Search results for: specific assessment

Authors: Pedram Saadati, Zahra Nazari

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Anticipating and identifying future opportunities and challenges facing industry activists for the emergence and entry of new knowledge and technologies of personal financial planning, and providing practical solutions is one of the goals of this research. For this purpose, a future research tool based on receiving opinions from the main players of the insurance industry has been used. The research method in this study was in 4 stages; including 1- a survey of the specialist salesforce of life insurance in order to identify the variables 2- the ranking of the variables by experts selected by a researcher-made questionnaire 3- holding a panel of experts with the aim of understanding the mutual effects of the variables and 4- statistical analyzes of the mutual effects matrix in Mick Mac software is done. The integrated analysis of influencing variables in the future has been done with the method of Structural Analysis, which is one of the efficient and innovative methods of future research. A list of opportunities and challenges was identified through a survey of best-selling life insurance representatives who were selected by snowball sampling. In order to prioritize and identify the most important issues, all the issues raised were sent to selected experts who were selected theoretically through a researcher-made questionnaire. The respondents determined the importance of 36 variables through scoring, so that the prioritization of opportunity and challenge variables can be determined. 8 of the variables identified in the first stage were removed by selected experts, and finally, the number of variables that could be examined in the third stage became 28 variables, which, in order to facilitate the examination, were divided into 6 categories, respectively, 11 variables of organization and management. Marketing and sales 7 cases, social and cultural 6 cases, technological 2 cases, rebranding 1 case and insurance 1 case were divided. The reliability of the researcher-made questionnaire was confirmed with the Cronbach's alpha test value of 0.96. In the third stage, by forming a panel consisting of 5 insurance industry experts, the consensus of their opinions about the influence of factors on each other and the ranking of variables was entered into the matrix. The matrix included the interrelationships of 28 variables, which were investigated using the structural analysis method. By analyzing the data obtained from the matrix by Mic Mac software, the findings of the research indicate that the categories of "correct training in the use of the software, the weakness of the technology of insurance companies in personalizing products, using the approach of equipping the customer, and honesty in declaring no need Customer to Insurance", the most important challenges of the influencer and the categories of "salesforce equipping approach, product personalization based on customer needs assessment, customer's pleasant experience of being consulted with consulting robots, business improvement of the insurance company due to the use of these tools, increasing the efficiency of the issuance process and optimal customer purchase" were identified as the most important opportunities for influence.

Keywords: personal financial planning, wealth management, advisor robots, life insurance, digital transformation

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Radu Deju, Carmen Mustata

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The VVR-S nuclear research reactor owned by Horia Hubulei National Institute of Physics and Nuclear Engineering (IFIN-HH) was designed for research and radioisotope production, being permanently shut-down in 2002, after 40 years of operation. All amount of the nuclear spent fuel S-36 and EK-10 type was returned to Russian Federation (first in 2009 and last in 2012), and the radioactive waste resulted from the reprocessing of it will remain permanently in the Russian Federation. The decommissioning strategy chosen is immediate dismantling. At this moment, the radionuclides with half-life shorter than 1 year have a minor contribution to the contamination of materials and equipment used in reactor department. The decommissioning of the reactor has started in 2010 and is planned to be finalized in 2020, being the first nuclear research reactor that has started the decommissioning project from the South-East of Europe. The management system applied in the decommissioning of the VVR-S research reactor integrates all common elements of management: nuclear safety, occupational health and safety, environment, quality- compliance with the requirements for decommissioning activities, physical protection and economic elements. This paper presents the application of integrated management system in decommissioning of systems, structures, equipment and components (SSEC) from pumps room, including the management of the resulted radioactive waste. The primary cooling system of this type of reactor includes circulation pumps, heat exchangers, degasser, filter ion exchangers, piping connection, drainage system and radioactive leaks. All the decommissioning activities of primary circuit were performed in stage 2 (year 2014), and they were developed and recorded according to the applicable documents, within the requirements of the Regulatory Body Licenses. In the presentation there will be emphasized how the integrated management system provisions are applied in the dismantling of the primary cooling system, for elaboration, approval, application of necessary documentation, records keeping before, during and after the dismantling activities. Radiation protection and economics are the key factors for the selection of the proper technology. Dedicated and advanced technologies were chosen to perform specific tasks. Safety aspects have been taken into consideration. Resource constraints have also been an important issue considered in defining the decommissioning strategy. Important aspects like radiological monitoring of the personnel and areas, decontamination, waste management and final characterization of the released site are demonstrated and documented.

Keywords: decommissioning, integrated management system, nuclear reactor, waste management

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Authors: Linette van der Merwe

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It is known that visual artists, performing artists, and literary artists have inspired each other since time immemorial. The enduring, symbiotic relationship between the various art genres is evident where words, colours, lines, and sounds act as metaphors, a physical separation of the transcendental reality of art. Simonides of Keos (c. 556-468 BC) confirmed this, stating that a poem is a talking picture, or, in a more modern expression, a picture is worth a thousand words. It can be seen as an ancient relationship, originating from the epigram (tombstone or artefact inscriptions), the carmen figuratum (figure poem), and the ekphrasis (a description in the form of a poem of a work of art). Visual artists, including Michelangelo, Leonardo da Vinci, and Goethe, wrote poems and songs. Goya, Degas, and Picasso are famous for their works of art and for trying their hands at poetry. Afrikaans writers whose fine art is often published together with their writing, as in the case of Andries Bezuidenhout, Breyten Breytenbach, Sheila Cussons, Hennie Meyer, Carina Stander, and Johan van Wyk, among others, are not a strange phenomenon either. Imitating one art form into another art form is a form of translation, transposition, contemplation, and discovery of artistic impressions, showing parallel interpretations rather than physical comparison. It is especially about the harmony that exists between the different art genres, i.e., a poem that describes a painting or a visual text that portrays a poem that becomes a translation, interpretation, and rediscovery of the verbal text, or rather, from the word text to the image text. Poetry-film, as a form of such a translation of the word text into an image text, can be considered a hybrid, transdisciplinary art form that connects poetry and film. Poetry-film is regarded as an intertwined entity of word, sound, and visual image. It is an attempt to transpose and transform a poem into a new artwork that makes the poem more accessible to people who are not necessarily open to the written word and will, in effect, attract a larger audience to a genre that usually has a limited market. Poetry-film is considered a creative expression of an inverted ekphrastic inspiration, a visual description, interpretation, and expression of a poem. Research also emphasises that animated poetry-film is not widely regarded as a genre of anything and is thus severely under-theorized. This paper will focus on Afrikaans animated poetry-films as a multimodal transposition of a poem text to an animated poetry film, with specific reference to animated poetry-films in Filmverse I (2014) and Filmverse II (2016).

