Search results for: recognition primed decision

Authors: Lakmali Anthony, Madeline Gillies

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Background Breast cancer (BC) is usually managed with surgical resection. Many outcomes traditionally used to define successful operative management, such as resection margin, do not adequately reflect patients’ experience. Patient-reported outcomes (PRO) such as Health-Related Quality of life (HRQoL) provide a means by which the impact of surgery for cancer can be reported in a patient-centered way. This exploratory cross-sectional study aims to; (1) describe postoperative HRQoL in patients who underwent primary resection in a regional Australian hospital; (2) describe the prevalence of anxiety, depression and clinically significant fear of cancer recurrence (FCR) in this population; and (3) identify demographic, psychosocial, disease and treatment factors associated with poorer self-reported HRQoL. Methods Patients who had resection of BC in a regional Australian hospital between 2015 and 2022 were eligible. Participants were asked to complete a survey designed to assess HRQoL, as well as validated instruments that assess several other psychosocial PROs hypothesized to be associated with HRQoL; emotional distress, fear of cancer recurrence, social support, dispositional optimism, body image and spirituality. Results Forty-six patients completed the survey. Clinically significant levels of FCR and emotional distress were present in this group. Many domains of HRQoL were significantly worse than an Australian reference population for BC. Demographic and disease factors associated with poor HRQoL included smoking and ongoing adjuvant systemic therapy. The primary operation was not associated with HRQoL for breast cancer. All psychosocial factors measured were associated with HRQoL. Conclusion HRQoL is an important outcome in surgery for both research and clinical practice. This study provides an overview of the quality of life in a regional Australian population of postoperative breast cancer patients and the factors that affect it. Understanding HRQoL and awareness of patients particularly vulnerable to poor outcomes should be used to aid the informed consent and shared decision-making process between surgeon and patient.

Keywords: breast cancer, surgery, quality of life, regional population

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Shafiqul Islam, Cordia Chu

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Bangladesh is one of the most vulnerable countries to climate related disasters such as flood and cyclone. Exploring from the semi-structured in-depth interviews of 38 stakeholders and literature review, this study examined the public spending distribution process in DRR. This paper demonstrates how the processes of political economy-enclosure, exclusion, encroachment, and entrenchment hinder the Disaster Risk Reduction (DRR) efforts of Department of Disaster Management (DDM) such as distribution of flood centres, cyclone centres and 40 days employment generation programs. Enclosure refers to when DRR projects allocated to less vulnerable areas or expand the roles of influencing actors into the public sphere. Exclusion refers to when DRR projects limit affected people’s access to resources or marginalize particular stakeholders in decision-making activities. Encroachment refers to when allocation of DRR projects and selection of location and issues degrade the environmental affect or contribute to other forms of disaster risk. Entrenchment refers to when DRR projects aggravate the disempowerment of common people worsen the concentrations of wealth and income inequality within a community. In line with United Nations (UN) Sustainable Development Goals (SDGs), Hyogo and Sendai Frameworks, in the case of Bangladesh, DRR policies implemented under the country’s national five-year plan, disaster-related acts and rules. These policies and practices have somehow enabled influential-elites to mobilize and distribute resources through bureaucracies. Exclusionary forms of fund distribution of DRR exist at both the national and local scales. DRR related allocations have encroached through the low land areas development project without consulting local needs. Most severely, DRR related unequal allocations have entrenched social class trapping the backward communities vulnerable to climate related disasters. Planners and practitioners of DRR need to take necessary steps to eliminate the potential risks from the processes of enclosure, exclusion, encroachment, and entrenchment happens in project fund allocations.

Keywords: Bangladesh, disaster risk reduction, fund distribution, political economy

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Authors: Euripides Antoniades

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In 1821 the Greek Revolution movement, under the political influence that arose from the French revolution, and the corresponding movements in Italy, Germany and America, requested the liberation of the nation and the establishment of an independent national state. Published topics in the British press regarding the Greek Revolution, focused on : a) the right of the Greeks to claim their freedom from Turkish domination in order to establish an independent state based on the principle of national autonomy, b) criticism regarding Turkish rule as illegal and the power of the Ottoman Sultan as arbitrary, c) the recognition of the Greek identity and its distinction from the Turkish one and d) the endorsement Greeks as the descendants of ancient Greeks. The advantage of newspaper as a media is sharing information and ideas and dealing with issues in greater depth and detail, unlike other media, such as radio or television. The London Times is a print publication that presents, in chronological or thematic order, the news, opinions or announcements about the most important events that have occurred in a place during a specified period of time. This paper employs the rich archive of The London Times archive by quoting extracts from publications of that period, to convey the British public perspective regarding the Greek Revolution from its beginning until the London Protocol of 1828. Furthermore, analyses the publications of the British newspaper in terms of the number of references to the Greek revolution, front page and editorial references as well as the size of publications on the revolution during the period 1821-1828. A combination of qualitative and quantitative content analysis was applied. An attempt was made to record Greek Revolution references along with the usage of specific words and expressions that contribute to the representation of the historical events and their exposure to the reading public. Key finds of this research reveal that a) there was a frequency of passionate daily articles concerning the events in Greece, their length, and context in The London Times, b) the British public opinion was influenced by this particular newspaper and c) the newspaper published various news about the revolution by adopting the role of animator of the Greek struggle. For instance, war events and the battles of Wallachin and Moldavia, Hydra, Crete, Psara, Mesollogi, Peloponnese were presented not only for informing the readers but for promoting the essential need for freedom and the establishment of an independent Greek state. In fact, this type of news was the main substance of the The London Times’ structure, establishing a positive image about the Greek Revolution contributing to the European diplomatic development such as the standpoint of France, - that did not wish to be detached from the conclusions regarding the English loans and the death of Alexander I of Russia and his succession by the ambitious Nicholas. These factors offered a change in the attitude of the British and Russians respectively assuming a positive approach towards Greece. The Great Powers maintained a neutral position in the Greek-Ottoman conflict, same time they engaged in Greek power increasement by offering aid.

