Search results for: traditional medicine

Authors: Frederica Pettit

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Contribution: Stakeholder involvement in CSR is essential to ensuring pro-environmental attitudes and behaviours across multi-stakeholder groups. Despite increased awareness of the benefits surrounding a collaborative approach to sustainability communications, its success is limited by difficulties engaging with active online conversations with stakeholder groups. Whilst previous research defines the effectiveness of sustainability communications; this paper contributes to knowledge through the development of a theoretical framework that explores the processes to achieving pro-environmental attitudes and behaviours in stakeholder groups. The research will also consider social media as an opportunity to communicate CSR information to all stakeholder groups. Approach: A systematic review was chosen to investigate the effectiveness of the types of sustainability communications used in the hospitality and tourism industries. The systematic review was completed using Web of Science and Scopus using the search terms “sustainab* communicat*” “effective or effectiveness,” and “hospitality or tourism,” limiting the results to peer-reviewed research. 133 abstracts were initially read, with articles being excluded for irrelevance, duplicated articles, non-empirical studies, and language. A total of 45 papers were included as part of the systematic review. 5 propositions were created based on the results of the systematic review, helping to develop a theoretical framework of the processes needed for companies to encourage pro-environmental behaviours across multi-stakeholder groups. Results: The theoretical framework developed in the paper determined the processes necessary for companies to achieve pro-environmental behaviours in stakeholders. The processes to achieving pro-environmental attitudes and behaviours are stakeholder-focused, identifying the need for communications to be specific to their targeted audience. Collaborative communications that enable stakeholders to engage with CSR information and provide feedback lead to a higher awareness of CSR shared visions and pro-environmental attitudes and behaviours. These processes should also aim to improve their relationships with stakeholders through transparency of CSR, CSR strategies that match stakeholder values and ethics whilst prioritizing sustainability as part of their job role. Alternatively, companies can prioritize pro-environmental behaviours using choice editing by mainstreaming sustainability as the only option. In recent years, there has been extensive research on social media as a viable source of sustainability communications, with benefits including direct interactions with stakeholders, the ability to enforce the authenticity of CSR activities and encouragement of pro-environmental behaviours. Despite this, there are challenges to implementing CSR, including difficulties controlling stakeholder criticisms, negative stakeholder influences and comments left on social media platforms. Conclusion: A lack of engagement with CSR information is a reoccurring reason for preventing pro-environmental attitudes and behaviours across stakeholder groups. Traditional CSR strategies contribute to this due to their inability to engage with their intended audience. Hospitality and tourism companies are improving stakeholder relationships through collaborative processes which reduce single-use plastic consumption. A collaborative approach to communications can lead to stakeholder satisfaction, leading to changes in attitudes and behaviours. Different sources of communications are accessed by different stakeholder groups, identifying the need for targeted sustainability messaging, creating benefits such as direct interactions with stakeholders, the ability to enforce the authenticity of CSR activities, and encouraging engagement with sustainability information.

Keywords: hospitality, pro-environmental attitudes and behaviours, sustainability communication, social media

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

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Authors: Sevelina Ndlovu

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Financial Technology (fintech) advancement is recognised as one of the most transformational innovations in the financial industry. Fintech has given rise to internet-only digital banking, a novel financial technology advancement, and innovation that allows banking services through internet applications with no need for physical branches. This technology is becoming a new banking normal among consumers for its ubiquitous and real-time access advantages. There is evident switching and migration from traditional banking towards these fintech facilities, which could possibly pose a systemic risk if not properly understood and monitored. Fintech advancement has also brought about the emergence and escalation of financial technology consumption themes such as trust, security, perceived risk, and sustainability within the banking industry, themes scarcely covered in existing theoretic literature. To that end, the objective of this research is to investigate factors that determine fintech adoption and propose an integrated adoption model. This study aims to establish what the significant drivers of adoption are and develop a conceptual model that integrates technological, behavioral, and environmental constructs by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). It proposes integrating constructs that influence financial consumption themes such as trust, perceived risk, security, financial incentives, micro-investing opportunities, and environmental consciousness to determine the impact of these factors on the adoption and intention to use digital banking apps. The main advantage of this conceptual model is the consolidation of a greater number of predictor variables that can provide a fuller explanation of the consumer's adoption of digital banking Apps. Moderating variables of age, gender, and income are incorporated. To the best of author’s knowledge, this study is the first that extends the UTAUT2 model with this combination of constructs to investigate user’s intention to adopt internet-only digital banking apps in the UK context. By investigating factors that are not included in the existing theories but are highly pertinent to the adoption of internet-only banking services, this research adds to existing knowledge and extends the generalisability of the UTAUT2 in a financial services adoption context. This is something that fills a gap in knowledge, as highlighted to needing further research on UTAUT2 after reviewing the theory in 2016 from its original version of 2003. To achieve the objectives of this study, this research assumes a quantitative research approach to empirically test the hypotheses derived from existing literature and pilot studies to give statistical support to generalise the research findings for further possible applications in theory and practice. This research is explanatory or casual in nature and uses cross-section primary data collected through a survey method. Convenient and purposive sampling using structured self-administered online questionnaires is used for data collection. The proposed model is tested using Structural Equation Modelling (SEM), and the analysis of primary data collected through an online survey is processed using Smart PLS software with a sample size of 386 digital bank users. The results are expected to establish if there are significant relationships between the dependent and independent variables and establish what the most influencing factors are.

Keywords: banking applications, digital banking, financial technology, technology adoption, UTAUT2