Keywords: poetry film, animated poetry film, poetic metaphor, conceptual metaphor, monomodal metaphor, multimodal metaphor, semiotic metaphor, multimodality, metaphor analysis, target domain, source domain

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Authors: Daniel Manaye Kabtamu, Anteneh Wodaje Bayeh

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With the development and utilization of new energy technology, people’s demand for large-scale energy storage system has become increasingly urgent. Vanadium redox flow battery (VRFB) is one of the most promising technologies for grid-scale energy storage applications because of numerous attractive features, such as long cycle life, high safety, and flexible design. However, the relatively low energy efficiency and high production cost of the VRFB still limit its practical implementations. It is of great attention to enhance its energy efficiency and reduce its cost. One of the main components of VRFB that can impressively impact the efficiency and final cost is the electrode materials, which provide the reactions sites for redox couples (V₂₊/V³⁺ and VO²⁺/VO₂⁺). Graphite felt (GF) is a typical carbon-based material commonly employed as electrode for VRFB due to low-cost, good chemical and mechanical stability. However, pristine GF exhibits insufficient wettability, low specific surface area, and poor kinetics reversibility, leading to low energy efficiency of the battery. Therefore, it is crucial to further modify the GF electrode to improve its electrochemical performance towards VRFB by employing active electrocatalysts, such as less expensive metal oxides. This study successfully fabricates low-cost plate-like bismuth vanadate (BiVO₄) material through a simple one-step hydrothermal route, employed as an electrocatalyst to adorn the GF for use as the negative electrode in VRFB. The experimental results show that BiVO₄-3h exhibits the optimal electrocatalytic activity and reversibility for the vanadium redox couples among all samples. The energy efficiency of the VRFB cell assembled with BiVO₄-decorated GF as the negative electrode is found to be 75.42% at 100 mA cm−2, which is about 10.24% more efficient than that of the cell assembled with heat-treated graphite felt (HT-GF) electrode. The possible reasons for the activity enhancement can be ascribed to the existence of oxygen vacancies in the BiVO₄ lattice structure and the relatively high surface area of BiVO₄, which provide more active sites for facilitating the vanadium redox reactions. Furthermore, the BiVO₄-GF electrode obstructs the competitive irreversible hydrogen evolution reaction on the negative side of the cell, and it also has better wettability. Impressively, BiVO₄-GF as the negative electrode shows good stability over 100 cycles. Thus, BiVO₄-GF is a promising negative electrode candidate for practical VRFB applications.

Keywords: BiVO₄ electrocatalyst, electrochemical energy storage, graphite felt, vanadium redox flow battery

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Authors: K. J. Keerthi, Vasundhara Kamineni, A. Ravi Shanker, T. Rammurthy, A. Vijaya Lakshmi, Q. Hasan

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Pancreatic β-cells are the predominant insulin-producing cell types within the Islets of Langerhans and insulin is the primary hormone which regulates carbohydrate and fat metabolism. Apoptosis of β-cells or insufficient insulin production leads to Diabetes Mellitus (DM). Current therapy for diabetes includes either medical management or insulin replacement and regular monitoring. Replacement of β- cells is an attractive treatment option for both Type-1 and Type-2 DM in view of the recent paper which indicates that β-cells apoptosis is the common underlying cause for both the Types of DM. With the development of Edmonton protocol, pancreatic β-cells allo-transplantation became possible, but this is still not considered as standard of care due to subsequent requirement of lifelong immunosuppression and the scarcity of suitable healthy organs to retrieve pancreatic β-cell. Fetal pancreatic cells from abortuses were developed as a possible therapeutic option for Diabetes, however, this posed several ethical issues. Hence, in the present study Mesenchymal stem cells (MSCs) were differentiated into insulin producing cells which were isolated from Human Umbilical cord (HUC) tissue. MSCs have already made their mark in the growing field of regenerative medicine, and their therapeutic worth has already been validated for a number of conditions. HUC samples were collected with prior informed consent as approved by the Institutional ethical committee. HUC (n=26) were processed using a combination of both mechanical and enzymatic (collagenase-II, 100 U/ml, Gibco ) methods to obtain MSCs which were cultured in-vitro in L-DMEM (Low glucose Dulbecco's Modified Eagle's Medium, Sigma, 4.5 mM glucose/L), 10% FBS in 5% CO2 incubator at 37°C. After reaching 80-90% confluency, MSCs were characterized with Flowcytometry and Immunocytochemistry for specific cell surface antigens. Cells expressed CD90+, CD73+, CD105+, CD34-, CD45-, HLA-DR-/Low and Vimentin+. These cells were differentiated to β-cells by using H-DMEM (High glucose Dulbecco's Modified Eagle's Medium,25 mM glucose/L, Gibco), β-Mercaptoethanol (0.1mM, Hi-Media), basic Fibroblast growth factor (10 µg /L,Gibco), and Nicotinamide (10 mmol/L, Hi-Media). Pancreatic β-cells were confirmed by positive Dithizone staining and were found to be functionally active as they released 8 IU/ml insulin on glucose stimulation. Isolating MSCs from usually discarded, abundantly available HUC tissue, expanding and differentiating to β-cells may be the most feasible cell therapy option for the millions of people suffering from DM globally.

Keywords: diabetes mellitus, human umbilical cord, mesenchymal stem cells, differentiation

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Authors: Aritra Das, Tanmay Mahapatra, Prabir Maharana, Sridhar Srikantiah

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In the absence of adequate well-equipped neonatal-care facilities serving rural Bihar, India, the practice of essential home-based newborn-care remains critically important for reduction of neonatal and infant mortality, especially among pre-term and small-for-gestational-age (Low-birth-weight) newborns. To improve the child health parameters in Bihar, ‘Very-Low-Birth-Weight (vLBW) Tracking’ intervention is being conducted by CARE India, since 2015, targeting public facility-delivered newborns weighing ≤2000g at birth, to improve their identification and provision of immediate post-natal care. To assess the effectiveness of the intervention, 200 public health facilities were randomly selected from all functional public-sector delivery points in Bihar and various outcomes were tracked among the neonates born there. Thus far, one pre-intervention (Feb-Apr’2015-born neonates) and three post-intervention (for Sep-Oct’2015, Sep-Oct’2016 and Sep-Oct’2017-born children) follow-up studies were conducted. In each round, interviews were conducted with the mothers/caregivers of successfully-tracked children to understand outcome, service-coverage and care-seeking during the neonatal period. Data from 171 matched facilities common across all rounds were analyzed using SAS-9.4. Identification of neonates with birth-weight ≤ 2000g improved from 2% at baseline to 3.3%-4% during post-intervention. All indicators pertaining to post-natal home-visits by frontline-workers (FLWs) improved. Significant improvements between baseline and post-intervention rounds were also noted regarding mothers being informed about ‘weak’ child – at the facility (R1 = 25 to R4 = 50%) and at home by FLW (R1 = 19%, to R4 = 30%). Practice of ‘Kangaroo-Mother-Care (KMC)’– an important component of essential newborn care – showed significant improvement in postintervention period compared to baseline in both facility (R1 = 15% to R4 = 31%) and home (R1 = 10% to R4=29%). Increasing trend was noted regarding detection and birth weight-recording of the extremely low-birth-weight newborns (< 1500 g) showed an increasing trend. Moreover, there was a downward trend in mortality across rounds, in each birth-weight strata (< 1500g, 1500-1799g and >= 1800g). After adjustment for the differential distribution of birth-weights, mortality was found to decline significantly from R1 (22.11%) to R4 (11.87%). Significantly declining trend was also observed for both early and late neonatal mortality and morbidities. Multiple regression analysis identified - birth during immediate post-intervention phase as well as that during the maintenance phase, birth weight > 1500g, children of low-parity mothers, receiving visit from FLW in the first week and/or receiving advice on extra care from FLW as predictors of survival during neonatal period among vLBW newborns. vLBW tracking was found to be a successful and sustainable intervention and has already been handed over to the Government.