Keywords: Greece, revolution, newspaper, the London times, London, great britain, mass media

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Authors: Yali Liu

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The ethnographic research involved a multi-sited field trip study in China to compile in-depth data from Chinese multilingual academics of Korean, Japanese, and Russian. It aimed to create a culturally-informed portrait of their values and perceptions regarding their choice of language for academic publishing. Extended and lengthy fieldwork, or known as ‘deep hanging out’, enabled the author to gain a comprehensive understanding of the research context at the macro-level and the participants’ experiences at the micro-level. This research involved multiple fieldwork sites, which the author selected in acknowledgment of the diversity in China’s regions with respect to their geopolitical context, socio-economic development, cultural traditions, and administrative status. The 14 weeks of data collection took the author over-land to five regions in northern China: Hebei province, Tianjin, Jilin province, Gansu province, and Xinjiang. Responding to the fieldwork dynamics, the author positioned herself at different degrees of insiderness and outsiderness. This occurred at three levels: the regional level, the individual level, and the within-individual level. To enhance the ability to reflect on the authors’ researcher subjectivity, the author explored her understanding of the five ‘I’s, derived from the authors’ natural attributes. This helped the author to monitor her subjectivity, particularly during critical decision-making. The methodological challenges the author navigated were related to interviewing elites; this involved the initial approach, establishing a relationship, and negotiating the unequal power relationship during our contact. The author developed a number of strategies to strengthen her authority, and to gain the confidence of her envisaged participants and secure their collaboration, and the author negotiated a form of reciprocity that reflected their needs and expectations. The current ethnographic research has both theoretical and practical significance. It contributes to the methodological development regarding multi-sited ethnographic research. The messiness and strategies about positioning and interviewing elites will provide practical lessons for researchers who conduct ethnographic research, especially from power-‘less’ positions.

Keywords: multi-sited ethnographic research, elite interview, multilingual China, subjectivity, reciprocity

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Authors: Angelis P. Barlampas

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The purpose of this study is to inform the reader, about the various applications of artificial intelligence (AI), in cardiac imaging. AI grows fast and its role is crucial in medical specialties, which use large amounts of digital data, that are very difficult or even impossible to be managed by human beings and especially doctors.Artificial intelligence (AI) refers to the ability of computers to mimic human cognitive function, performing tasks such as learning, problem-solving, and autonomous decision making based on digital data. Whereas AI describes the concept of using computers to mimic human cognitive tasks, machine learning (ML) describes the category of algorithms that enable most current applications described as AI. Some of the current applications of AI in cardiac imaging are the follows: Ultrasound: Automated segmentation of cardiac chambers across five common views and consequently quantify chamber volumes/mass, ascertain ejection fraction and determine longitudinal strain through speckle tracking. Determine the severity of mitral regurgitation (accuracy > 99% for every degree of severity). Identify myocardial infarction. Distinguish between Athlete’s heart and hypertrophic cardiomyopathy, as well as restrictive cardiomyopathy and constrictive pericarditis. Predict all-cause mortality. CT Reduce radiation doses. Calculate the calcium score. Diagnose coronary artery disease (CAD). Predict all-cause 5-year mortality. Predict major cardiovascular events in patients with suspected CAD. MRI Segment of cardiac structures and infarct tissue. Calculate cardiac mass and function parameters. Distinguish between patients with myocardial infarction and control subjects. It could potentially reduce costs since it would preclude the need for gadolinium-enhanced CMR. Predict 4-year survival in patients with pulmonary hypertension. Nuclear Imaging Classify normal and abnormal myocardium in CAD. Detect locations with abnormal myocardium. Predict cardiac death. ML was comparable to or better than two experienced readers in predicting the need for revascularization. AI emerge as a helpful tool in cardiac imaging and for the doctors who can not manage the overall increasing demand, in examinations such as ultrasound, computed tomography, MRI, or nuclear imaging studies.

Keywords: artificial intelligence, cardiac imaging, ultrasound, MRI, CT, nuclear medicine

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Authors: Meidesta Pitria, Akiko Okabe

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In high-density informal settlement, extension area at the outside of the houses could primarily happen as a spatial modification response. House extension in high-density informal settlement is not only becoming a physical spatial modification that makes a blur zone between private and public but also supporting the growth and existence of informal economy and other daily activities in both individuals and communities. This research took a case study in an informal settlement named Kampung Cikini, a densely populated area in Central Jakarta. The aim of this study is to identify and clarify house extension as a strategy in dealing with urbanization in an informal settlement. By using the perspective and information from housewives, the analysis is based on the assumption that land ownership transformation and the activities in house extension area influence the different kinds of house extension’s spatial modification and local planning policy in relation with the implementation of house extension strategy. The data collection was done in four sites, two sites are located in outer-wide alley and another two sites are located in inner-narrow alley. In this research, data of 104 housewives in 86 houses were collected through representatives of housewives and local leader of each sites. The research was started from participatory mapping process, deep interview with local leader, and initiated collaboration with housewives community in having a celebration as communal event to cultivate together the issue. This study shows that land ownership, activities, and alley are indispensable in the decision of extension space making. The more permanency status of land ownership the more permanent and various extension could be implemented. However, in some blocks, the existence of origin house or first land owner also has a significant role in coordination and agreement in using and modifying extension space. In outer-wide alley, the existence of more various activities in front area of the houses is significantly related with the chance given by having wider alley, particularly for informal income generating activities. In the inner-narrow alley, limited space in front of the houses affects more negotiations in the community for having more shared spaces, even inside their private space.

