Search results for: diagnostic language assessment

Authors: Lavinia Flueckiger, Roselind Lieb, Andrea H. Meyer, Cornelia Witthauer, Jutta Mata

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Objective: Health behaviors tend to show a high variability over time within the same person. However, most existing research can only assess a snapshot of a person’s behavior and not capture this natural daily variability. Two intensive longitudinal studies examine the variability in health behavior over one academic year and their implications for other aspects of daily life such as affect and academic performance. Can already a single day of increased physical activity, snacking, or improved sleep have beneficial effects? Methods: In two intensive longitudinal studies with up to 65 assessment days over an entire academic year, university students (Study 1: N = 292; Study 2: N = 304) reported sleep quality, physical activity, snacking, positive and negative affect, and learning goal achievement. Results: Multilevel structural equation models showed that on days on which participants reported better sleep quality or more physical activity than usual, they also reported increased positive affect, decreased negative affect, and better learning goal achievement. Higher day-to-day snacking was only associated with increased positive affect. Both, increased day-to-day sleep quality and physical activity were indirectly associated with better learning goal achievement through changes in positive and negative affect; results for snacking were mixed. Importantly, day-to-day sleep quality was a stronger predictor for affect and learning goal achievement than physical activity or snacking. Conclusion: One day of better sleep or more physical activity than usual is associated with improved affect and academic performance. These findings have important implications for low-threshold interventions targeting the improvement of daily functioning.

Keywords: sleep quality, physical activity, snacking, affect, academic performance, multilevel structural equation model

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Authors: Pankaj Dhiman, Simranjeet Kaur

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This research paper presents a comprehensive sentiment analysis of social media responses to videos on Facebook, YouTube, Twitter, and Instagram during the 2024 Indian general elections. The study focuses on the sentiment patterns of voters towards the National Democratic Alliance (NDA) and The Indian National Developmental Inclusive Alliance (INDIA) on these platforms. The analysis aims to understand the impact of social media on voter sentiment and its correlation with the election outcome. The study employed a mixed-methods approach, combining both quantitative and qualitative methods. With a total of 200 posts analysed during general election-2024 final phase, the sentiment analysis was conducted using natural language processing (NLP) techniques, including sentiment dictionaries and machine learning algorithms. The results show that NDA received significantly more positive sentiment responses across all platforms, with a positive sentiment score of 47% compared to INDIA's score of 38.98 %. The analysis also revealed that Twitter and YouTube were the most influential platforms in shaping voter sentiment, with 60% of the total sentiment score coming from these two platforms. The study's findings suggest that social media sentiment analysis can be a valuable tool for understanding voter sentiment and predicting election outcomes. The results also highlight the importance of social media in shaping public opinion and the need for political parties to engage effectively with voters on these platforms. The study's implications are significant, as they indicate that social media can be a key factor in determining the outcome of elections. The findings also underscore the need for political parties to develop effective social media strategies to engage with voters and shape public opinion.

Keywords: Indian Elections-2024, NDA, INDIA, sentiment analysis, social media, democracy

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Authors: M. A. Mabasa, O. Ramokolo, M. Z. Mnikathi, D. Mathabatha, T. Manyapelo

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The study examines the importance of translating South African folklore from Oral into Written Literature in a Multilingual Education. Therefore, the study postulates that translation can be regarded as a valuable tool when oral and written literature is transmitted from one generation to another. The study entails that translation does not take place in a haphazard fashion; for that reason, skills such as translation principles are required to translate folklore significantly and effectively. The purpose of the study is to indicate the significance of using translation relating to folklore in teaching and learning. The study also observed that Modernism in literature should be shared amongst varieties of cultures because folklore is interactive in narrating stories, folktales and myths to sharpen the reader’s knowledge and intellect because they are informative and educative in nature. As a technological tool, the study points out that translation is of paramount importance in the sense that the meanings of different data can be made available in all South African official languages using oral and written forms of folklore. The study opines that tradition and customary beliefs and practices in the institution of higher learning. The study envisages the way in which literature of folklore can be juxtaposed to ensure that translated folklore is of quality assured standards. The study alludes that well-translated folklore can serve as oral and written literature, which may contribute to the child’s learning and acquisition of knowledge and insights during cognitive development toward maturity. Methodologically, the study selects a qualitative research approach and selects content analysis as an instrument for data gathering, which will be analyzed qualitatively in consideration of the significance of translating folklore as written and spoken literature in a documented way. The study reveals that the translation of folktales promotes functional multilingualism in high-function formal contexts like a university. The study emphasizes that translated and preserved literary folklore may serve as a language repository from one generation to another because of the archival and storage of information in the form of a term bank.