Keywords: weak newborn tracking, very low birth weight babies, newborn care, community response

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Elizabeth Patricia Beck

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Stepping into various English as foreign language classrooms, one will see some fundamental similarities. There will likely be groups of students working collaboratively, possibly sitting at tables together. They will be using a set coursebook or photocopies of materials developed by publishers or the teacher. The teacher will be carefully monitoring students’ behaviour and progress. The teacher will also likely be insisting that the students only speak English together, possibly having implemented a complex penalty and award systems to encourage this. This is communicative language teaching and it is commonly how foreign languages are taught around the world. Recently, there has been much interest in the codeswitching behaviour of learners in foreign or second language classrooms. It is a significant topic as it relates to second language acquisition theory, language teaching training and policy, and student expectations and classroom practice. Generally in an English as a foreign language context, an ‘English Only’ policy is the norm. This is based on historical factors, socio-political influence and theories surrounding language learning. The trend, however, is shifting and, based on these same factors, a re-examination of language use in the foreign language classroom is taking place. This paper reports the findings of an examination into the codeswitching behaviour of learners with a shared native language in an English classroom. Specifically, it addresses the question of classroom code-switching by adult learners in the EFL classroom during student-to-student, spoken interaction. Three generic categories of code switching are proposed based on published research and classroom practice. Italian adult learners at three levels were observed and patterns of language use were identified, recorded and analysed using the proposed categories. After observations were completed, a questionnaire was distributed to the students focussing on attitudes and opinions around language choice in the EFL classroom, specifically, the usefulness of L1 for specific functions in the classroom. The paper then investigates the relationship between learners’ foreign language proficiency and the frequency and type of code-switching that they engaged in, and the relationship between learners’ attitudes to classroom code-switching and their behaviour. Results show that code switching patterns underwent changes as the students’ level of English language proficiency improved, and that students’ attitudes towards code-switching generally correlated with their behaviour with some exceptions, however. Finally, the discussion focusses on the details of the language produced in observation, possible influencing factors that may affect the frequency and type of code switching that took place, and additional influencing factors that may affect students’ attitudes towards code switching in the foreign language classroom. An evaluation of the limitations of this study is offered and some suggestions are made for future research in this field of study.

Keywords: code-switching, EFL, second language aquisition, adult learners

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Authors: Muhammad Irfan

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The rise of radicalization within Islam has spawned a new era of global terror. The battlefield Successes of ISIS and the Taliban are fuelled by an ideological war waged, largely and successfully, in the media arena. This research will examine how Islamic extremist groups are using media modalities and populist narratives to influence migrant Muslim populations in Europe towards extremism. In 2014, ISIS shocked the world in exporting horrifically graphic forms of violence on social media. Their Muslim support base was largely disgusted and reviled. In response, they reconfigured their narrative by introducing populist 'hooks', astutely portraying the Muslim populous as oppressed and exploited by unjust, corrupt autocratic regimes and Western power structures. Within this crucible of real and perceived oppression, hundreds of thousands of the most desperate, vulnerable and abused migrants left their homelands, risking their lives in the hope of finding peace, justice, and prosperity in Europe. Instead, many encountered social stigmatization, detention and/or discrimination for being illegal migrants, for lacking resources and for simply being Muslim. This research will examine how Islamic extremist groups are exploiting the disenfranchisement of these migrant populations and using populist messaging on social media to influence them towards violent extremism. ISIS, in particular, formulates specific encoded messages for newly-arriving Muslims in Europe, preying upon their vulnerability. Violence is posited, as a populist response, to the tyranny of European oppression. This research will analyze the factors and indicators which propel Muslim migrants along the spectrum from resilience to violence extremism. Expected outcomes are identification of factors which influence vulnerability towards violent extremism; an early-warning detection framework; predictive analysis models; and de-radicalization frameworks. This research will provide valuable tools (practical and policy level) for European governments, security stakeholders, communities, policy-makers, and educators; it is anticipated to contribute to a de-escalation of Islamic extremism globally.

Keywords: populism, radicalization, de-radicalization, social media, ISIS, Taliban, shariah, jihad, Islam, Europe, political communication, terrorism, migrants, refugees, extremism, global terror, predictive analysis, early warning detection, models, strategic communication, populist narratives, Islamic extremism

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Azza A. Ali, Mona G. Khalil, Hemat A. Elariny, Shereen S. El Shaer

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Background: Aluminium (Al) is very abundant metal in the earth’s crust. It is a constituent of cooking utensils, medicines, cosmetics, some foods and food additives. Salts of Al are widely used in the treatment of drinking water for purification purposes. Excessive and prolonged exposure to Al causes oxidative stress and impairment of many physiological functions. Its accumulation in liver and kidney causes hepatotoxicity and nephrotoxicity. Social isolation (SI) or Protein malnutrition (PM) also increases oxidative stress and may enhance the toxicity of Al as well as the degeneration in liver and kidney. Epigallocatechin-3-gallate (EGCG) is the most abundant catechin in green tea and has strong antioxidant as well as anti-inflammatory activities and can protect against oxidative stress-induced degenerations. Objective: To study the influence of stress or PM on Al-induced nephrotoxicity and hepatotoxicity in rats, as well as on the potential role of EGCG in providing protection. Methods: Rats received daily AlCl3 (70 mg/kg, IP) for three weeks (Al-toxicity groups) except one normal control group received saline. Al-toxicity groups were divided into four treated and four untreated groups; treated rats received EGCG (10 mg/kg, IP) together with AlCl3. One group of both treated and untreated rats served as control for each of them, and the others were subjected to either stress (mild using isolation or high using electric shock) or to PM (10% casein diet). Specimens of liver and kidney were used for assessment of levels of inflammatory mediators as TNF-α, IL6β, nuclear factor kappa B (NF-κB), oxidative stress (MDA, SOD, TAC, NO), Caspase-3 and for DNA fragmentation as well as for histopathological examinations. Biochemical changes were also measured in the serum as total lipids, cholesterol, triglycerides, glucose, proteins, bilirubin, creatinine and urea as well as the level of Alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) and lactate deshydrogenase (LDH). Results: Nephrotoxicity and hepatotoxicity induced by Al were enhanced in rats exposed to stress and to PM. The influence of stress was more pronounced than PM. Al-toxicity was indicated by the increase in liver and kidney MDA, NO, TNF-α, IL-6β, NF-κB, caspase-3, DNA fragmentation and in ALT, AST, ALP, LDH and total lipids, cholesterol, triglycerides, glucose, proteins, bilirubin, creatinine and urea levels, together with the decrease in total proteins, SOD, TAC. EGCG provided protection against hazards of Al as indicated by the decrease in MDA, NO, TNF-α, IL-6β, NF-κB, caspase-3 and DNA fragmentation as well as in levels of ALT, AST, ALP, LDH and total lipids, cholesterol, triglycerides, glucose, proteins, bilirubin, creatinine and urea in liver and kidney, together with the increase in total proteins, SOD, TAC and confirmed by histopathological examinations. It provided more pronounced protection in high stressful conditions than in mild one than in PM. Conclusion: Stress have a bad impact on Al-induced nephrotoxicity and hepatotoxicity more than PM. Thus it can clarify and maximize the role of EGCG in providing protection. Consequently, administration of EGCG is advised with excessive Al-exposure to avoid nephrotoxicity and hepatotoxicity especially in populations more subjected to stress or PM.