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Authors: Sini George

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Active learning pedagogies are valued for their success in increasing 21st-century learners’ engagement, developing transferable skills like critical thinking or quantitative reasoning, and creating deeper and more lasting educational gains. 'Blended learning' is an active learning pedagogical approach in which direct instruction moves from the group learning space to the individual learning space, and the resulting group space is transformed into a dynamic, interactive learning environment where the educator guides students as they apply concepts and engage creatively in the subject matter. This project aimed to develop a blended learning instructional approach to teaching concepts around pharmaceutical calculations to year 1 pharmacy students. The wrong dose, strength or frequency of a medication accounts for almost a third of medication errors in the NHS therefore, progression to year 2 requires a 70% pass in this calculation test, in addition to the standard progression requirements. Many students were struggling to achieve this requirement in the past. It was also challenging to teach these concepts to students of a large class (> 130) with mixed mathematical abilities, especially within a traditional didactic lecture format. Therefore, short screencasts with voice-over of the lecturer were provided in advance of a total of four teaching sessions (two hours/session), incorporating core content of each session and talking through how they approached the calculations to model metacognition. Links to the screencasts were posted on the learning management. Viewership counts were used to determine that the students were indeed accessing and watching the screencasts on schedule. In the classroom, students had to apply the knowledge learned beforehand to a series of increasingly difficult set of questions. Students were then asked to create a question in group settings (two students/group) and to discuss the questions created by their peers in their groups to promote deep conceptual learning. Students were also given time for question-and-answer period to seek clarifications on the concepts covered. Student response to this instructional approach and their test grades were collected. After collecting and organizing the data, statistical analysis was carried out to calculate binomial statistics for the two data sets: the test grade for students who received blended learning instruction and the test grades for students who received instruction in a standard lecture format in class, to compare the effectiveness of each type of instruction. Student response and their performance data on the assessment indicate that the learning of content in the blended learning instructional approach led to higher levels of student engagement, satisfaction, and more substantial learning gains. The blended learning approach enabled each student to learn how to do calculations at their own pace freeing class time for interactive application of this knowledge. Although time-consuming for an instructor to implement, the findings of this research demonstrate that the blended learning instructional approach improves student academic outcomes and represents a valuable method to incorporate active learning methodologies while still maintaining broad content coverage. Satisfaction with this approach was high, and we are currently developing more pharmacy content for delivery in this format.

Keywords: active learning, blended learning, deep conceptual learning, instructional approach, metacognition, pharmaceutical calculations

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Authors: Victor Kang, Sirene Bellahnid, Amy Al-Simaani

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Efficient documentation and completion of clerical tasks are pillars of efficient patient-centered care in acute settings such as the emergency department (ED). Medical scribes aid physicians with documentation, navigation of electronic health records, results gathering, and communication coordination with other healthcare teams. However, the use of medical scribes is not widespread, with some hospitals even continuing to discontinue their programs. One reason for this could be the lack of studies that have outlined concrete improvements in efficiency and patient and provider satisfaction in emergency departments before and after incorporating scribes. Methods: We conducted a review of the literature concerning the implementation of a medical scribe program and emergency department performance. For this review, a narrative synthesis accompanied by textual commentaries was chosen to present the selected papers. PubMed was searched exclusively. Initially, no date limits were set, but seeing as the electronic medical record was officially implemented in Canada in 2013, studies published after this date were preferred as they provided insight into the interplay between its implementation and scribes on quality improvement. Results: Throughput, efficiency, and cost-effectiveness were the most commonly used parameters in evaluating scribes in the Emergency Department. Important throughput metrics, specifically door-to-doctor and disposition time, were significantly decreased in emergency departments that utilized scribes. Of note, this was shown to be the case in community hospitals, where the burden of documentation and clerical tasks would fall directly upon the attending physician. Academic centers differ in that they rely heavily on residents and students; so the implementation of scribes has been shown to have limited effect on these metrics. However, unique to academic centers was the provider’s perception of incrased time for teaching was unique to academic centers. Consequently, providers express increased work satisfaction in relation to time spent with patients and in teaching. Patients, on the other hand, did not demonstrate a decrease in satisfaction in regards to the care that was provided, but there was no significant increase observed either. Of the studies we reviewed, one of the biggest limitations was the lack of significance in the data. While many individual studies reported that medical scribes in emergency rooms improved relative value units, patient satisfaction, provider satisfaction, and increased number of patients seen, there was no statistically significant improvement in the above criteria when compiled in a systematic review. There is also a clear publication bias; very few studies with negative results were published. To prove significance, data from more emergency rooms with scribe programs would need to be compiled which also includes emergency rooms who did not report noticeable benefits. Furthermore, most data sets focused only on scribes in academic centers. Conclusion: Ultimately, the literature suggests that while emergency room physicians who have access to medical scribes report higher satisfaction due to lower clerical burdens and can see more patients per shift, there is still variability in terms of patient and provider satisfaction. Whether or not this variability exists due to differences in training (in-house trainees versus contractors), population profile (adult versus pediatric), setting (academic versus community), or which shifts scribe work cannot be determined based on the studies that exist. Ultimately, more scribe programs need to be evaluated to determine whether these variables affect outcomes and prove whether scribes significantly improve emergency room efficiency.

Keywords: emergency medicine, medical scribe, scribe, documentation

Procedia PDF Downloads 71

Authors: Zofija Tupikovskaja-Omovie, David Tyler, Sam Dhanapala, Steve Hayes

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The UK is leading in online retail and mobile adoption. However, there is a dearth of information relating to mobile apparel retail, and developing an understanding about consumer browsing and purchase behavior in m-retail channel would provide apparel marketers, mobile website and app developers with the necessary understanding of consumers’ needs. Despite the rapid growth of mobile retail businesses, no published study has examined shopping behaviour on fashion mobile websites and apps. A mixed method approach helped to understand why fashion consumers prefer websites on mobile devices, when mobile apps are also available. The following research methods were employed: survey, eye-tracking experiments, observation, and interview with retrospective think aloud. The mobile gaze tracking device by SensoMotoric Instruments was used to understand frustrations in navigation and other issues facing consumers in mobile channel. This method helped to validate and compliment other traditional user-testing approaches in order to optimize user experience and enhance the development of mobile retail channel. The study involved eight participants - females aged 18 to 35 years old, who are existing mobile shoppers. The participants used the Topshop mobile app and website on a smart phone to complete a task according to a specified scenario leading to a purchase. The comparative study was based on: duration and time spent at different stages of the shopping journey, number of steps involved and product pages visited, search approaches used, layout and visual clues, as well as consumer perceptions and expectations. The results from the data analysis show significant differences in consumer behaviour when using a mobile app or website on a smart phone. Moreover, two types of problems were identified, namely technical issues and human errors. Having a mobile app does not guarantee success in satisfying mobile fashion consumers. The differences in the layout and visual clues seem to influence the overall shopping experience on a smart phone. The layout of search results on the website was different from the mobile app. Therefore, participants, in most cases, behaved differently on different platforms. The number of product pages visited on the mobile app was triple the number visited on the website due to a limited visibility of products in the search results. Although, the data on traffic trends held by retailers to date, including retail sector breakdowns for visits and views, data on device splits and duration, might seem a valuable source of information, it cannot explain why consumers visit many product pages, stay longer on the website or mobile app, or abandon the basket. A comprehensive list of pros and cons was developed by highlighting issues for website and mobile app, and recommendations provided. The findings suggest that fashion retailers need to be aware of actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added to which is the challenge of retaining existing and acquiring new customers. There seem to be differences in the way fashion consumers search and shop on mobile, which need to be explored in further studies.

