as producing different ways of being, or becoming, as learners, involving us reconfiguring multiple relationships: to learning, to each other, to research, to the institution and to our emotions. The project provided the opportunity for students to bring their own research and wider interests into the classroom, take ownership of sessions, collaborate with each other and to define the criteria against which they would be assessed. Drawing on students’ reflections on their experience of co-creation alongside theoretical considerations engaging with the processual nature of learning, concepts of equality and the generative qualities of the interrelationships in the classroom, the paper suggests that the dynamic nature of collaborative and participatory modes of engagement have the potential to foster relevant and significant learning experiences. The findings as a result of the project could be quantified in terms of the high level of student engagement in the project, specifically investment in the assessment, alongside the ambition and high quality of the student work produced. However, reflection on the outcomes of the experiment prompts a further set of questions about the nature of positionality in connection to learning, the ways our identities as learners are formed in and through our relationships in the classroom and the potential and productive nature of creative practice in education. Overall, the paper interrogates questions of what it means to work with students to invent and assemble the curriculum and it assesses the benefits and challenges of co-creation. Underpinning it is the argument that, particularly in the current climate of higher education, it is increasingly important to ask what it means to teach and to envisage what kinds of learning can be possible.

Keywords: co-creation, collaboration, learning, participation, risk

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Authors: Getachew Weldemichael, Sentayehu Alamerew, Leta Tulu, Gezahegn Berecha

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Coffee quality improvement program is becoming the focus of coffee research, as the world coffee consumption pattern shifted to high-quality coffee. However, there is limited information on the genetic variation of C. Arabica for quality improvement in potential specialty coffee growing areas of Ethiopia. Therefore, this experiment was conducted with the objectives of determining the magnitude of variation among 105 coffee accessions collected from east Wollega coffee growing areas and assessing correlations between the different coffee qualities attributes. It was conducted in RCRD with three replications. Data on green bean physical characters (shape and make, bean color and odor) and organoleptic cup quality traits (aromatic intensity, aromatic quality, acidity, astringency, bitterness, body, flavor, and overall standard of the liquor) were recorded. Analysis of variance, clustering, genetic divergence, principal component and correlation analysis was performed using SAS software. The result revealed that there were highly significant differences (P<0.01) among the accessions for all quality attributes except for odor and bitterness. Among the tested accessions, EW104 /09, EW101 /09, EW58/09, EW77/09, EW35/09, EW71/09, EW68/09, EW96 /09, EW83/09 and EW72/09 had the highest total coffee quality values (the sum of bean physical and cup quality attributes). These genotypes could serve as a source of genes for green bean physical characters and cup quality improvement in Arabica coffee. Furthermore, cluster analysis grouped the coffee accessions into five clusters with significant inter-cluster distances implying that there is moderate diversity among the accessions and crossing accessions from these divergent inter-clusters would result in hetrosis and recombinants in segregating generations. The principal component analysis revealed that the first three principal components with eigenvalues greater than unity accounted for 83.1% of the total variability due to the variation of nine quality attributes considered for PC analysis, indicating that all quality attributes equally contribute to a grouping of the accessions in different clusters. Organoleptic cup quality attributes showed positive and significant correlations both at the genotypic and phenotypic levels, demonstrating the possibility of simultaneous improvement of the traits. Path coefficient analysis revealed that acidity, flavor, and body had a high positive direct effect on overall cup quality, implying that these traits can be used as indirect criteria to improve overall coffee quality. Therefore, it was concluded that there is considerable variation among the accessions, which need to be properly conserved for future improvement of the coffee quality. However, the variability observed for quality attributes must be further verified using biochemical and molecular analysis.

Keywords: accessions, Coffea arabica, cluster analysis, correlation, principal component

Procedia PDF Downloads 165