Keywords: aluminum, stress, protein malnutrition, nephrotoxicity, hepatotoxicity, epigallocatechin-3-gallate, rats

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Authors: Praveena Sinha

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Context: Diabetes is a global public health burden, particularly affecting postmenopausal women. Insulin resistance (IR) is prevalent in this population, and it is associated with an increased risk of developing type 2 diabetes. Yoga therapy is gaining attention as a complementary intervention for diabetes due to its potential to address stress psychophysiology. This study focuses on the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Research Aim: The aim of this research is to investigate the effect of a 3-month long yoga practice on insulin resistance in early postmenopausal women. Methodology: The study conducted a prospective longitudinal design with 67 women within five years of menopause. Participants were divided into two groups based on their willingness to join yoga. The Yoga group (n = 37) received routine gynecological management along with an integrated yoga module, while the Non-Yoga group (n = 30) received only routine management. Insulin resistance was measured using the homeostasis model assessment of insulin resistance (HOMA-IR) method before and after the intervention. Statistical analysis was performed using GraphPad Prism Version 5 software, with statistical significance set at P < 0.05. Findings: The results indicate a significant decrease in serum fasting insulin levels and HOMA-IR measurements in the Yoga group, although the decrease did not reach statistical significance. In contrast, the Non-Yoga group showed a significant rise in serum fasting insulin levels and HOMA-IR measurements after 3 months, suggesting a detrimental effect on insulin resistance in these postmenopausal women. Theoretical Importance: This study provides evidence that a 12-week yoga practice can attenuate the increase in insulin resistance in early postmenopausal women. It highlights the potential of yoga as a preventive measure against the early onset of insulin resistance and the development of type 2 diabetes mellitus. Regular yoga practice can be a valuable tool in addressing hormonal imbalances associated with early postmenopause, leading to a decrease in morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in this population. Data Collection and Analysis Procedures: Data collection involved measuring serum fasting insulin levels and calculating HOMA-IR. Statistical analysis was performed using GraphPad Prism Version 5 software, and mean values with standard error of the mean were reported. The significance level was set at P < 0.05. Question Addressed: The study aimed to address whether a 3-month long yoga practice could attenuate insulin resistance in early postmenopausal women. Conclusion: The research findings support the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Regular yoga practice has the potential to prevent the early onset of insulin resistance and the development of type 2 diabetes mellitus in this population. By addressing the hormonal imbalances associated with early post menopause, yoga could significantly decrease morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in these subjects.

Keywords: post menopause, insulin resistance, HOMA-IR, yoga, type 2 diabetes mellitus

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Authors: Kevin De Castro Cogle, Mirian Kubo, Maria Anastasiadi, Fady Mohareb, Claire Rossi

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Background: The bioaccessibility of bioactive compounds is a critical determinant of the nutritional quality of various food products. Despite its importance, there is a limited number of comprehensive studies aimed at assessing how the composition of a food matrix influences the bioaccessibility of a compound of interest. This knowledge gap has prompted a growing need to investigate the intricate relationship between food matrix formulations and the bioaccessibility of bioactive compounds. One such class of bioactive compounds that has attracted considerable attention is curcuminoids. These naturally occurring phytochemicals, extracted from the roots of Curcuma longa, have gained popularity owing to their purported health benefits and also well known for their poor bioaccessibility Project aim: The primary objective of this research project is to systematically assess the influence of matrix composition on the bioaccessibility of curcuminoids. Additionally, this study aimed to develop a series of predictive models for bioaccessibility, providing valuable insights for optimising the formula for functional foods and provide more descriptive nutritional information to potential consumers. Methods: Food formulations enriched with curcuminoids were subjected to in vitro digestion simulation, and their bioaccessibility was characterized with chromatographic and spectrophotometric techniques. The resulting data served as the foundation for the development of predictive models capable of estimating bioaccessibility based on specific physicochemical properties of the food matrices. Results: One striking finding of this study was the strong correlation observed between the concentration of macronutrients within the food formulations and the bioaccessibility of curcuminoids. In fact, macronutrient content emerged as a very informative explanatory variable of bioaccessibility and was used, alongside other variables, as predictors in a Bayesian hierarchical model that predicted curcuminoid bioaccessibility accurately (optimisation performance of 0.97 R2) for the majority of cross-validated test formulations (LOOCV of 0.92 R2). These preliminary results open the door to further exploration, enabling researchers to investigate a broader spectrum of food matrix types and additional properties that may influence bioaccessibility. Conclusions: This research sheds light on the intricate interplay between food matrix composition and the bioaccessibility of curcuminoids. This study lays a foundation for future investigations, offering a promising avenue for advancing our understanding of bioactive compound bioaccessibility and its implications for the food industry and informed consumer choices.

Keywords: bioactive bioaccessibility, food formulation, food matrix, machine learning, probabilistic modelling

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Authors: Ippei Torii, Kaoruko Ohtani, Takahito Niwa, Naohiro Ishii

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This paper shows developing an objectivity index using the measurement of subtle eyeball movement to diagnose autism. The developmentally disabled assessment varies, and the diagnosis depends on the subjective judgment of professionals. Therefore, a supplementary inspection method that will enable anyone to obtain the same quantitative judgment is needed. The diagnosis are made based on a comparison of the time of gazing an object in the conventional autistic study, but the results do not match. First, we divided the pupil into four parts from the center using measurements of subtle eyeball movement and comparing the number of pixels in the overlapping parts based on an afterimage. Then we developed the objective evaluation indicator to judge non-autistic and autistic people more clearly than conventional methods by analyzing the differences of subtle eyeball movements between the right and left eyes. Even when a person gazes at one point and his/her eyeballs always stay fixed at that point, their eyes perform subtle fixating movements (ie. tremors, drifting, microsaccades) to keep the retinal image clear. Particularly, the microsaccades link with nerves and reflect the mechanism that process the sight in a brain. We converted the differences between these movements into numbers. The process of the conversion is as followed: 1) Select the pixel indicating the subject's pupil from images of captured frames. 2) Set up a reference image, known as an afterimage, from the pixel indicating the subject's pupil. 3) Divide the pupil of the subject into four from the center in the acquired frame image. 4) Select the pixel in each divided part and count the number of the pixels of the overlapping part with the present pixel based on the afterimage. 5) Process the images with precision in 24 - 30fps from a camera and convert the amount of change in the pixels of the subtle movements of the right and left eyeballs in to numbers. The difference in the area of the amount of change occurs by measuring the difference between the afterimage in consecutive frames and the present frame. We set the amount of change to the quantity of the subtle eyeball movements. This method made it possible to detect a change of the eyeball vibration in numerical value. By comparing the numerical value between the right and left eyes, we found that there is a difference in how much they move. We compared the difference in these movements between non-autistc and autistic people and analyzed the result. Our research subjects consists of 8 children and 10 adults with autism, and 6 children and 18 adults with no disability. We measured the values through pasuit movements and fixations. We converted the difference in subtle movements between the right and left eyes into a graph and define it in multidimensional measure. Then we set the identification border with density function of the distribution, cumulative frequency function, and ROC curve. With this, we established an objective index to determine autism, normal, false positive, and false negative.