Keywords: house extension, housewives, informal settlement, kampung, high density

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Authors: Marina Karaseva

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The beginning of our century became a new digital epoch in the educational situation. Last decade the newest stage of this process had been initialized by the touch-screen mobile devices with program applications for them. The touch possibilities for learning fundamentals of music are of especially importance for music majors. The phenomenon of touching, firstly, makes it realistic to play on the screen as on music instrument, secondly, helps students to learn music theory while listening in its sound elements by music ear. Nowadays we can detect several levels of such mobile applications: from the basic ones devoting to the elementary music training such as intervals and chords recognition, to the more advanced applications which deal with music perception of non-major and minor modes, ethnic timbres, and complicated rhythms. The main purpose of the proposed paper is to disclose the main tendencies in this process and to demonstrate the most innovative features of music theory applications on the base of iOS and Android systems as the most common used. Methodological recommendations how to use these digital material musicologically will be done for the professional music education of different levels. These recommendations are based on more than ten year ‘iTheory’ teaching experience of the author. In this paper, we try to logically classify all types of ‘iTheory’mobile applications into several groups, according to their methodological goals. General concepts given below will be demonstrated in concrete examples. The most numerous group of programs is formed with simulators for studying notes with audio-visual links. There are link-pair types as follows: sound — musical notation which may be used as flashcards for studying words and letters, sound — key, sound — string (basically, guitar’s). The second large group of programs is programs-tests containing a game component. As a rule, their basis is made with exercises on ear identification and reconstruction by voice: sounds and intervals on their sounding — harmonical and melodical, music modes, rhythmic patterns, chords, selected instrumental timbres. Some programs are aimed at an establishment of acoustical communications between concepts of the musical theory and their musical embodiments. There are also programs focused on progress of operative musical memory (with repeating of sounding phrases and their transposing in a new pitch), as well as on perfect pitch training In addition a number of programs improvisation skills have been developed. An absolute pitch-system of solmisation is a common base for mobile programs. However, it is possible to find also the programs focused on the relative pitch system of solfegе. In App Store and Google Play Market online store there are also many free programs-simulators of musical instruments — piano, guitars, celesta, violin, organ. These programs may be effective for individual and group exercises in ear training or composition classes. Great variety and good sound quality of these programs give now a unique opportunity to musicians to master their music abilities in a shorter time. That is why such teaching material may be a way to effective study of music theory.

Keywords: ear training, innovation in music education, music theory, mobile devices

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Authors: Nada Mohamed, Abdel Aziz Mohamed

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Climate change in coastal areas is a global issue that can be felt on local scale and will be around for decades and centuries to come to an end; it also has critical risks on the city’s economy, communities, and the natural environment. One of these changes that cause a huge risk on coastal cities is the sea level rise (SLR). SLR is a result of scarcity and reduction in global environmental system. The main cause of climate change and global warming is the countries with high development index (HDI) as Japan and Germany while the medium and low HDI countries as Egypt does not have enough awareness and advanced tactics to adapt with this changes that destroy urban areas and cause loss in land and economy. This is why Climate Resilience is one of the UN sustainable development goals 2030, which is calling for actions to strengthen climate change resilience through mitigation and adaptation. For many reasons, adaptation has received less attention than mitigation and it is only recently that adaptation has become a focal global point of attention. This adaption can be achieved through some actions such as upgrading the use and the design of the land, adjusting business and activities of people, and increasing community understanding of climate risks. To reach the adaption goals, and we have to apply a strategic pathway to Climate Resilience, which is the Urban Bioregionalism Paradigm. Resiliency has been framed as persistence, adaptation, and transformation. Climate Resilience decision support system includes a visualization platform where ecological, social, and economic information can be viewed alongside with specific geographies that's why Urban Bioregionalism is a socio-ecological system which is defined as a paradigm that has potential to help move social attitudes toward environmental understanding and deepen human-environment connections within ecological development. The research aim is to achieve an adaptive integrated urban development model throughout the analyses of tactics and strategies that can be used to adapt urban areas and coastal communities to the challenges of climate changes especially SLR and also simulation model using advanced technological software for a coastal city corridor to elaborates the suitable strategy to apply.

Keywords: climate resilience, sea level rise, SLR, coastal resilience, adaptive development simulation

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Authors: Manoj Kumar Reddy Pulim, Lakshmi Muthukrishnan, Geetha Jayapathy, Radhika Raman

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Introduction: In the past two decades, noninvasive positive pressure ventilation (NIPPV) emerged as one of the most important advances in the management of both acute and chronic respiratory failure in children. In the acute setting, it is an alternative to intubation with a goal to preserve normal physiologic functions, decrease airway injury, and prevent respiratory tract infections. There is a need to determine the clinical profile and parameters which point towards the need for NIV in the pediatric emergency setting. Objectives: i) To study the clinical profile of children who required non invasive ventilation and invasive ventilation, ii) To study the clinical parameters common to children who required non invasive ventilation. Methods: All children between one month to 18 years, who were intubated in the pediatric emergency department and those for whom decision to commence Non Invasive Ventilation was made in Emergency Room were included in the study. Children were transferred to the Paediatric Intensive Care Unit and started on Non Invasive Ventilation as per our hospital policy and followed up in the Paediatric Intensive Care Unit. Clinical profile of all children which included age, gender, diagnosis and indication for intubation were documented. Clinical parameters such as respiratory rate, heart rate, saturation, grunting were documented. Parameters obtained were subject to statistical analysis. Observations: Airway disease (Bronchiolitis 25%, Viral induced wheeze 22%) was a common diagnosis in 32 children who required Non Invasive Ventilation. Neuromuscular disorder was the common diagnosis in 27 children (78%) who were Intubated. 17 children commenced on Non Invasive Ventilation who later needed invasive ventilation had Neuromuscular disease. High frequency nasal cannula was used in 32, and mask ventilation in 17 children. Clinical parameters common to the Non Invasive Ventilation group were age < 1 year (17), tachycardia n = 7 (22%), tachypnea n = 23 (72%) and severe respiratory distress n = 9 (28%), grunt n = 7 (22%), SPO2 (80% to 90%) n = 16. Children in the Non Invasive Ventilation + INTUBATION group were > 3 years (9), had tachycardia 7 (41%), tachypnea 9(53%) with a male predominance n = 9. In statistical comparison among 3 groups,'p' value was significant for pH, saturation, and use of Ionotrope. Conclusion: Invasive ventilation can be avoided in the paediatric Emergency Department in children with airway disease, by commencing Non Invasive Ventilation early. Intubation in the pediatric emergency department has a higher association with neuromuscular disorders.