Keywords: consumer behavior, eye-tracking technology, fashion retail, mobile app, m-retail, smart phones, topshop, user experience, website

Procedia PDF Downloads 424

Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Wei Ji

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This study was conducted in the Kansas City metropolitan area of the United States, which has experienced significant urban sprawling in recent decades. The remote sensing of land cover changes in this area spanned over four decades from 1972 through 2010. The project was implemented in two stages: the first stage focused on detection of long-term trends of urban land cover change, while the second one examined how to detect the coupled effects of human impact and climate change on urban landscapes. For the first-stage study, six Landsat images were used with a time interval of about five years for the period from 1972 through 2001. Four major land cover types, built-up land, forestland, non-forest vegetation land, and surface water, were mapped using supervised image classification techniques. The study found that over the three decades the built-up lands in the study area were more than doubled, which was mainly at the expense of non-forest vegetation lands. Surprisingly and interestingly, the area also saw a significant gain in surface water coverage. This observation raised questions: How have human activities and precipitation variation jointly impacted surface water cover during recent decades? How can we detect such coupled impacts through remote sensing analysis? These questions led to the second stage of the study, in which we designed and developed approaches to detecting fine-scale surface waters and analyzing coupled effects of human impact and precipitation variation on the waters. To effectively detect urban landscape changes that might be jointly shaped by precipitation variation, our study proposed “urban wetscapes” (loosely-defined urban wetlands) as a new indicator for remote sensing detection. The study examined whether urban wetscape dynamics was a sensitive indicator of the coupled effects of the two driving forces. To better detect this indicator, a rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. Three SPOT images for years 1992, 2008, and 2010, respectively were classified with this technique to generate the four types of land cover as described above. The spatial analyses of remotely-sensed wetscape changes were implemented at the scales of metropolitan, watershed, and sub-watershed, as well as based on the size of surface water bodies in order to accurately reveal urban wetscape change trends in relation to the driving forces. The study identified that urban wetscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds in response to human impacts at different scales. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while generally smaller wetlands decreased mainly due to human development activities. These results confirm that wetscape dynamics can effectively reveal the coupled effects of human impact and climate change on urban landscapes. As such, remote sensing of this indicator provides new insights into the relationships between urban land cover changes and driving forces.

Keywords: urban land cover, human impact, climate change, rule-based classification, across-scale analysis

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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Authors: Jan F. Talts, Amit Saxena, Kåre Engkilde

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Chemotherapy-induced peripheral neuropathy (CIPN) is one of the most frequent side effects caused by anti-neoplastic agents, with a prevalence from 19 % to 85 %. Clinically, CIPN is a mostly sensory neuropathy leading to pain and to motor and autonomic changes. Due to its high prevalence among cancer patients, CIPN constitutes a major problem for both cancer patients and survivors, especially because currently, there is no single effective method of preventing CIPN. Hearing loss is the most common form of sensory impairment in humans and can be caused by ototoxic chemical compounds such as chemotherapy (platinum-based antineoplastic agents).In rodents, single or repeated cisplatin injections induce peripheral neuropathy and hearing impairment mimicking human disorder, allowing studying the efficacy of new pharmacological candidates in chemotherapy-induced hearing loss and peripheral neuropathy. RNA sequencing data from full term amniotic fluid (TAF) mesenchymal stemcell (MSC) clones was used to identify neural-specific markers present on TAF-MSC. Several prospective neural markers were tested by flow cytometry on cultured TAF-MSC. One of these markers was used for cell-sorting using Tyto MACSQuant cell sorter, and the neural marker positive cell population was expanded for several passages to the final therapeutic product stage. Peripheral neuropathy and hearing loss was induced in mice by administration of cisplatin in three week-long cycles. The efficacy of neural-specific TAF-MSC in treating hearing loss and pain perception was evaluated by administration of three injections of 3 million cells/kg by intravenous route or three injections of 3 million cells/kg by intra-arterial route after each cisplatin cycle treatment. Auditory brainstem responses (ABR) are electric potentials recorded from scalp electrodes, and the first ABR wave represents the summed activity of the auditory nerve fibers contacting the inner hair cells. For ABR studies, mice were anesthetized, then earphones were placed in the left ear of each mouse, an active electrode was placed in the vertex of the skull, a reference electrode under the skin of the mastoid bone, and a ground electrode in the neck skin. The stimuli consisted of tone pips of five frequencies (2, 4, 6, 12, 16, and 24 kHz) at various sound levels (from 0 to 90 dB) ranging to cover the mouse auditory frequency range. The von Frey test was used to assess the onset and maintenance of mechanical allodynia over time. Mice were placed in clear plexiglass cages on an elevated mesh floor and tested after 30 min of habituation. Mechanical paw withdrawal threshold was examined using an electronic von Frey anesthesiometer. Cisplatin groups treated with three injections of 3 million cells/kg by intravenous route and three injections of 3 million cells/kg by intra-arterial route after each cisplatin cycle treatment presented, a significant increase of hearing acuity characterized by a decrease of ABR threshold and a decrease of neuropathic pain characterized by an increase of von Frey paw withdrawal threshold compared to controls only receiving cisplatin. This study shows that treatment with MSCselected for neural specificity presents significant positive efficacy on the chemotherapy-induced neuropathic pain and the chemotherapy-induced hearing loss.

Keywords: mesenchymal stem cell, peripheral neuropathy, amniotic fluid, regenerative medicine