Keywords: subtle eyeball movement, autism, microsaccade, pursuit eye movements, ROC curve

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Authors: A. Bortkiewcz, A. Dudarewicz, P. Małecki, M. Kłaczyński, T. Wszołek, Małgorzata Pawlaczyk-Łuszczyńska

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Low-frequency noise (LFN) has been recognized as a special environmental pollutant. It is usually considered a broadband noise with the dominant content of low frequencies from 10 Hz to 250 Hz. A growing body of data shows that LFN differs in nature from other environmental noises, which are at comparable levels but not dominated by low-frequency components. The primary and most frequent adverse effect of LFN exposure is annoyance. Moreover, some recent investigations showed that LFN at relatively low A-weighted sound pressure levels (40−45 dB) occurring in office-like areas could adversely affect the mental performance, especially of high-sensitive subjects. It is well documented that high-frequency noise disturbs various types of human functions; however, there is very little data on the impact of LFN on well-being and health, including the cardiovascular system. Heart rate variability (HRV) is a sensitive marker of autonomic regulation of the circulatory system. Walker and co-workers found that LFN has a significantly more negative impact on cardiovascular response than exposure to high-frequency noise and that changes in HRV parameters resulting from LFN exposure tend to persist over time. The negative reactions of the cardiovascular system in response to LFN generated by wind turbines (20-200 Hz) were confirmed by Chiu. The scientific aim of the study is to assess the relationship between the spectral-temporal characteristics of LFN and the activity of the autonomic nervous system, considering the subjective assessment of annoyance, sensitivity to this type of noise, and cognitive and general health status. The study will be conducted in 20 male students in a special, acoustically prepared, constantly supervised room. Each person will be tested 4 times (4 sessions), under conditions of non-exposure (sham) and exposure to noise of wind turbines recorded at a distance of 250 meters from the turbine with different frequencies and frequency ranges: acoustic band 20 Hz-20 kHz, infrasound band 5-20 Hz, acoustic band + infrasound band. The order of sessions of the experiment will be randomly selected. Each session will last 1 h. There will be a 2-3 days break between sessions to exclude the possibility of the earlier session influencing the results of the next one. Before the first exposure, a questionnaire will be conducted on noise sensitivity, general health status using the GHQ questionnaire, hearing organ status and sociodemographic data. Before each of the 4 exposures, subjects will complete a brief questionnaire on their mood and sleep quality the night before the test. After the test, the subjects will be asked about any discomfort and subjective symptoms during the exposure. Before the test begins, Holter ECG monitoring equipment will be installed. HRV will be analyzed from the ECG recordings, including time and frequency domain parameters. The tests will always be performed in the morning (9-12) to avoid the influence of diurnal rhythm on HRV results. Students will perform psychological tests 15 minutes before the end of the test (Vienna Test System).

Keywords: neurovegetative control, heart rate variability (HRV), cognitive processes, low frequency noise

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Authors: Ioanna Garefi, Irene Kalemaki

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Education is not solely about preparing young people for the world of work but also about equipping them with competences that will enable them to become socially proactive, empowered, responsible, and engaged citizens who will collectively contribute to and benefit from an inclusive and sustainable future. Hence, progress assessment towards competence development is an ongoing process where continuous efforts are needed. This paper abstract presents the work of the H2020 NEMESIS project that aims to investigate, experiment and co-create together with schools a model for introducing and embedding social innovation education (SIE henceforth) in European primary and secondary schools. All in all, during the 2018-2019 academic year, 8 schools from 5 European countries involving 56 teachers, 1030 students, and 80 external stakeholders, experimented with different methodologies for embedding SIE in their contexts. This paper captures briefly the impact of these efforts towards the cultivation and progression of students’ social innovation (SI henceforth) competences. As part of the model, 14 SI competences, whose progress was evaluated, have been introduced falling under 3 interrelated categories: competences for identifying opportunities for social and collective value creation, competences for developing collaborations and building meaningful relations and competences for taking action both on an individual and collective level. Methodologically wise, the evaluation strategy employed was informed by a realist approach, enabling the researchers to go beyond synthesizing 'what happened' and towards understanding 'why it happened', delving into ‘what works, for whom and in what circumstances’. The reason for choosing such an approach was because it goes beyond attempting to answer the basic yes or no question of evaluation and focus on an ‘explanatory quest’ tracing the limits of when and where intervention is effective. A rich mix of sources of evidence have been employed, from focus groups with 80 people from the 5 EU countries to an online survey to 206 students, classroom observations, students’ narratives granting them with the opportunity to freely express their opinions, short stories letting students express their feelings through their imagination and also, drawings so that younger children can express their perception of reality. All these evidences offered insights on the impact of SIE on the development of students’ competences. Research findings showed that students progressed in all 14 SI competences through their involvement in the different activities. This positive progression is attributed to the model’s three core principles: 1) the student-centered approach, rendering students active and self-determined producers of their own learning, 2) the co-creation process fostering intergenerational interactions, empowering thus students by making their voices heard and valued and also, 3) the transformative social action whereby through their projects, students are able to witness the impact they are bringing about with their actions. Concluding, these initial findings, together with the forthcoming evaluation research to a pool of 30 schools around Europe, have the potential to raise the dynamics of the under-investigated field of SIE and encourage its embeddedness in more schools around Europe.

Keywords: competence development, education, social innovation, students

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Authors: Johan Esbach

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The entrepreneur has traditionally been defined through various historical lenses, emphasising individual traits, risk-taking, speculation, innovation and firm creation. However, these definitions often fail to address the dynamic nature of the modern entrepreneurial functions, which respond to unpredictable uncertainties and transition to routine management as certainty is achieved. This paper proposes a revised definition, positioning the entrepreneur as a dynamic function rather than a human construct, that emerges to address specific uncertainties in economic systems, but fades once uncertainty is resolved. By examining historical definitions and its limitations, including the works of Cantillon, Say, Schumpeter, and Knight, this paper identifies a gap in literature and develops a generalised definition for the entrepreneur. The revised definition challenges conventional thought by shifting focus from static attributes such as alertness, traits, firm creation, etc., to a dynamic role that includes reliability, adaptation, scalability, and adaptability. The methodology of this paper employs a mixed approach, combining theoretical analysis and case study examination to explore the dynamic nature of the entrepreneurial function in relation to uncertainty. The selection of case studies includes companies like Airbnb, Uber, Netflix, and Tesla, as these firms demonstrate a clear transition from entrepreneurial uncertainty to routine certainty. The data from the case studies is then analysed qualitatively, focusing on the patterns of entrepreneurial function across the selected companies. These results are then validated using quantitative analysis, derived from an independent survey. The primary finding of the paper will validate the entrepreneur as a dynamic function rather than a static, human-centric role. In considering the transition from uncertainty to certainty in companies like Airbnb, Uber, Netflix, and Tesla, the study shows that the entrepreneurial function emerges explicitly to address market, technological, or social uncertainties. Once these uncertainties are resolved and a certainty in the operating environment is established, the need for the entrepreneurial function ceases, giving way to routine management and business operations. The paper emphasises the need for a definitive model that responds to the temporal and contextualised nature of the entrepreneur. In adopting the revised definition, the entrepreneur is positioned to play a crucial role in the reduction of uncertainties within economic systems. Once the uncertainties are addressed, certainty is manifested in new combinations or new firms. Finally, the paper outlines policy implications for fostering environments that enables the entrepreneurial function and transition theory.