Keywords: clinical parameters, indications, non invasive ventilation, paediatric emergency room

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Authors: Yan-Shen Yang, Bai-Chen Xie

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Background and significance of the study: Both green power trading schemes and interregional power transmission are effective ways to increase green power absorption and achieve renewable power development goals. China accelerates the construction of interregional power transmission lines and the green power market. A critical issue focusing on the close interaction between these two approaches arises, which can heavily affect the green power quota allocation and renewable power development. Existing studies have not discussed this issue adequately, so it is urgent to figure out their relationship to achieve a suitable power market design and a more reasonable power grid construction.Basic methodologies: We develop an equilibrium model of the power market in China to analyze the coupling effect of these two approaches as well as their influence on power generation and interregional transmission in China. Our model considers both the Tradable green certificate (TGC) and green power market, which consists of producers, consumers in the market, and an independent system operator (ISO) minimizing the total system cost. Our equilibrium model includes the decision optimization process of each participant. To reformulate the models presented as a single-level one, we replace the producer, consumer, ISO, and market equilibrium problems with their Karush-Kuhn-Tucker (KKT) conditions, which is further reformulated as a mixed-integer linear programming (MILP) and solved in Gurobi solver. Major findings: The result shows that: (1) the green power market can significantly promote renewable power absorption while the TGC market provides a more flexible way for green power trading. (2) The phenomena of inefficient occupation and no available transmission lines appear simultaneously. The existing interregional transmission lines cannot fully meet the demand for wind and solar PV power trading in some areas while the situation is vice versa in other areas. (3) Synchronous implementation of green power and TGC trading mechanism can benefit the development of green power as well as interregional power transmission. (4) The green power transaction exacerbates the unfair distribution of carbon emissions. The Carbon Gini Coefficient is up to 0.323 under the green power market which shows a high Carbon inequality. The eastern coastal region will benefit the most due to its huge demand for external power.

Keywords: green power market, tradable green certificate, interregional power transmission, power market equilibrium model

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Authors: Denise Levy, Anna Lucia C. H. Villavicencio

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Food irradiation is a processing and preservation technique to eliminate insects and parasites and reduce disease-causing microorganisms. Moreover, the process helps to inhibit sprouting and delay ripening, extending fresh fruits and vegetables shelf-life. Nevertheless, most Brazilian consumers seem to misunderstand the difference between irradiated food and radioactive food and the general public has major concerns about the negative health effects and environmental contamination. Society´s judgment and decision making are directly linked to perceived benefits and risks. The web-based project entitled ‘Scientific information about food irradiation: Internet as a tool to approach science and society’ was created by the Nuclear and Energetic Research Institute (IPEN), in order to offer an interdisciplinary approach to science education, integrating economic, ethical, social and political aspects of food irradiation. This project takes into account that, misinformation and unfounded preconceived ideas impact heavily on the acceptance of irradiated food and purchase intention by the Brazilian consumer. Taking advantage of the potential value of the Internet to enhance communication and education among general public, a research study was carried out regarding the possibilities and trends of Information and Communication Technologies among the Brazilian population. The content includes concepts, definitions and Frequently Asked Questions (FAQ) about processes, safety, advantages, limitations and the possibilities of food irradiation, including health issues, as well as its impacts on the environment. The project counts on eight self-instructional interactive web courses, situating scientific content in relevant social contexts in order to encourage self-learning and further reflections. Communication is a must to improve public understanding of science. The use of information technology for quality scientific divulgation shall contribute greatly to provide information throughout the country, spreading information to as many people as possible, minimizing geographic distances and stimulating communication and development.

Keywords: food irradiation, multimedia learning tools, nuclear science, society and education

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Chieh-Ning Lan, Tzu-Shin Lin, Kun-Hao Lin

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Chinese handwriting skill is one of the basic skills of school-age children in Taiwan, which helps them to learn most academic subjects. Differ from the alphabetic language system, Chinese written language is a logographic script with a complicated 2-dimensional character structure as a morpheme. Visuospatial ability places a great role in Chinese handwriting to maintain good proportion and alignment of these interwoven strokes. In Taiwan, school-age students faced the challenge to recognize and write down Chinese characters, especially in children with written expression difficulties (CWWDs). In this study, we developed an instructional app to help CWWDs practice Chinese handwriting skills, and we aimed to apply the mobile assisted language learning (MALL) system in clinical writing strategies. To understand the feasibility and satisfaction of this auxiliary instructional writing app, we investigated the perceive and value both from school-age students and the clinic therapists, who were the target users and the experts. A group of 8 elementary school children, as well as 8 clinic therapists, were recruited. The school-age students were asked to go through a paper-based instruction and were asked to score the visual expression based on their graphic preference; the clinic therapists were asked to watch an introductive video of this instructional app and complete the online formative questionnaire. In the results of our study, from the perspective of user interface design, school-age students were more attracted to cartoon-liked pictures rather than line drawings or vivid photos. Moreover, compared to text, pictures which have higher semantic transparency were more commonly chosen by children. In terms of the quantitative survey from clinic therapists, they were highly satisfied with this auxiliary instructional writing app, including the concepts such as visual design, teaching contents, and positive reinforcement system. Furthermore, the qualitative results also suggested comprehensive positive feedbacks on the teaching contents and the feasibility of integrating the app into clinical treatments. Interestingly, we found that clinic therapists showed high agreement in approving CWWDs’ writing ability with using orthographic knowledge; however, in the qualitative section, clinic therapists pointed out that CWWDs usually have relative insufficient background knowledge in Chinese character orthographic rules, which because it is not a key-point in conventional handwriting instruction. Also, previous studies indicated that conventional Chinese reading and writing instructions were lacked of utilizing visual-spatial arrangement strategies. Based on the sharing experiences from all participants, we concluded several interesting topics that are worth to dedicate to in the future. In this undergoing app system, improvement and revision will be applied into the system design, and will establish a better and more useful instructional system for CWWDs within their treatments; enlightened by the opinions related to learning content, the importance of orthographic knowledge in Chinese character recognition should be well discussed and involved in CWWDs’ intervention in the future.