Keywords: translation, editing, teaching, learning, folklores

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Authors: Anjana R. Menon, Anjana Bhasi

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Development of highways and railways play crucial role in a nation’s economic growth. While rigid concrete pavements are durable with high load bearing characteristics, growing economies mostly rely on flexible pavements which are easier in construction and more economical. The strength of flexible pavement is based on the strength of subgrade and load distribution characteristics of intermediate granular layers. In this scenario, to simultaneously meet economy and strength criteria, it is imperative to strengthen and stabilize the load transferring layers, namely subbase and base. Geosynthetic reinforcement in planar and cellular forms have been proven effective in improving soil stiffness and providing a stable load transfer platform. Studies have proven the relative superiority of cellular form-geocells over planar geosynthetic forms like geogrid, owing to the additional confinement of infill material and pocket effect arising from vertical deformation. Hence, the present study investigates the efficiency of geocells over single/multiple layer geogrid reinforcements by a series of three-dimensional model analyses of a flexible pavement section under a standard repetitive wheel load. The stress transfer mechanism and deformation profiles under various reinforcement configurations are also studied. Geocell reinforcement is observed to take up a higher proportion of stress caused by the traffic loads compared to single and double-layer geogrid reinforcements. The efficiency of single geogrid reinforcement reduces with an increase in embedment depth. The contribution of lower geogrid is insignificant in the case of the double-geogrid reinforced system.

Keywords: Geocell, Geogrid, Flexible Pavement, Repetitive Wheel Load, Numerical Analysis

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Authors: Vladimir Zobov, Nail Nazarov, Alexandra Vyshtakalyuk, Vyacheslav Semenov, Irina Galyametdinova, Vladimir Reznik

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The aim of this study was to investigate hepatoprotective properties of the Xymedon derivative L-ascorbate 1- (2-hydroxyethyl)-4,6-dimethyl-1,2-dihydropyrimidine-2-one (XD), which exhibits high efficiency as actoprotector. The study was carried out on 68 male albino rats weighing 250-400 g using preventive exposure to the test preparation. Effectiveness of XD win comparison with effectiveness of Xymedon (original substance) after administration of the compounds in identical doses. Maximum dose was 20 mg/kg. The animals orally received Xymedon or its derivative in doses of 10 and 20 mg/kg over 4 days. In 1-1.5 h after drug administration, CCl4 in vegetable oil (1:1) in a dose of 2 ml/kg. Controls received CCl4 but without hepatoprotectors. Intact control group consisted of rats, not receiving CCl4 or other compounds. The next day after the last administration of CCl4 and compounds under study animals were dehematized under ether anesthesia, blood and liver samples were taken for biochemical and histological analysis. Xymedon and XD administered according to the preventice scheme, exerted hepatoprotective effects: Xymedon — in the dose of 20 mg/kg, XD — in doses of 10 and 20 mg/kg. The drugs under study had different effects on liver condition, affected by induction with CCl4. Xymedon had a more pronounced effect both on the ALT level, which can be elevated not only due to destructive changes in hepatocytes, but also as a cholestasis manifestation, and on the serum total protein level, which reflects protein synthesis in liver. XD had a more pronounced effect on AST level, which is one of the markers of hepatocyte damage. Lower effective dose of XD — 10 mg/kg, compared to Xymedon effective according to, and its pronounced effect on AST, the hepatocyte cytolysis marker, is indicative of its higher preventive effectiveness, compared to Xymedon. This work was performed with the financial support of Russian Science Foundation (grant No: 14-50-00014).

Keywords: hepatoprotectors, pyrimidine derivatives, toxic liver damage, xymedon

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Authors: Kayum Fokoue Carole

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This paper aims at verifying the effectiveness of reaching target populations while paying attention to their cultural background when communicating new knowledge, ideas or technology in a multicultural world. Our case study is an experiment on the communication of knowledge on breast cancer in three sub-Saharan countries (Ghana, Tchad, and Cameroon health). The methodology consisted of submitting a semi-structured questionnaire to local populations in some localities in these target countries in order to determine the cultural barriers hindering the effective communication of knowledge on breast cancer. Once this done, sensitization documents on breast cancer were translated into Ewe (Ghana), Mbaye (Tchad), Ghomala’, Ewondo, and Fufulde (Cameroon). In each locality, a sensitization programme was organised for two groups. For one group, the cultural barriers discovered were taken into consideration while communicating during the programme whereas in the other group, they were not. Another questionnaire was disseminated after three months to verify the level of appropriation of those who attended the campaign based on Chumbow’s appropriation theory. This paper, therefore, discusses some spiritual beliefs, representations and practices in the target African communities hindering effective communication of issues on breast cancer in the target localities. Findings reveal that only 38% of respondents in the group of those for whom cultural barriers were not taken into account during the programme had a high level of appropriation while for the other group, 86% had a high level of appropriation. This is evidence that the communication of issues on breast cancer can be more effective by reaching different populations in a language they best master while paying attention to their culture. Therefore, international communication of new knowledge should be culturally contextualised. Suggestions at the end of the paper are directed towards the achievement of these goals. The present work promotes international partnership in addressing and resolving global health preoccupations since research findings from one community/country can be mutualized in partnership with other communities and countries.