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

Procedia PDF Downloads 136

Authors: Leah Li Echiverri, Haoyu Shang, Yue Li

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Wenzhou-Kean University (WKU) is a Sino-US Cooperative University in China. It practices the English Immersion Program (EIP), where all the courses are taught in English. Class discussions and presentations are pervasively interwoven in designing students’ learning experiences. This WKU model has brought positive influences on students and is in some way ahead of traditional college English majors. However, literature to support the perceptions on the positive outcomes of this teaching and learning model remain scarce. The distinctive profile of Chinese-ESL students in an English Medium of Instruction (EMI) environment contributes further to the scarcity of literature compared to existing studies conducted among ESL learners in Western educational settings. Hence, the study investigated the students’ perceptions towards the English Immersion Program and determine how it influences Chinese-ESL students’ academic performance (AP). This research can provide empirical data that would be helpful to educators, teaching practitioners, university administrators, and other researchers in making informed decisions when developing curricular reforms, instructional and pedagogical methods, and university-wide support programs using this educational model. The purpose of the study was to establish the relationship between the English Immersion Program and Academic Performance among Chinese-ESL students enrolled at WKU for the academic year 2020-2021. Course length, immersion location, course type, and instructional design were the constructs of the English immersion program. English language learning, learning efficiency, and class participation were used to measure academic performance. Descriptive-correlational design was used in this cross-sectional research project. A quantitative approach for data analysis was applied to determine the relationship between the English immersion program and Chinese-ESL students’ academic performance. The research was conducted at WKU; a Chinese-American jointly established higher educational institution located in Wenzhou, Zhejiang province. Convenience, random, and snowball sampling of 283 students, a response rate of 10.5%, were applied to represent the WKU student population. The questionnaire was posted through the survey website named Wenjuanxing and shared to QQ or WeChat. Cronbach’s alpha was used to test the reliability of the research instrument. Findings revealed that when professors integrate technology (PowerPoint, videos, and audios) in teaching, students pay more attention. This contributes to the acquisition of more professional knowledge in their major courses. As to course immersion, students perceive WKU as a good place to study, providing them a high degree of confidence to talk with their professors in English. This also contributes to their English fluency and better pronunciation in their communication. In the construct of designing instruction, the use of pictures, video clips, and professors’ non-verbal communication, and demonstration of concern for students encouraged students to be more active in-class participation. Findings on course length and academic performance indicated that students’ perception regarding taking courses during fall and spring terms can moderately contribute to their academic performance. In conclusion, the findings revealed a significantly strong positive relationship between course type, immersion location, instructional design, and academic performance.

Keywords: class participation, English immersion program, English language learning, learning efficiency

Procedia PDF Downloads 146

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

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Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

Procedia PDF Downloads 230

Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

Procedia PDF Downloads 46

Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

Procedia PDF Downloads 95

Authors: Awatef Ahmed Ben Ramadan, Aqsa Arshad

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Background: There is a huge Muslim migration movement to North America and Europe for several reasons, primarily refuge from war areas and partly to search for better work and educational chances. There are always concerns regarding first-Generation Immigrant women's health and computer literacy, an adequate understanding of the health systems, and the use of the existing healthcare technology and services effectively and efficiently. Language proficiency level, preference for cultural and traditional remedies, socioeconomic factors, fear of stereotyping, limited accessibility to health services, and general unfamiliarity with the existing health services and resources are familiar variables among these women. Aims: The current study aims to assess the health and digital literacy of first-generation Muslim women in Atlanta city. Also, the study aims to examine how the COVID-19 pandemic has encouraged the use of health information technology and increased technology awareness among the targeted women. Methods: The study design is cross-sectional correlational research. The study will be conducted to produce preliminary results that the investigators want to have to supplement an NIH grant application about leveraging information technology to reduce the health inequalities amongst the first-generation immigrant Muslim women in Atlanta City. The investigators will collect the study data in two phases using different tools. Phase one was conducted in June 2022; the investigators used tools to measure health and digital literacy amongst 42 first-generation immigrant Muslim women. Phase two was conducted in November 2022; the investigators measured the Knowledge, Attitude, and Practice (KAP) of using health information technology such as telehealth from a sample of 45 first-generation Muslim immigrant women in Atlanta; in addition, the investigators measured how the current pandemic has affected their KAP to use telemedicine and telehealth services. Both phases' study participants were recruited using convenience sampling methodology. The investigators collected around 40 of 18 years old or older first-generation Muslim immigrant women for both study phases. The study excluded Immigrants who hold work visas and second-generation immigrants. Results: At the point of submitting this abstract, the investigators are still analyzing the study data to produce preliminary results to apply for an NIH grant entitled "Leveraging Health Information Technology (Health IT) to Address and Reduce Health Care Disparities (R01 Clinical Trial Optional)". This research will be the first step of a comprehensive research project to assess and measure health and digital literacy amongst a vulnerable community group. The targeted group might have different points of view from the U.S.-born inhabitants on how to: promote their health, gain healthy lifestyles and habits, screen for diseases, adhere to health treatment and follow-up plans, perceive the importance of using available and affordable technology to communicate with their providers and improve their health, and help in making serious decisions for their health. The investigators aim to develop an educational and instructional health mobile application considering the language and cultural factors that affect immigrants' ability to access different health and social support sources, know their health rights and obligations in their communities, and improve their health behavior and behavior lifestyles.

Keywords: first-generation immigrant Muslim women, telehealth, COVID-19 pandemic, health information technology, health and digital literacy

Procedia PDF Downloads 56

Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

Procedia PDF Downloads 117

Authors: Arjun Kumar Rath, Titus Dhanasingh

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Embedded product development requires software to test hardware functionality during development and finding issues during manufacturing in larger quantities. As the components are getting integrated, the devices are tested for their full functionality using advanced software tools. Benchmarking tools are used to measure and compare the performance of product features. At present, these tests are based on a variety of methods involving varying hardware and software platforms. Typically, these tests are custom built for every product and remain unusable for other variants. A majority of the tests goes undocumented, not updated, unusable when the product is released. To bridge this gap, a solution accelerator in the form of a framework can address these issues for running all these tests from one place, using an off-the-shelf tests library in a continuous integration environment. There are many open-source test frameworks or tools (fuego. LAVA, AutoTest, KernelCI, etc.) designed for testing embedded system devices, with each one having several unique good features, but one single tool and framework may not satisfy all of the testing needs for embedded systems, thus an extensible framework with the multitude of tools. Embedded product testing includes board bring-up testing, test during manufacturing, firmware testing, application testing, and assembly testing. Traditional test methods include developing test libraries and support components for every new hardware platform that belongs to the same domain with identical hardware architecture. This approach will have drawbacks like non-reusability where platform-specific libraries cannot be reused, need to maintain source infrastructure for individual hardware platforms, and most importantly, time is taken to re-develop test cases for new hardware platforms. These limitations create challenges like environment set up for testing, scalability, and maintenance. A desirable strategy is certainly one that is focused on maximizing reusability, continuous integration, and leveraging artifacts across the complete development cycle during phases of testing and across family of products. To get over the stated challenges with the conventional method and offers benefits of embedded testing, an embedded test framework (ETF), a solution accelerator, is designed, which can be deployed in embedded system-related products with minimal customizations and maintenance to accelerate the hardware testing. Embedded test framework supports testing different hardwares including microprocessor and microcontroller. It offers benefits such as (1) Time-to-Market: Accelerates board brings up time with prepacked test suites supporting all necessary peripherals which can speed up the design and development stage(board bring up, manufacturing and device driver) (2) Reusability-framework components isolated from the platform-specific HW initialization and configuration makes the adaptability of test cases across various platform quick and simple (3) Effective build and test infrastructure with multiple test interface options and preintegrated with FUEGO framework (4) Continuos integration - pre-integrated with Jenkins which enabled continuous testing and automated software update feature. Applying the embedded test framework accelerator throughout the design and development phase enables to development of the well-tested systems before functional verification and improves time to market to a large extent.