Keywords: auxiliary instructional app, children with writing difficulties, Chinese handwriting, orthographic knowledge

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Simone Balin, Cecilia M. Bolognesi, Paolo Borin

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In the construction industry, there is a large amount of data and interconnected information. To manage this information effectively, a transition to the immersive digitization of information processes is required. This transition is important to improve knowledge circulation, product quality, production sustainability and user satisfaction. However, there is currently a lack of a common definition of immersion in the construction industry, leading to misunderstandings and limiting the use of advanced immersive technologies. Furthermore, the lack of guidelines and a common vocabulary causes interested actors to abandon the virtual world after the first collaborative steps. This research aims to define the optimal use of immersive technologies in the AEC sector, particularly for collaborative processes based on the BIM methodology. Additionally, the research focuses on creating classes and levels to structure and define guidelines and a vocabulary for the use of the " Immersive Need Level." This concept, matured by recent technological advancements, aims to enable a broader application of state-of-the-art immersive technologies, avoiding misunderstandings, redundancies, or paradoxes. While the concept of "Informational Need Level" has been well clarified with the recent UNI EN 17412-1:2021 standard, when it comes to immersion, current regulations and literature only provide some hints about the technology and related equipment, leaving the procedural approach and the user's free interpretation completely unexplored. Therefore, once the necessary knowledge and information are acquired (Informational Need Level), it is possible to transition to an Immersive Need Level that involves the practical application of the acquired knowledge, exploring scenarios and solutions in a more thorough and detailed manner, with user involvement, via different immersion scales, in the design, construction or management process of a building or infrastructure. The need for information constitutes the basis for acquiring relevant knowledge and information, while the immersive need can manifest itself later, once a solid information base has been solidified, using the senses and developing immersive awareness. This new approach could solve the problem of inertia among AEC industry players in adopting and experimenting with new immersive technologies, expanding collaborative iterations and the range of available options.

Keywords: AECindustry, immersive technology (IMT), virtual reality, augmented reality, building information modeling (BIM), decision making, collaborative process, information need level, immersive level of need

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Authors: Ricardo Godoy, Herbert Venthur, Hector Jimenez, Andres Quiroz, Ana Mutis

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In agriculture, grape production has great economic importance at global level, considering that in 2013 it reached 7.4 million hectares (ha) covered by plantations of this fruit worldwide. Chile is the number one exporter in the world with 800,000 tons. However, these values have been threatened by the attack of the grapevine moth, Lobesia botrana (Denis & Schiffermuller) (Lepidoptera: Tortricidae), since its detection in 2008. Nowadays, the use of semiochemicals, in particular the major component of the sex pheromone, (E,Z)-7.9-dodecadienil acetate, are part of mating disruption methods to control L. botrana. How insect pests can recognize these molecules, is being part of huge efforts to deorphanize their olfactory mechanism at molecular level. Thus, an interesting group of proteins has been identified in the antennae of insects, where odorant-binding proteins (OBPs) are known by transporting molecules to odorant receptors (ORs) and a co-receptor (ORCO) causing a behavioral change in the insect. Other proteins such as chemosensory proteins (CSPs), ionotropic receptors (IRs), odorant degrading enzymes (ODEs) and sensory neuron membrane proteins (SNMPs) seem to be involved, but few studies have been performed so far. The above has led to an increasing interest in insect communication at a molecular level, which has contributed to both a better understanding of the olfaction process and the design of new pest management strategies. To date, it has been reported that the ORs can detect one or a small group of odorants in a specific way. Therefore, the objective of this study is the identification of genes that encode these ORs using the antennal transcriptome of L. botrana. Total RNA was extracted for females and males of L. botrana, and the antennal transcriptome sequenced by Next Generation Sequencing service using an Illumina HiSeq2500 platform with 50 million reads per sample. Unigenes were assembled using Trinity v2.4.0 package and transcript abundance was obtained using edgeR. Genes were identified using BLASTN and BLASTX locally installed in a Unix system and based on our own Tortricidae database. Those Unigenes related to ORs were characterized using ORFfinder and protein Blastp server. Finally, a phylogenetic analysis was performed with the candidate amino acid sequences for LbotORs including amino acid sequences of other moths ORs, such as Bombyx mori, Cydia pomonella, among others. Our findings suggest 61 genes encoding ORs and one gene encoding an ORCO in both sexes, where the greatest difference was found in the OR6 because of the transcript abundance according to the value of FPKM in females and males was 1.48 versus 324.00. In addition, according to phylogenetic analysis OR6 is closely related to OR1 in Cydia pomonella and OR6, OR7 in Epiphyas postvittana, which have been described as pheromonal receptors (PRs). These results represent the first evidence of ORs present in the antennae of L. botrana and a suitable starting point for further functional studies with selected ORs, such as OR6, which is potentially related to pheromonal recognition.