Keywords: dynamic function, uncertainty, revised definition, transition

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Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

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Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Antoine Dumont, Weiji Hong, Zheng-Hong Lu

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Light emitting diodes (LEDs) are steadily becoming the new standard for luminescent display devices because of their energy efficiency and relatively low cost, and the purity of the light they emit. Our research focuses on the optical properties of the lead halide perovskite CsPbBr₃ and its family that is showing steadily improving performances in LEDs and solar cells. The objective of this work is to investigate CsPbBr₃ as an emitting layer made by physical vapor deposition instead of the usual solution-processed perovskites, for use in LEDs. The deposition in vacuum eliminates any risk of contaminants as well as the necessity for the use of chemical ligands in the synthesis of quantum dots. Initial results show the versatility of the dual-source evaporation method, which allowed us to create different phases in bulk form by altering the mole ratio or deposition rate of CsBr and PbBr₂. The distinct phases Cs₄PbBr₆, CsPbBr₃ and CsPb₂Br₅ – confirmed through XPS (x-ray photoelectron spectroscopy) and X-ray diffraction analysis – have different optical properties and morphologies that can be used for specific applications in optoelectronics. We are particularly focused on the blue shift expected from quantum dots (QDs) and the stability of the perovskite in this form. We already obtained proof of the formation of QDs through our dual source evaporation method with electron microscope imaging and photoluminescence testing, which we understand is a first in the community. We also incorporated the QDs in an LED structure to test the electroluminescence and the effect on performance and have already observed a significant wavelength shift. The goal is to reach 480nm after shifting from the original 528nm bulk emission. The hole transport layer (HTL) material onto which the CsPbBr₃ is evaporated is a critical part of this study as the surface energy interaction dictates the behaviour of the QD growth. A thorough study to determine the optimal HTL is in progress. A strong blue shift for a typically green emitting material like CsPbBr₃ would eliminate the necessity of using blue emitting Cl-based perovskite compounds and could prove to be more stable in a QD structure. The final aim is to make a perovskite QD LED with strong blue luminescence, fabricated through a dual-source evaporation technique that could be scalable to industry level, making this device a viable and cost-effective alternative to current commercial LEDs.

Keywords: material physics, perovskite, light emitting diode, quantum dots, high vacuum deposition, thin film processing

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Authors: Bamikole J. Adeyemi, Prashant Jadhawar, Lateef Akanji

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Theoretically, there exist two mathematical interfaces (fluid-solid and fluid-fluid) when a liquid film is present on solid surfaces. These interfaces overlap if the mineral surface is oil-wet or mixed wet, and therefore, the effects of disjoining pressure are significant on both boundaries. Hence, dewetting is a necessary process that could detach oil from the mineral surface. However, if the thickness of the thin water film directly in contact with the surface is large enough, disjoining pressure can be thought to be zero at the liquid-liquid interface. Recent studies show that the integration of fluid-fluid interactions with fluid-rock interactions is an important step towards a holistic approach to understanding smart water effects. Experiments have shown that the brine solution can alter the micro forces at oil-water interfaces, and these ion-specific interactions lead to oil emulsion formation. The natural emulsifiers present in crude oil behave as polyelectrolytes when the oil interfaces with low salinity water. Wettability alteration caused by low salinity waterflooding during Enhanced Oil Recovery (EOR) process results from the activities of divalent ions. However, polyelectrolytes are said to lose their viscoelastic property with increasing cation concentrations. In this work, the influence of cation concentrations on the dynamics of viscoelastic liquid-liquid interfaces is numerically investigated. The resultant ion concentrations at the crude oil/brine interfaces were estimated using a surface complexation model. Subsequently, the ion concentration parameter is integrated into a mathematical model to describe its effects on the dynamics of a viscoelastic interfacial thin film. The film growth, stability, and rupture were measured after different time steps for three types of fluids (Newtonian, purely elastic and viscoelastic fluids). The interfacial films respond to exposure time in a similar manner with an increasing growth rate, which resulted in the formation of more droplets with time. Increased surfactant accumulation at the interface results in a higher film growth rate which leads to instability and subsequent formation of more satellite droplets. Purely elastic and viscoelastic properties limit film growth rate and consequent film stability compared to the Newtonian fluid. Therefore, low salinity and reduced concentration of the potential determining ions in injection water will lead to improved interfacial viscoelasticity.

Keywords: liquid-liquid interfaces, surfactant concentrations, potential determining ions, residual oil mobilization

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Authors: Sonia Tamanna, Akramul Hassan, Mohammad Shakil Mahmood, Farzana Ansari, Gowhar Rashid, Mir Fahim Faisal, M. Zakir Hossain Howlader

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Background: Preeclampsia (PE), a pregnancy-specific hypertensive disorder, significantly impacts maternal and fetal health. It is particularly prevalent in underdeveloped countries and is linked to preterm delivery and fetal growth. The renin-angiotensin system (RAS) plays a crucial role in ensuring a successful pregnancy outcome, with Angiotensin-Converting Enzyme 2 (ACE2) being a key component. ACE2 converts ANG II to Ang-(1-7), offering protection against ANG II-induced stress and inflammation while regulating blood pressure and osmotic balance during pregnancy. The reduced maternal plasma angiotensin-converting enzyme 2 (ACE2) seen in preeclampsia might contribute to its pathogenesis. However, there has been a dearth of comprehensive research into the association between ACE2 gene polymorphism and preeclampsia. In the South Asian population, hypertension is strongly linked to two SNPs: rs2285666 and rs879922. This genotype was therefore considered, and the possible association of maternal and fetal ACE2 gene polymorphism with preeclampsia within the Bangladeshi population was evaluated. Method: DNA was extracted from peripheral white blood cells (WBCs) using the organic method, and SNP genotyping was done via PCR-RFLP. Odds ratios (OR) with 95% confidence intervals (95% CI) were calculated using logistic regression to determine relative risk. Result: A comprehensive case-control study was conducted on 51 PE patients and their infants, along with 56 control subjects and their infants. Maternal single nuvleotide polymorphisms (SNP) (rs2285666) analysis revealed a strong association between the TT genotype and preeclampsia, with a four-fold increased risk in mothers (P=0.024, OR=4.00, 95% CI=1.36-11.37) compared to their ancestral genotype CC. However, the CT genotype (rs2285666) showed no significant difference (P=0.46, OR=1.54, 95% CI=0.57-4.14). Notably, no significant correlation was found in infants, regardless of their gender. For rs879922, no significant association was observed in both mothers and infants. This pioneering study suggests that mothers carrying the ACE2 gene variant rs2285666 (TT allele) may be at higher risk for preeclampsia, potentially influencing hypertension characteristics, whereas rs879922 does not appear to be associated with developing preeclampsia. Conclusion: This study sheds light on the role of ACE2 gene polymorphism, particularly the rs2285666 TT allele, in maternal susceptibility to preeclampsia. However, rs879922 does not appear to be linked to the risk of PE. This research contributes to our understanding of the genetic underpinnings of preeclampsia, offering insights into potential avenues for prevention and management.