Keywords: board diagnostics software, embedded system, hardware testing, test frameworks

Procedia PDF Downloads 117

Authors: Loyd R. Hook, Maryam Moharek

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With the envisioned future growth of low altitude urban aircraft operations for airborne delivery service and advanced air mobility, strategies to coordinate and deconflict aircraft flight paths must be prioritized. Autonomous coordination and planning of flight trajectories is the preferred approach to the future vision in order to increase safety, density, and efficiency over manual methods employed today. Difficulties arise because any conflict resolution must be constrained by all other aircraft, all airspace restrictions, and all ground-based obstacles in the vicinity. These considerations make pair-wise tactical deconfliction difficult at best and unlikely to find a suitable solution for the entire system of vehicles. In addition, more traditional methods which rely on long time scales and large protected zones will artificially limit vehicle density and drastically decrease efficiency. Instead, strategic planning, which is able to respond to highly dynamic conditions and still account for high density operations, will be required to coordinate multiple vehicles in the highly constrained low altitude urban environment. This paper develops and evaluates such a planning algorithm which can be implemented autonomously across multiple aircraft and situations. Data from this evaluation provide promising results with simulations showing up to 10 aircraft deconflicted through a relatively narrow low-altitude urban canyon without any vehicle to vehicle or obstacle conflict. The algorithm achieves this level of coordination beginning with the assumption that each vehicle is controlled to follow an independently constructed flight path, which is itself free of obstacle conflict and restricted airspace. Then, by preferencing speed change deconfliction maneuvers constrained by the vehicles flight envelope, vehicles can remain as close to the original planned path and prevent cascading vehicle to vehicle conflicts. Performing the search for a set of commands which can simultaneously ensure separation for each pair-wise aircraft interaction and optimize the total velocities of all the aircraft is further complicated by the fact that each aircraft's flight plan could contain multiple segments. This means that relative velocities will change when any aircraft achieves a waypoint and changes course. Additionally, the timing of when that aircraft will achieve a waypoint (or, more directly, the order upon which all of the aircraft will achieve their respective waypoints) will change with the commanded speed. Put all together, the continuous relative velocity of each vehicle pair and the discretized change in relative velocity at waypoints resembles a hybrid reachability problem - a form of control reachability. This paper proposes two methods for finding solutions to these multi-body problems. First, an analytical formulation of the continuous problem is developed with an exhaustive search of the combined state space. However, because of computational complexity, this technique is only computable for pairwise interactions. For more complicated scenarios, including the proposed 10 vehicle example, a discretized search space is used, and a depth-first search with early stopping is employed to find the first solution that solves the constraints.

Keywords: strategic planning, autonomous, aircraft, deconfliction

Procedia PDF Downloads 70

Authors: Mei Xuan Tan, Gim-Yang Maggie Pee, Mei Chee Tan

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Academic performance, in the form of scoring high grades in enrolled subjects, is not the only significant trait in achieving success. Engineering graduates with experience in working on hands-on projects in a team setting are highly sought after in industry upon graduation. Such projects are typically real world problems that require the integration and application of knowledge and skills from several disciplines. In a traditional university setting, subjects are taught in a silo manner with no cross participation from other departments or disciplines. This may lead to knowledge compartmentalization and students are unable to understand and connect the relevance and applicability of the subject. University instructors thus see this integration across disciplines as a challenging task as they aim to better prepare students in understanding and solving problems for work or future studies. To improve students’ academic performance and to cultivate various skills such as critical thinking, there has been a gradual uptake in the use of an active learning approach in introductory science and engineering courses, where lecturing is traditionally the main mode of instruction. This study aims to discuss the implementation and experience of a hands-on, interdisciplinary project that involves all the four core subjects taught during the term at the Singapore University of Technology Design (SUTD). At SUTD, an interdisciplinary design activity, named 2D, is integrated into the curriculum to help students reinforce the concepts learnt. A student enrolled in SUTD experiences his or her first 2D in Term 1. This activity. which spans over one week in Week 10 of Term 1, highlights the application of chemistry, physics, mathematics, humanities, arts and social sciences (HASS) in designing an engineering product solution. The activity theme for Term 1 2D revolved around “work and play”. Students, in teams of 4 or 5, used a scaled-down model of a chemical launcher to launch a projectile across the room. It involved the use of a small chemical combustion reaction between ethanol (a highly volatile fuel) and oxygen. This reaction generated a sudden and large increase in gas pressure built up in a closed chamber, resulting in rapid gas expansion and ejection of the projectile out of the launcher. Students discussed and explored the meaning of play in their lives in HASS class while the engineering aspects of a combustion system to launch an object using underlying principles of energy conversion and projectile motion were revisited during the chemistry and physics classes, respectively. Numerical solutions on the distance travelled by the projectile launched by the chemical launcher, taking into account drag forces, was developed during the mathematics classes. At the end of the activity, students developed skills in report writing, data collection and analysis. Specific to this 2D activity, students gained an understanding and appreciation on the application and interdisciplinary nature of science, engineering and HASS. More importantly, students were exposed to design and problem solving, where human interaction and discussion are important yet challenging in a team setting.

Keywords: active learning, collaborative learning, first year undergraduate, interdisciplinary, STEAM

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Authors: Md. Nuru Miah, A. F. M. Akhter Uddin

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Medicinal plants are grown naturally in a tropical environment in Bangladesh and used as drug and therapeutic agents in the health care system. According to Bangladesh Agricultural Research Institute (BARI), there are 722 species of medicinal plants in the country. Of them, 255 plants are utilized by the manufacturers of Ayurvedic and Unani medicines. Medicinal plants like Aloevera, Ashwagonda, shotomul,Tulsi, Vuikumra, Misridana are extensively cultivated in some selected areas as well; where Aloevera scored the highest position in production. In the early 1980, Ayurvedic and Unani companies procured 80 percent of medicinal plants from natural forests, and the rest 20 percent was imported. Now the scenario has changed; 80 percent is imported, and the rest 20 percent is collected from local products(Source: Astudy on sectorbased need assessment of Business promotion council-Herbal products and medicinal plants, page-4). Uttara Development Program Society, a leading Non- Government development organization in Bangladesh, has been implementing a value chain development project under promoting Agricultural commercialization and Enterprises of Pally Karma Sahayak Foundation (PKSF) funded by the International Fund for Agricultural Development (IFAD) in Natore Sadar Upazila from April 2017 to sustainably develop the technological interventions for products and market development. The ultimate goal of the project is to increase income, generate employment and develop this sector as a sustainable business enterprise. Altogether 10,000 farmers (Nursery owners, growers, input supplier, processors, whole sellers, and retailers) are engaged in different activities of the project. The entrepreneurs engaged in medicinal plant cultivation did not know and follow environmental and good agricultural practices. They used to adopt traditional methodology in production and processing. Locally the farmers didn’t have any positive initiative to expand their business as well as developvalue added products. A lot of diversified products could be possible to develop and marketed with the introduction of post-harvest processing technology and market linkage with the local and global buyer. Training is imparted to the nursery owners and herbal growers on production technologies, sowing method, use of organic fertilizers/compost/pesticides, harvesting procedures, and storage facilities. Different types of herbal tea like Rosella, Moringa, Tulshi, and Basak are being produced and packed locally with a good scope of its marketing in different cities of the country. The project has been able to achieve a significant impact in the development of production technologies, but still, there is room for further improvement in processing, packaging, and marketing level. The core intervention of the current project to develop some entrepreneurs for branding, packaging, promotion, and marketing while considering environment friendly practices. The present strategies will strengthen the knowledge and skills of the entrepreneurs for the production and marketing of their products, maintaining worldwide accepted compliance system for easy access to the global market.