Keywords: antennal transcriptome, lobesia botrana, odorant receptors (ORs), phylogenetic analysis

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Brennan Lodge

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Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

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Authors: Oljana Hoxhaj

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The integration process of Albania into the European family carries many difficulties. In this context, the Albanian legislator is inclined to implement in the domestic legal framework models which have been successful in other countries. Our paper aims to present an analytical and comparative approach to the health system in Albania and France, mainly focusing on citizen’s access to these services. Different standards and cultures between states, in the context of an approximate model, will be the first challenge of our paper. Over the last few years, the Albanian government has undertaken concrete reforms in this sector, aiming to transform the vision on which the previous health system was structured. In this perspective, the state fulfills not only an obligation to its citizens, but also consolidates progressive steps toward alignment with European Union standards. The necessity to undertake a genuine reform in this area has come as an exigency of society, which has permanently identified problems within this sector, considering it ineffective, out of standards, and corrupt. The inclusion of health services on the Albanian government agenda reflects its will in the function of good governance, transparency, and broadening access to the provision of quality health services in the public and private sectors. The success of any initiative in the health system consists of giving priority to patient needs. Another objective that should be in the state's consideration is to create the premise to provide a comprehensive process on whose foundations partnership and broader co-operation with beneficiary entities are established in any decision-making that is directly related to their interests. Some other important and widespread impacts on the effective realization of citizens' access to the healthcare system coincide with the construction of appropriate infrastructure, increasing the professionalism and qualification of medical staff, and the allocation of a higher budget. France has one of the most effective healthcare models in Europe. That is why we have chosen to analyze this country, aiming to highlight the advantages of this system, as well as the commitment of the French state to drafting effective health policies. In the framework of the process of harmonization of the Albanian legislation with that of the European Union, through our work, we aim to identify the space to implement the whole of these legislative innovations in the Albanian legislation.

Keywords: effective service, harmonization level, innovation, reform

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Authors: Davod Ahmadigheidari, Isabel Alvarez, Kate Sinclair, Marnie Davidson, Patrick Cortbaoui, Hugo Melgar-Quiñonez

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The burden of collecting water tends to disproportionately fall on women and girls in low-income countries. Specifically, women spend between one to eight hours per day fetching water for domestic use in Sub-Saharan Africa. While there has been research done on the global time burden for collecting water, it has been mainly focused on water quality parameters; leaving the relationship between water fetching and health outcomes understudied. There is little available evidence regarding the relationship between water fetching and maternal child care practices. The main objective of this study was to help fill the aforementioned gap in the literature. Data from two surveys in Ethiopia and Malawi conducted by CARE Canada in 2016-2017 were used. Descriptive statistics indicate that women were predominantly responsible for collecting water in both Ethiopia (87%) and Malawi (99%) respectively, with the majority spending more than 30 minutes per day on water collection. With regards to child care practices, in both countries, breastfeeding was relatively high (77% and 82%, respectively); and treatment for malnutrition was low (15% and 8%, respectively). However, the same consistency was not found for weighing; in Ethiopia only 16% took their children for weighting in contrast to 94% in Malawi. These three practices were summed to create one variable for regressions analyses. Unadjusted logistic regression findings showed that only in Ethiopia was time fetching water significantly associated with child care practices. Once adjusted for covariates, this relationship was no longer found to be significant. Adjusted logistic regressions also showed that the factors that did influence child care practices differed slightly between the two countries. In Ethiopia, a lack of access to community water supply (OR= 0.668; P=0.010), poor attitudes towards gender equality (OR= 0.608; P=0.001), no access to land and (OR=0.603; P=0.000), significantly decreased a women’s odd of using positive childcare practices. Notably, being young women between 15-24 years (OR=2.308; P=0.017), and 25-29 (OR=2.065; P=0.028) increased probability of using positive childcare practices. Whereas in Malawi, higher maternal age, low decision-making power, significantly decreased a women’s odd of using positive childcare practices. In conclusion, this study found that even though amount of time spent by women fetching water makes a difference for childcare practices, it is not significantly related to women’s child care practices when controlling the covariates. Importantly, women’s age contributes to child care practices in Ethiopia and Malawi.

Keywords: time fetching water, community water supply, women’s child care practices, Ethiopia, Malawi

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Authors: Zuoji Huang, Jinyan Sun, Chunlin Wang, Haiming Qian, Nan Xu

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The spatial extent and area of central river bars can always vary due to the impact of water level, sediment supply and human activities. In 2016, a catastrophic flood disaster caused by sustained and heavy rainfall happened in the middle and lower Yangtze River. The flood led to the most serious economic and social loss since 1954, and strongly affected the central river bar. It is essential to continuously monitor the dynamics change of central bars because it can avoid frequent field measurements in central bars before and after the flood disaster and is helpful for flood warning. This paper focused on the dynamic change of central bars of Phoenix bar and Changsha bar in the Yangtze River in 2016. In this study, GF-1 (GaoFen-1) WFV(wide field view) data was employed owing to its high temporal frequency and high spatial resolution. A simple NDWI (Normalized Difference Water Index) method was utilized for river central bar mapping. Human-checking was then performed to ensure the mapping quality. The relationship between the area of central bars and the measured water level was estimated using four mathematical models. Furthermore, a risk assessment index was proposed to map the spatial pattern of inundation risk of central bars. The results indicate a good ability of the GF-1 WFV imagery with a 16-m spatial resolution to characterize the seasonal variation of central river bars and to capture the impact of a flood disaster on the area of central bars. This paper observed a significant negative but nonlinear relationship between the water level and the area of central bars, and found that the cubic function fits best among four models (R² = 0.9839, P < 0.000001, RMSE = 0.4395). The maximum of the inundated area of central bars appeared during the rainy season on July 8, 2016, and the minimum occurred during the dry season on December 28, 2016, which are consistent with the water level measured by the hydrological station. The results derived from GF-1 data could provide a useful reference for decision-making of real-time disaster early warning and post-disaster reconstruction.