Keywords: ACE2, PCR-RFLP, preeclampsia, single nuvleotide polymorphisms (SNPs)

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Authors: Orkide Donma, Mustafa M. Donma, Muhammet Demirkol, Murat Aydin, Tuba Gokkus, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

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Obesity in childhood establishes a ground for adulthood obesity. Especially morbid obesity is an important problem for the children because of the associated diseases such as diabetes mellitus, cancer and cardiovascular diseases. In this study, body mass index (BMI), body fat ratios, anthropometric measurements and ratios were evaluated together with different laboratory indices upon evaluation of obesity in morbidly obese (MO) children. Children with nutritional problems participated in the study. Written informed consent was obtained from the parents. Study protocol was approved by the Ethics Committee. Sixty-two MO girls aged 129.5±35.8 months and 75 MO boys aged 120.1±26.6 months were included into the scope of the study. WHO-BMI percentiles for age-and-sex were used to assess the children with those higher than 99^th as morbid obesity. Anthropometric measurements of the children were recorded after their physical examination. Bio-electrical impedance analysis was performed to measure fat distribution. Anthropometric ratios, body fat ratios, Index-I and Index-II as well as insulin sensitivity indices (ISIs) were calculated. Girls as well as boys were binary grouped according to homeostasis model assessment-insulin resistance (HOMA-IR) index of <2.5 and >2.5, fasting glucose to insulin ratio (FGIR) of <6 and >6 and quantitative insulin sensitivity check index (QUICKI) of <0.33 and >0.33 as the frequently used cut-off points. They were evaluated based upon their BMIs, arms, legs, trunk, whole body fat percentages, body fat ratios such as fat mass index (FMI), trunk-to-appendicular fat ratio (TAFR), whole body fat ratio (WBFR), anthropometric measures and ratios [waist-to-hip, head-to-neck, thigh-to-arm, thigh-to-ankle, height/2-to-waist, height/2-to-hip circumference (C)]. SPSS/PASW 18 program was used for statistical analyses. p≤0.05 was accepted as statistically significance level. All of the fat percentages showed differences between below and above the specified cut-off points in girls when evaluated with HOMA-IR and QUICKI. Differences were observed only in arms fat percent for HOMA-IR and legs fat percent for QUICKI in boys (p≤ 0.05). FGIR was unable to detect any differences for the fat percentages of boys. Head-to-neck C was the only anthropometric ratio recommended to be used for all ISIs (p≤0.001 for both girls and boys in HOMA-IR, p≤0.001 for girls and p≤0.05 for boys in FGIR and QUICKI). Indices which are recommended for use in both genders were Index-I, Index-II, HOMA/BMI and log HOMA (p≤0.001). FMI was also a valuable index when evaluated with HOMA-IR and QUICKI (p≤0.001). The important point was the detection of the severe significance for HOMA/BMI and log HOMA while they were evaluated also with the other indices, FGIR and QUICKI (p≤0.001). These parameters along with Index-I were unique at this level of significance for all children. In conclusion, well-accepted ratios or indices may not be valid for the evaluation of both genders. This study has emphasized the limiting properties for boys. This is particularly important for the selection process of some ratios and/or indices during the clinical studies. Gender difference should be taken into consideration for the evaluation of the ratios or indices, which will be recommended to be used particularly within the scope of obesity studies.

Keywords: anthropometry, childhood obesity, gender, insulin sensitivity index

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Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

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Authors: Mona Alyedreessy

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This study, which is based on a qualitative study sample of thirty-four British converts from different ages, ethnicities, social classes, areas and religious backgrounds in London, investigates the common challenges, problems and abuse in the name of Islam that many British female Muslim converts experienced during their time as Muslims, which caused them to leave the faith. It is an important study, as it creates an awareness of the weaknesses found in western Muslim societies and in various Islamic educational programs that causes people to leave Islam and contribute towards its negative reputation in the media. The women in this study shared common problems regarding gender and racial discrimination, identity development, feminism, marriage, parenting, Muslim culture, isolation, extremism, belonging and practising Islam in both Muslim and non-Muslim societies with differing sacrifices and consequences that caused them to de-convert. The study argues that many of the personal, religious and social problems female Muslim converts experience are due to a lack of knowledge about Islam and their rights as Muslim women, which often results in them being vulnerable and influenced by the opinions, attitudes and actions of uneducated, abusive, non-practising and extremist Muslims. For example, it was found that young female converts in particular were often taken advantage of and manipulated into believing that many negative actions displayed by patriarchal Muslim husbands were a part of Islam. This created much confusion, especially when their husbands used specific Quran texts and Hadiths to justify their abuse, authority and attitudes that made them miserable. As a result and based on the positive experiences of some converts, the study found that obtaining a broad Islamic education that started with an intimate study of the Prophet Muhammad’s biography alongside being guided by the teachings of western Muslim scholars contributed greatly towards a more enjoyable conversion journey, as women were able to identify and avoid problematic Muslims and abuse in the name of Islam. This in turn helped to create a healthier family unit and Muslim society. Those who enjoyed being Muslims were able to create a balanced western Muslim identity by negotiating and applying their own morals and western values to their understanding of The Prophet’s biography and The Quran and integrated Islamic values into their own secular western environments that were free from foreign cultural practices. The outcomes of the study also highlight some effective modern approaches to da’wah based on the teachings of The Prophet Mohammad and other prophets for young Arab and Asian Muslims who marry, study and live among non-Muslims and converts.

Keywords: abuse, apostasy, converts, Muslims

Procedia PDF Downloads 232

Authors: Piret Pernik

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Based on strategic, operational, and technical analysis of the ongoing armed conflict in Ukraine, this paper will examine the opportunities and risks of using small commercial drones (dual-use unmanned aerial vehicles, UAV) for military purposes. The paper discusses the opportunities and risks in the information domain, encompassing both cyber and electromagnetic interference and attacks. The paper will draw conclusions on a possible strategic impact to the battlefield outcomes in the modern armed conflicts by the widespread use of dual-use UAVs. This article will contribute to filling the gap in the literature by examining based on empirical data cyberattacks and electromagnetic interference. Today, more than one hundred states and non-state actors possess UAVs ranging from low cost commodity models, widely are dual-use, available and affordable to anyone, to high-cost combat UAVs (UCAV) with lethal kinetic strike capabilities, which can be enhanced with Artificial Intelligence (AI) and Machine Learning (ML). Dual-use UAVs have been used by various actors for intelligence, reconnaissance, surveillance, situational awareness, geolocation, and kinetic targeting. Thus they function as force multipliers enabling kinetic and electronic warfare attacks and provide comparative and asymmetric operational and tactical advances. Some go as far as argue that automated (or semi-automated) systems can change the character of warfare, while others observe that the use of small drones has not changed the balance of power or battlefield outcomes. UAVs give considerable opportunities for commanders, for example, because they can be operated without GPS navigation, makes them less vulnerable and dependent on satellite communications. They can and have been used to conduct cyberattacks, electromagnetic interference, and kinetic attacks. However, they are highly vulnerable to those attacks themselves. So far, strategic studies, literature, and expert commentary have overlooked cybersecurity and electronic interference dimension of the use of dual use UAVs. The studies that link technical analysis of opportunities and risks with strategic battlefield outcomes is missing. It is expected that dual use commercial UAV proliferation in armed and hybrid conflicts will continue and accelerate in the future. Therefore, it is important to understand specific opportunities and risks related to the crowdsourced use of dual-use UAVs, which can have kinetic effects. Technical countermeasures to protect UAVs differ depending on a type of UAV (small, midsize, large, stealth combat), and this paper will offer a unique analysis of small UAVs both from the view of opportunities and risks for commanders and other actors in armed conflict.