Keywords: aloe vera, herbs and shrubs, market, interventions

Procedia PDF Downloads 60

Authors: Eli Avraham

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The Arab Spring was widely covered in the global media and the number of Western tourists traveling to the area began to fall. The goal of this study was to analyze which media strategies marketers in Middle Eastern countries chose to employ in their attempts to repair the negative image of the area in the wake of the Arab Spring. Several studies were published concerning image-restoration strategies of destinations during crises around the globe; however, these strategies were not part of an overarching theory, conceptual framework or model from the fields of crisis communication and image repair. The conceptual framework used in the current study was the ‘multi-step model for altering place image’, which offers three types of strategies: source, message and audience. Three research questions were used: 1.What public relations crisis techniques and advertising campaign components were used? 2. What media policies and relationships with the international media were adopted by Arab officials? 3. Which marketing initiatives (such as cultural and sports events) were promoted? This study is based on qualitative content analysis of four types of data: 1) advertising components (slogans, visuals and text); (2) press interviews with Middle Eastern officials and marketers; (3) official media policy adopted by government decision-maker (e.g. boycotting or arresting newspeople); and (4) marketing initiatives (e.g. organizing heritage festivals and cultural events). The data was located in three channels from December 2010, when the events started, to September 31, 2013: (1) Internet and video-sharing websites: YouTube and Middle Eastern countries' national tourism board websites; (2) News reports from two international media outlets, The New York Times and Ha’aretz; these are considered quality newspapers that focus on foreign news and tend to criticize institutions; (3) Global tourism news websites: eTurbo news and ‘Cities and countries branding’. Using the ‘multi-step model for altering place image,’ the analysis reveals that Middle Eastern marketers and officials used three kinds of strategies to repair their countries' negative image: 1. Source (cooperation and media relations; complying, threatening and blocking the media; and finding alternatives to the traditional media) 2. Message (ignoring, limiting, narrowing or reducing the scale of the crisis; acknowledging the negative effect of an event’s coverage and assuring a better future; promotion of multiple facets, exhibitions and softening the ‘hard’ image; hosting spotlight sporting and cultural events; spinning liabilities into assets; geographic dissociation from the Middle East region; ridicule the existing stereotype) and 3. Audience (changing the target audience by addressing others; emphasizing similarities and relevance to specific target audience). It appears that dealing with their image problems will continue to be a challenge for officials and marketers of Middle Eastern countries until the region stabilizes and its regional conflicts are resolved.

Keywords: Arab spring, cultural events, image repair, Middle East, tourism marketing

Procedia PDF Downloads 257

Authors: Vladimir A. Basiuk, Laura J. Flores-Sanchez, Victor Meza-Laguna, Jose O. Flores-Flores, Lauro Bucio-Galindo, Elena V. Basiuk

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Noncovalent nanohybrid materials combining carbon nanotubes (CNTs) with phthalocyanines (Pcs) is a subject of increasing research effort, with a particular emphasis on the design of new heterogeneous catalysts, efficient organic photovoltaic cells, lithium batteries, gas sensors, field effect transistors, among other possible applications. The possibility of using unsubstituted Pcs for CNT functionalization is very attractive due to their very moderate cost and easy commercial availability. However, unfortunately, the deposition of unsubstituted Pcs onto nanotube sidewalls through the traditional liquid-phase protocols turns to be very problematic due to extremely poor solubility of Pcs. On the other hand, unsubstituted free-base H₂Pc phthalocyanine ligand, as well as many of its transition metal complexes, exhibit very high thermal stability and considerable volatility under reduced pressure, which opens the possibility for their physical vapor deposition onto solid surfaces, including nanotube sidewalls. In the present work, we show the possibility of simple, fast and efficient noncovalent functionalization of single-walled carbon nanotubes (SWNTs) with a series of 3d metal(II) phthalocyanines Me(II)Pc, where Me= Co, Ni, Cu, and Zn. The functionalization can be performed in a temperature range of 400-500 °C under moderate vacuum and requires about 2-3 h only. The functionalized materials obtained were characterized by means of Fourier-transform infrared (FTIR), Raman, UV-visible and energy-dispersive X-ray spectroscopy (EDS), scanning and transmission electron microscopy (SEM and TEM, respectively) and thermogravimetric analysis (TGA). TGA suggested that Me(II)Pc weight content is 30%, 17% and 35% for NiPc, CuPc, and ZnPc, respectively (CoPc exhibited anomalous thermal decomposition behavior). The above values are consistent with those estimated from EDS spectra, namely, of 24-39%, 27-36% and 27-44% for CoPc, CuPc, and ZnPc, respectively. A strong increase in intensity of D band in the Raman spectra of SWNT‒Me(II)Pc hybrids, as compared to that of pristine nanotubes, implies very strong interactions between Pc molecules and SWNT sidewalls. Very high absolute values of binding energies of 32.46-37.12 kcal/mol and the highest occupied and lowest unoccupied molecular orbital (HOMO and LUMO, respectively) distribution patterns, calculated with density functional theory by using Perdew-Burke-Ernzerhof general gradient approximation correlation functional in combination with the Grimme’s empirical dispersion correction (PBE-D) and the double numerical basis set (DNP), also suggested that the interactions between Me(II) phthalocyanines and nanotube sidewalls are very strong. The authors thank the National Autonomous University of Mexico (grant DGAPA-IN200516) and the National Council of Science and Technology of Mexico (CONACYT, grant 250655) for financial support. The authors are also grateful to Dr. Natalia Alzate-Carvajal (CCADET of UNAM), Eréndira Martínez (IF of UNAM) and Iván Puente-Lee (Faculty of Chemistry of UNAM) for technical assistance with FTIR, TGA measurements, and TEM imaging, respectively.