Keywords: central bars, dynamic change, water level, the Yangtze river

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Authors: Lynn Machin

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Using the lens of a theoretical framework relating to learning to learn the intention of the case study was to explore how transferable the teaching and learning skills of a newly qualified teacher (post-compulsory education) were when used in an overseas, unfamiliar and challenging post-compulsory educational environment. Particularly, the research sought to explore how this newly qualified teacher made use of the skills developed during their teacher training and to ascertain if, and what, other skills were necessary in order for them to have a positive influence on their learners and for them to be able to thrive within a different country and learning milieu. This case study looks at the experience of a trainee teacher who recently qualified in the UK to teach in post compulsory education (i.e. post 16 education). Rather than gaining employment in a UK based academy or college of further education this newly qualified teacher secured her first employment as a teacher in a province in China. Moreover, the newly qualified teacher had limited travel experience and had never travelled to Asia. She was one of the quieter and more reserved members on the one year teacher training course and was the least likely of the group to have made the decision to work abroad. How transferable the pedagogical skills that she had gained during her training would be when used in a culturally different and therefore (to her, challenging) environment was a key focus of the study. Another key focus was to explore the dispositions being used by the newly qualified teacher in order for her to teach and to thrive in an overseas educational environment. The methodological approach used for this study was both interpretative and qualitative. Associated methods were: Observation: observing the wider and operational practice of the newly qualified teacher over a five day period, and their need, ability and willingness to be reflective, resilient, reciprocal and resourceful. Interview: semi-structured interview with the newly qualified teacher following the observation of her practice. Findings from this case study illuminate the modifications made by the newly qualified teacher to her bank of teaching and learning strategies as well as the essentiality of dispositions used by her to know how to learn and also, crucially, to be ready and willing to do so. Such dispositions include being resilient, resourceful, reciprocal and reflective; necessary in order to adapt to the emerging challenges encountered by the teacher during their first months of employment in China. It is concluded that developing the skills to teach is essential for good teaching and learning practices. Having dispositions that enable teachers to work in ever changing conditions and surroundings is, this paper argues, essential for transferability and longevity of use of these skills.

Keywords: learning, post-compulsory, resilience, transferable

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Sandhya Rijal, Saroj Adhikari, Ramesh R. Pant

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Non-Timber Forest Products (NTFPs) have attracted substantial interest in the recent years with the increasing recognition that these can provide essential community needs for improved and diversified rural livelihood and support the objectives of biodiversity conservation. Nevertheless, various challenges are witnessed in their sustainable harvest and management. Assuming that sustainable management with community stewardship can offer one of the solutions to existing challenges, the study assesses the linkages between NTFPs and rural livelihood in Lamabagar village of Dolakha, Nepal. The major objective was to document the status of NTFPs and their contributions in households of Lamabagar. For status documentation, vegetation sampling was done using systematic random sampling technique. 30 plots of 10 m × 10 m were laid down in six parallel transect lines at horizontal distance of 160 m in two different community forests. A structured questionnaire survey was conducted in 76 households (excluding non-response rate) using stratified random sampling technique for contribution analysis. Likewise, key informant interview and focus group discussions were also conducted for data triangulations. 36 different NTFPs were recorded from the vegetation sample in two community forests of which 50% were used for medicinal purposes. The other uses include fodder, religious value, and edible fruits and vegetables. Species like Juniperus indica, Daphne bholua Aconitum spicatum, and Lyonia ovalifolia were frequently used for trade as a source of income, which was sold in local market. The protected species like Taxus wallichiana and Neopicrorhiza scrophulariiflora were also recorded in the area for which the trade is prohibited. The protection of these species urgently needs community stewardship. More than half of the surveyed households (55%) were depending on NTFPs for their daily uses, other than economic purpose whereas 45% of them sold those products in the market directly or in the form of local handmade products as a source of livelihood. NTFPs were the major source of primary health curing agents especially for the poor and unemployed people in the study area. Hence, the NTFPs contributed to livelihood under three different categories: subsistence, supplement income and emergency support, depending upon the economic status of the households. Although the status of forest improved after handover to the user group, the availability of valuable medicinal herbs like Rhododendron anthopogon, Swertia nervosa, Neopicrorhiza scrophulariiflora, and Aconitum spicatum were declining. Inadequacy of technology, lack of easy transport access, and absence of good market facility were the major limitations for external trade of NTFPs in the study site. It was observed that people were interested towards conservation only if they could get some returns: economic in terms of rural settlements. Thus, the study concludes that NTFPs could contribute rural livelihood and support conservation objectives only if local communities are provided with the easy access of technology, market and capital.

Keywords: contribution, medicinal, subsistence, sustainable harvest

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Authors: Tigist Mekonnen Melesse

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Since rural households are basically entitled to food through own production, improving productivity might lead to enhance the welfare of rural population through higher food availability at the household level and lowering the price of agricultural products. Increasing agricultural productivity through the use of improved technology is one of the desired outcomes from sensible food security and agricultural policy. The ultimate objective of this study was to evaluate the potential impact of improved agricultural technology adoption on smallholders’ crop productivity and welfare. The study is conducted in Ethiopia covering 1500 rural households drawn from four regions and 15 rural villages based on data collected by Ethiopian Rural Household Survey. Endogenous treatment effect model is employed in order to account for the selection bias on adoption decision that is expected from the self-selection of households in technology adoption. The treatment indicator, technology adoption is a binary variable indicating whether the household used improved seeds and chemical fertilizer or not. The outcome variables were cereal crop productivity, measured in real value of production and welfare of households, measured in real per capita consumption expenditure. Results of the analysis indicate that there is positive and significant effect of improved technology use on rural households’ crop productivity and welfare in Ethiopia. Adoption of improved seeds and chemical fertilizer alone will increase the crop productivity by 7.38 and 6.32 percent per year of each. Adoption of such technologies is also found to improve households’ welfare by 1.17 and 0.25 percent per month of each. The combined effect of both technologies when adopted jointly is increasing crop productivity by 5.82 percent and improving welfare by 0.42 percent. Besides, educational level of household head, farm size, labor use, participation in extension program, expenditure for input and number of oxen positively affect crop productivity and household welfare, while large household size negatively affect welfare of households. In our estimation, the average treatment effect of technology adoption (average treatment effect on the treated, ATET) is the same as the average treatment effect (ATE). This implies that the average predicted outcome for the treatment group is similar to the average predicted outcome for the whole population.