Keywords: dual-use technology, cyber attacks, electromagnetic warfare, case studies of cyberattacks in armed conflicts

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Authors: Gerd Wilsch, Tobias Guenther, Tobias Voelker

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In view of the ageing of vital infrastructure facilities, a reliable condition assessment of concrete structures is becoming of increasing interest for asset owners to plan timely and appropriate maintenance and repair interventions. For concrete structures, reinforcement corrosion induced by penetrating chlorides is the dominant deterioration mechanism affecting the serviceability and, eventually, structural performance. The determination of the quantitative chloride ingress is required not only to provide valuable information on the present condition of a structure, but the data obtained can also be used for the prediction of its future development and associated risks. At present, wet chemical analysis of ground concrete samples by a laboratory is the most common test procedure for the determination of the chloride content. As the chloride content is expressed by the mass of the binder, the analysis should involve determination of both the amount of binder and the amount of chloride contained in a concrete sample. This procedure is laborious, time-consuming, and costly. The chloride profile obtained is based on depth intervals of 10 mm. LIBS is an economically viable alternative providing chloride contents at depth intervals of 1 mm or less. It provides two-dimensional maps of quantitative element distributions and can locate spots of higher concentrations like in a crack. The results are correlated directly to the mass of the binder, and it can be applied on-site to deliver instantaneous results for the evaluation of the structure. Examples for the application of the method in the laboratory for the investigation of diffusion and migration of chlorides, sulfates, and alkalis are presented. An example for the visualization of the Li transport in concrete is also shown. These examples show the potential of the method for a fast, reliable, and automated two-dimensional investigation of transport processes. Due to the better spatial resolution, more accurate input parameters for model calculations are determined. By the simultaneous detection of elements such as carbon, chlorine, sodium, and potassium, the mutual influence of the different processes can be determined in only one measurement. Furthermore, the application of a mobile LIBS system in a parking garage is demonstrated. It uses a diode-pumped low energy laser (3 mJ, 1.5 ns, 100 Hz) and a compact NIR spectrometer. A portable scanner allows a two-dimensional quantitative element mapping. Results show the quantitative chloride analysis on wall and floor surfaces. To determine the 2-D distribution of harmful elements (Cl, C), concrete cores were drilled, split, and analyzed directly on-site. Results obtained were compared and verified with laboratory measurements. The results presented show that the LIBS method is a valuable addition to the standard procedures - the wet chemical analysis of ground concrete samples. Currently, work is underway to develop a technical code of practice for the application of the method for the determination of chloride concentration in concrete.

Keywords: chemical analysis, concrete, LIBS, spectroscopy

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Authors: Olusegun F. Adebowale

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Research has confirmed that the emergence of information technology is significantly reflected in the field of psychology and its related disciplines due to its widespread use at reasonable price and its user-friendliness. It is consequently affecting ordinary life in many areas like shopping, advertising, corresponding and educating. Specifically the innovations of computer technology led to several new forms of communication, all with implications and applicability for counselling and psychotherapy practices. This is premise on which online counselling is based. Most institutions of higher learning in Nigeria have established their presence on the Internet and have deployed a variety of applications through ICT. Some are currently attempting to include counselling services in such applications with the belief that many counselling needs of students are likely to be met. This study therefore explored different challenges and preferences students present in online counselling interaction in a given Nigerian university with the view to guide new universities that may want to invest into these areas as to necessary preparations and referral requirements. The study is a mixed method research incorporating qualitative and quantitative methodologies to sample the preferences and concerns students express in online interaction. The sample comprised all the 876 students who visited the university online counselling platform either voluntarily, by invitation or by referral. The instrument for data collection was the online counselling platform of the university 'OAU Online counsellors'. The period of data collection spanned between January 2011 and October 2012. Data were analysed quantitatively (using percentages and Mann-Whitney U test) and qualitatively (using Interpretative Phenomenological Analysis (IPA)). The results showed that the students seem to prefer real-time chatting as their online medium of communicating with the online counsellor. The majority of students resorted to e-mail when their effort to use real-time chatting were becoming thwarted. Also, students preferred to enter into online counselling relationships voluntarily to other modes of entry. The results further showed that the prevalent counselling needs presented by students during online counselling sessions were mainly in the areas of social interaction and academic/educational concerns. Academic concerns were found to be prevalent, in form of course offerings, studentship matters and academic finance matters. The personal/social concerns were in form of students’ welfare, career related concerns and relationship matters. The study concludes students’ preferences include voluntary entry into online counselling, communication by real-time chatting and a specific focus on their academic concerns. It also recommends that all efforts should be made to encourage students’ voluntary entry into online counselling through reliable and stable internet infrastructure that will be able to support real-time chatting.

Keywords: online, counselling, needs, preferences

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Authors: Ghada Ahmed

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Feminist translation is one of the strategies adopted in the field of translation studies when a gendered content is being rendered from one language to another, and this strategy has been examined in previous studies on written texts. This research, however, addresses the practice of feminist translation in audiovisual texts that are concerned with the screen, dialogue, image and visual aspects. In this thesis, the objectives are studying feminist translation and its adaptation in subtitling from Arabic into English. It addresses the connections between gender and translation as one domain and feminist translation practices with particular consideration of feminist translation strategies in English subtitles. It examines the visibility of the translator throughout the process, assuming that feminist translation is a product directed by the translator’s feminist position, culture, and ideology as a means of helping unshadow women. It also discusses how subtitling constraints impact feminist translation and how the image that has a narrative value can be integrated into the content of the English subtitles. The reasons for conducting this research project are to study language sexism in English and look into Arabic into English gendered content, taking into consideration the Arabic cultural concepts that may lose their connotations when they are translated into English. This research is also analysing the image in an audiovisual text and its contribution to the written dialogue in subtitling. Thus, this research attempts to answer the following questions: To what extent is there a form of affinity between a gendered content and translation? Is feminist translation an act of merely working on a feminist text or feminising the language of any text, by incorporating the translator’s ideology? How can feminist translation practices be applied in an audiovisual text? How likely is it to adapt feminist translation looking into visual components as well as subtitling constraints? Moreover, the paper searches into the fields of gender and translation; feminist translation, language sexism, media studies, and the gap in the literature related to feminist translation practice in visual texts. For my case study, the "Speed Sisters" film has been chosen so as to analyze its English subtitles for my research. The film is a documentary that was produced in 2015 and directed by Amber Fares. It is about five Palestinian women who try to break the stereotypes about women, and have taken their passion about car-racing forward to be the first all-women car-racing driving team in the Middle East. It tackles the issue of gender in both content and language and this is reflected in the translation. As the research topic is semiotic-channelled, the choice for the theoretical approaches varies and combines between translation studies, audiovisual translation, gender studies, and media studies. Each of which will contribute to understanding a specific field of the research and the results will eventually be integrated to achieve the intended objectives in a way that demonstrates rendering a gendered content in one of the audiovisual translation modes from a language into another.

Keywords: audiovisual translation, feminist translation, films gendered content, subtitling conventions and constraints

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