Keywords: carbon nanotubes, functionalization, gas-phase, metal(II) phthalocyanines

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Authors: Agnieszka E. Laudy, Karolina Stępien, Sergiusz Lulinski, Krzysztof Durka, Stefan Tyski

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1,3-dihydro-1-hydroxy-2,1-benzoxaborole and its derivatives are a particularly interesting group of synthetic agents and were successfully employed in supramolecular chemistry medicine. The first important compounds, 5-fluoro-1,3-dihydro-1-hydroxy-2,1-benzoxaborole and 5-chloro-1,3-dihydro-1-hydroxy-2,1-benzoxaborole were identified as potent antifungal agents. In contrast, (S)-3-(aminomethyl)-7-(3-hydroxypropoxy)-1-hydroxy-1,3-dihydro-2,1-benzoxaborole hydrochloride is in the second phase of clinical trials as a drug for the treatment of Gram-negative bacterial infections of the Enterobacteriaceae family and Pseudomonas aeruginosa. Equally important and difficult task is to search for compounds active against Gram-negative bacilli, which have multi-drug-resistance efflux pumps actively removing many of the antibiotics from bacterial cells. We have examined whether halogen-substituted benzoxaborole-based derivatives and their analogues possess antibacterial activity and are substrates for multi-drug-resistance efflux pumps. The antibacterial activity of 1,3-dihydro-3-hydroxy-1,1-dimethyl-1,2,3-benzosiloxaborole and 10 halogen-substituted its derivatives, as well as 1,2-phenylenediboronic acid and 3 synthesised fluoro-substituted its analogs, were evaluated. The activity against the reference strains of Gram-positive (n=5) and Gram-negative bacteria (n=10) was screened by the disc-diffusion test (0.4 mg of tested compounds was applied onto paper disc). The minimal inhibitory concentration values and the minimal bactericidal concentration values were estimated according to The Clinical and Laboratory Standards Institute and The European Committee on Antimicrobial Susceptibility Testing recommendations. During the minimal inhibitory concentration values determination with or without phenylalanine-arginine beta-naphthylamide (50 mg/L) efflux pump inhibitor, the concentrations of tested compounds ranged 0.39-400 mg/L in the broth medium supplemented with 1 mM magnesium sulfate. Generally, the studied benzosiloxaboroles and benzoxadiboroles showed a higher activity against Gram-positive cocci than against Gram-negative rods. Moreover, benzosiloxaboroles have the higher activity than benzoxadiboroles compounds. In this study, we demonstrated that substitution (mono-, di- or tetra-) of 1,3-dihydro-3-hydroxy-1,1-dimethyl-1,2,3-benzosiloxaborole with halogen groups resulted in an increase in antimicrobial activity as compared to the parent substance. Interestingly, the 6,7-dichloro-substituted parent substance was found to be the most potent against Gram-positive cocci: Staphylococcus sp. (minimal inhibitory concentration 6.25 mg/L) and Enterococcus sp. (minimal inhibitory concentration 25 mg/L). On the other hand, mono- and dichloro-substituted compounds were the most actively removed by efflux pumps present in Gram-negative bacteria mainly from Enterobacteriaceae family. In the presence of efflux pump inhibitor the minimal inhibitory concentration values of chloro-substituted benzosiloxaboroles decreased from 400 mg/L to 3.12 mg/L. Of note, the highest increase in bacterial susceptibility to tested compounds in the presence of phenylalanine-arginine beta-naphthylamide was observed for 6-chloro-, 6,7-dichloro- and 6,7-difluoro-substituted benzosiloxaboroles. In the case of Escherichia coli, Enterobacter cloacae and P. aeruginosa strains at least a 32-fold decrease in the minimal inhibitory concentration values of these agents were observed. These data demonstrate structure-activity relationships of the tested derivatives and highlight the need for further search for benzoxaboroles and related compounds with significant antimicrobial properties. Moreover, the influence of phenylalanine-arginine beta-naphthylamide on the susceptibility of Gram-negative rods to studied benzosiloxaboroles indicate that some tested agents are substrates for efflux pumps in Gram-negative rods.

Keywords: antibacterial activity, benzosiloxaboroles, efflux pumps, phenylalanine-arginine beta-naphthylamide

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Authors: Ponchang Apollos Wuyep, Alice Njolke Mafe, Longchi Satkat Zacheaus, Dogun Ojochogu, Dabot Ayuba Yakubu

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Fungi causes huge losses when infections occur both in plants and animals. Synthetic Antifungal drugs are mostly very expensive and highly cytotoxic when taken. This study was aimed at determining the in vitro and in vivo antifungal activities of the leaves and stem extracts of Terminalia mantaly (Umbrella tree)H. Perrier on Aspergillus species in a bid to identify potential sources of cheap starting materials for the synthesis of new drugs to address the growing antimicrobial resistance. T. mantaly leave and stem powdered plant was extracted by fractionation using the method of solvent partition co-efficient in their graded form in the order n-hexane, Ethyl acetate, methanol and distilled water and phytochemical screening of each fraction revealed the presence of alkaloids, saponins, Tannins, flavonoids, carbohydrates, steroids, anthraquinones, cardiac glycosides and terpenoids in varying degrees. The Agar well diffusion technique was used to screen for antifungal activity of the fractions on clinical isolates of Aspergillus species (Aspergillus flavus and Aspergillus fumigatus). Minimum inhibitory concentration (MIC50) of the most active extracts was determined by the broth dilution method. The fractions test indicated a high antifungal activity with zones of inhibition ranging from 6 to 26 mm and 8 to 30mm (leave fractions) and 10mm to 34mm and 14mm to36mm (stem fractions) on A. flavus and A. fumigatus respectively. All the fractions indicated antifungal activity in a dose response relationship at concentrations of 62.5mg/ml, 125mg/ml, 250mg/ml and 500mg/ml. Better antifungal efficacy was shown by the Ethyl acetate, Hexane and Methanol fractions in the in vitro as the most potent fraction with MIC ranging from 62.5 to 125mg/ml. There was no statistically significant difference (P>0.05) in the potency of the Eight fractions from leave and stem (Hexane, Ethyl acetate, methanol and distilled water, antifungal (fluconazole), which served as positive control and 10% DMSO(Dimethyl Sulfoxide)which served as negative control. In the in vivo investigations, the ingestion technique was used for the infectious studies Female Drosophilla melanogaster(UAS-Diptericin)normal flies(positive control),infected and not treated flies (negative control) and infected flies with A. fumigatus and placed on normal diet, diet containing fractions(MSM and HSM each at concentrations of 10mg/ml 20mg/ml, 30mg/ml, 40mg/ml, 50mg/ml, 60mg/ml, 70mg/ml, 80mg/ml, 90mg/ml and 100mg/ml), diet containing control drugs(fluconazole as positive control)and infected flies on normal diet(negative control), the flies were observed for fifteen(15) days. Then the total mortality of flies was recorded each day. The results of the study reveals that the flies were susceptible to infection with A. fumigatus and responded to treatment with more effectiveness at 50mg/ml, 60mg/ml and 70mg/ml for both the Methanol and Hexane stem fractions. Therefore, the Methanol and Hexane stem fractions of T. mantaly contain therapeutically useful compounds, justifying the traditional use of this plant for the treatment of fungal infections.