Keywords: Endogenous treatment effect, technologies, productivity, welfare, Ethiopia

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Authors: Emily Kislik, Gabriel Mantilla Saltos, Gladys Torres, Mercy Borbor-Córdova

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The Galápagos Marine Reserve (GMR) is an internationally-recognized region of consistent upwelling events, high productivity, and rich biodiversity. Despite its high-nutrient, low-chlorophyll condition, the archipelago has experienced phytoplankton blooms, especially in the western section between Isabela and Fernandina Islands. However, little is known about how climate variability will affect future phytoplankton standing stock in the Galápagos, and no consistent protocols currently exist to quantify phytoplankton biomass, identify species, or monitor for potential harmful algal blooms (HABs) within the archipelago. This analysis investigates physical, chemical, and biological oceanic variables that contribute to algal blooms within the GMR, using 4 km Aqua MODIS satellite imagery and 0.125-degree wind stress data from January 2003 to December 2016. Furthermore, this study analyzes chlorophyll-a concentrations at varying spatial scales— within the greater archipelago, as well as within five smaller bioregions based on species biodiversity in the GMR. Seasonal and interannual trend analyses, correlations, and hotspot identification were performed. Results demonstrate that chlorophyll-a is expressed in two seasons throughout the year in the GMR, most frequently in September and March, with a notable hotspot in the Elizabeth Bay bioregion. Interannual chlorophyll-a trend analyses revealed highest peaks in 2003, 2007, 2013, and 2016, and variables that correlate highly with chlorophyll-a include surface temperature and particulate organic carbon. This study recommends future in situ sampling locations for phytoplankton monitoring, including the Elizabeth Bay bioregion. Conclusions from this study contribute to the knowledge of oceanic drivers that catalyze primary productivity and consequently affect species biodiversity within the GMR. Additionally, this research can inform policy and decision-making strategies for species conservation and management within bioregions of the Galápagos.

Keywords: bioregions, ecological monitoring, phytoplankton, remote sensing

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Authors: Dejenie Birile Gemeda, Wilhelm Stork

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The power system is one of the most important systems in modern society. The existing power system is approaching the critical operating limits as views of several power system operators. With the increase of load demand, high capacity and long transmission networks are widely used to meet the requirement. With the integration of renewable energies such as wind and solar, the uncertainty, intermittence bring bigger challenges to the operation of power systems. These dynamic uncertainties in the power system lead to power disturbances. The disturbances in a heavily stressed power system cause distance relays to mal-operation or false alarms during post fault power oscillations. This unintended operation of these relays may propagate and trigger cascaded trappings leading to total power system blackout. This is due to relays inability to take an appropriate tripping decision based on ensuing power swing. According to the N-1 criterion, electric power systems are generally designed to withstand a single failure without causing the violation of any operating limit. As a result, some overloaded components such as overhead transmission lines can still work for several hours under overload conditions. However, when a large power swing happens in the power system, the settings of the distance relay of zone 3 may trip the transmission line with a short time delay, and they will be acting so quickly that the system operator has no time to respond and stop the cascading. Misfiring of relays in absence of fault due to power swing may have a significant loss in economic performance, thus a loss in revenue for power companies. This research paper proposes a method to distinguish stable power swing from unstable using dynamic line rating (DLR) in response to power swing or disturbances. As opposed to static line rating (SLR), dynamic line rating support effective mitigation actions against propagating cascading outages in a power grid. Effective utilization of existing transmission lines capacity using machine learning DLR predictions will improve the operating point of distance relay protection, thus reducing unintended power outages due to power swing.

Keywords: blackout, cascading outages, dynamic line rating, power swing, overhead transmission lines

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Authors: Solomon Okorley

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With the emergence of artificial intelligence, a proposition that has been made with increasing conviction is the need to assign legal personhood to robots. A major problem that arises when dealing with robots is the issue of liability: who do it hold liable when a robot causes harm? The suggestion to assign legal personality to robots has been made to aid in the assignment of liability. This paper contends that it is premature to assign legal personhood to robots. The paper employed the doctrinal and comparative research methodology. The paper first discusses the various theories that underpin the granting of legal personhood to juridical personalities to ascertain whether these theories can aid in the proposition to assign legal personhood to robots. These theories include fiction theory, aggregate theory, realist theory, and organism theory. Except for the aggregate theory, the fiction theory, the realist theory and the organism theory provide a good foundation to the proposal for legal personhood to be assigned to robots. The paper considers whether robots should be assigned legal personhood from a jurisprudential approach. The legal positivists assert that no metaphysical presuppositions are needed to determine who could be a legal person: the sole deciding factor is the engagement in legal relations and this prerequisite could be fulfilled by robots. However, rationalists, religionists and naturalists assert that the satisfaction of the metaphysical criteria is the basis of legal personality and since robots do not possess this feature, they cannot be assigned legal personhood. This differing perspective shows that the jurisprudential school of thought to which one belongs influences the decision whether to assign legal personhood to robots. The paper makes arguments for and against the assigning of legal personhood to robots. Assigning legal personhood to robots is necessary for the assigning of liability; and since robots are independent in their operation, they should be assigned legal personhood. However, it is argued that the degree of autonomy is insufficient. Robots do not understand legal obligations; they do not have a will of their own and the purported autonomy that they possess is an ‘imputed autonomy’. A crucial question to be asked is ‘whether it is desirable to confer legal personhood on robots’ and not ‘whether legal personhood should be assigned to robots’. This is due to the subjective nature of the responses to such a question as well as the peculiarities of countries in response to this question. The main argument in support of assigning legal personhood to robots is to aid in assigning liability. However, it is argued conferring legal personhood on robots is not the only way to deal with liability issues. Since any of the stakeholders involved with the robot system can be held liable for an accident, it is not desirable to assign legal personhood to robot. It is forecasted that in the epoch of strong artificial intelligence, granting robots legal personhood is plausible; however, in the current era, it is premature.

Keywords: autonomy, legal personhood, premature, jurisprudential

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

Procedia PDF Downloads 70