Keywords: Terminalia mantaly, Aspergillus fumigatus, cytotoxic, Drosophila melanogaster, antifungal

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Authors: Jerome Dalphinis, Vishal Patel

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The Bailiwick of Jersey is an island British crown dependency situated off the coast of France. Jersey General Hospital’s emergency department sees approximately 40,000 patients a year. It’s outside the NHS, with secondary care being free at the point of care. Sedation is a continuum which extends from a normal conscious level to being fully unresponsive. Procedural sedation produces a minimally depressed level of consciousness in which the patient retains the ability to maintain an airway, and they respond appropriately to physical stimulation. The goals of it are to improve patient comfort and tolerance of the procedure and alleviate associated anxiety. Indications can be stratified by acuity, emergency (cardioversion for life-threatening dysrhythmia), and urgency (joint reduction). In the emergency department, this is most often achieved using a combination of opioids and benzodiazepines. Some departments also use ketamine to produce dissociative sedation, a cataleptic state of profound analgesia and amnesia. The response to pharmacological agents is highly individual, and the drugs used occasionally have unpredictable pharmacokinetics and pharmacodynamics, which can always result in progression between levels of sedation irrespective of the intention. Therefore, practitioners must be able to ‘rescue’ patients from deeper sedation. These practitioners need to be senior clinicians with advanced airway skills (AAS) training. It can lead to adverse effects such as dangerous hypoxia and unintended loss of consciousness if incorrectly undertaken; studies by the National Confidential Enquiry into Patient Outcome and Death (NCEPOD) have reported avoidable deaths. The Royal College of Emergency Medicine, UK (RCEM) released an updated ‘Safe Sedation of Adults in the Emergency Department’ guidance in 2017 detailing a series of standards for staff competencies, and the required environment and equipment, which are required for each target sedation depth. The emergency department in Jersey undertook audit research in 2018 to assess their current practice. It showed gaps in clinical competency, the need for uniform care, and improved documentation. This spurred the development of a checklist incorporating the above RCEM standards, including contraindication for procedural sedation and difficult airway assessment. This was approved following discussion with the relevant heads of departments and the patient safety directorates. Following this, a second audit research was carried out in 2019 with 17 completed checklists (11 relocation of joints, 6 cardioversions). Data was obtained from looking at the controlled resuscitation drugs book containing documented use of ketamine, alfentanil, and fentanyl. TrakCare, which is the patient electronic record system, was then referenced to obtain further information. The results showed dramatic improvement compared to 2018, and they have been subdivided into six categories; pre-procedure assessment recording of significant medical history and ASA grade (2 fold increase), informed consent (100% documentation), pre-oxygenation (88%), staff (90% were AAS practitioners) and monitoring (92% use of non-invasive blood pressure, pulse oximetry, capnography, and cardiac rhythm monitoring) during procedure, and discharge instructions including the documented return of normal vitals and consciousness (82%). This procedural sedation checklist is a safe intervention that identifies pertinent information about the patient and provides a standardised checklist for the delivery of gold standard of care.

Keywords: advanced airway skills, checklist, procedural sedation, resuscitation

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Kanokwan Chancharoenchai

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Economic growth can be considered as an important element of countries’ development process. For developing countries, like Thailand, to ensure the continuous growth of the economy, the Thai government usually implements various policies to stimulate economic growth. They may take the form of fiscal, monetary, trade, and other policies. Because of these different aspects, understanding factors relating to economic growth could allow the government to introduce the proper plan for the future economic stimulating scheme. Consequently, this issue has caught interest of not only policymakers but also academics. This study, therefore, investigates explanatory variables for economic growth in Thailand from 2005 to 2017 with a total of 52 quarters. The findings would contribute to the field of economic growth and become helpful information to policymakers. The investigation is estimated throughout the production function with non-linear Cobb-Douglas equation. The rate of growth is indicated by the change of GDP in the natural logarithmic form. The relevant factors included in the estimation cover three traditional means of production and implicit effects, such as human capital, international activity and technological transfer from developed countries. Besides, this investigation takes the internal and external instabilities into account as proxied by the unobserved inflation estimation and the real effective exchange rate (REER) of the Thai baht, respectively. The unobserved inflation series are obtained from the AR(1)-ARCH(1) model, while the unobserved REER of Thai baht is gathered from naive OLS-GARCH(1,1) model. According to empirical results, the AR(|2|) equation which includes seven significant variables, namely capital stock, labor, the imports of capital goods, trade openness, the REER of Thai baht uncertainty, one previous GDP, and the world financial crisis in 2009 dummy, presents the most suitable model. The autoregressive model is assumed constant estimator that would somehow cause the unbias. However, this is not the case of the recursive coefficient model from the state space model that allows the transition of coefficients. With the powerful state space model, it provides the productivity or effect of each significant factor more in detail. The state coefficients are estimated based on the AR(|2|) with the exception of the one previous GDP and the 2009 world financial crisis dummy. The findings shed the light that those factors seem to be stable through time since the occurrence of the world financial crisis together with the political situation in Thailand. These two events could lower the confidence in the Thai economy. Moreover, state coefficients highlight the sluggish rate of machinery replacement and quite low technology of capital goods imported from abroad. The Thai government should apply proactive policies via taxation and specific credit policy to improve technological advancement, for instance. Another interesting evidence is the issue of trade openness which shows the negative transition effect along the sample period. This could be explained by the loss of price competitiveness to imported goods, especially under the widespread implementation of free trade agreement. The Thai government should carefully handle with regulations and the investment incentive policy by focusing on strengthening small and medium enterprises.

Keywords: autoregressive model, economic growth, state space model, Thailand

Procedia PDF Downloads 124