Keywords: cultural barriers, communication, health, breast cancer

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Authors: Avanika Gupta

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Education plays a significant and remedial role in balancing the socio-economic fabric of a country. Inclusive education is considered as the most appropriate mode of teaching students with hearing impairment (SwHI) by various national and international legislations. But inclusive education is still an evolving concept among the disability studies scholars and policy makers in India. The study aimed to examine accessibility of SwHI in mainstream schools if there are special provisions for SwHI. The study also intended to identify if the provisions are same for deaf and hard-of-hearing students. Using stratified random sampling technique, a school was selected from each of the six administrative zones of Nagpur city. All the selected schools had primary and secondary level education and were co-educational in nature. Interview with principals of these schools and focused-group- observation method showcased lack of accessibility for SwHI in attending schools. Not even a single school had a hearing impaired student, either deaf or hard-of-hearing depicting the double marginalization of SwHI. This is despite the fact that the right to education is a fundamental right in India, and national legislation on disability has special provisions for ensuring educational opportunities to SwHI. None of the schools even had an Indian Sign Language (ISL) instructor. Both observations seemed cause and effect of one another. One of the principals informed that they have seats for all students with disabilities but they usually lie vacant due to lack of awareness among the parents. One school had 2 students with locomotive impairment while another had a student with visual impairment. Principals of two special schools were also interviewed to understand the reason behind the low enrollment rate of SwHI in mainstream schools. Guardian preference, homogeneity, relatable faculty, familiar environment were some of the chief reasons mentioned. Few suggestions for the policymakers, teachers, guardians and the students are also recommended so that Indian education system could become inclusive in true sense.

Keywords: deaf, hard-of-hearing, inclusive education, India, Nagpur, students with hearing impairment

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Authors: Iuliana-Erika Köpeczi

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‘Language is no longer regarded as peripheral to our grasp of the world we live in, but as central to it. Words are not mere vocal labels or communicational adjuncts superimposed upon an already given order of things. They are collective products of social interaction, essential instruments through which human beings constitute and articulate their world’, said Roy Harris. If we were to accept the above-mentioned premise, then we surely must accept that discourse, generally, - and political discourse, specifically -, bears a crucial importance to one’s perception of reality. The way in which political rhetoric constructs reality changes the relationship between the voter and his/her view of the world, which, in turn, influences greatly the future trends of political participation. In this context, our inquiry focuses on the role of populist discourses in the post 9/11 political rhetoric, and how this led to the formation, construction and reconstruction of identity within the ‘us’ vs. ‘them’ dichotomy. It is our hypothesis that anti-intellectualistic elements played a significant role in the manner in which identity construction had been carried out on a discursive level. By adopting a comparative approach, we intend to identify the similarities and differences between the use of such anti-intellectualist elements in the United States of America on one hand – within the discourse of Rick Santorum, – and France on the other – with Marine le Pen’s discourse. Our methodological approach uses close textual analysis of primary source material (discourse analysis); historical contextualization of both primary documents and broader socio-political and cultural framework through archival research and secondary sources; as well as interpretation of primary texts through theoretical frameworks (qualitative research). We hope that the output of our endeavor will be useful in better understanding the different correlations that exist between anti-intellectualism and populism and how the interactions between these two elements aids in political identity construction through discourse.

Keywords: anti-intellectualism, discourse theory, France, identity construction, populism, United States of America

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Authors: Francesca Radice

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Domestic and sexual violence provokes, on average in Australia, one female death per week due to intimate violence behaviours. 83% of couples meet online, and intercepting domestic and sexual violence at this level would be beneficial. It has been observed that violent or coercive behaviour has been apparent from initial conversations on dating apps like Tinder. Child pornography, stalking, and coercive control are some criminal offences from dating apps, including women murdered after finding partners through Tinder. Police databases and predictive policing are novel approaches taken to prevent crime before harm is done. This research will investigate how police databases can be used in a privacy-preserving way to characterise users in terms of their potential for violent crime. Using the COPS database of NSW Police, we will explore how the past criminal record can be interpreted to yield a category of potential danger for each dating app user. It is up to the judgement of each subscriber on what degree of the potential danger they are prepared to enter into. Sentiment analysis is an area where research into natural language processing has made great progress over the last decade. This research will investigate how sentiment analysis can be used to interpret interchanges between dating app users to detect manipulative or coercive sentiments. These can be used to alert law enforcement if continued for a defined number of communications. One of the potential problems of this approach is the potential prejudice a categorisation can cause. Another drawback is the possibility of misinterpreting communications and involving law enforcement without reason. The approach will be thoroughly tested with cross-checks by human readers who verify both the level of danger predicted by the interpretation of the criminal record and the sentiment detected from personal messages. Even if only a few violent crimes can be prevented, the approach will have a tangible value for real people.

Keywords: sentiment analysis, data mining, predictive policing, virtual manipulation

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Authors: Surender Singh, Yogendra Kumar Gupta

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Boerhaavia diffusa (BD) Linn. belonging to family Nyctaginaceae is a herbaceous plant and known as ‘punarnava’ in Hindi, used as herbal medicine for pain relief and various ailments. It is widely used as a green leafy vegetable in many Asian and African countries. The objective of present study was to investigate potential adverse effects, if any, of standardized root extract of Boerhaavia diffusa in rats following subchronic administration. In acute toxicity study, no mortality was found at a dose of 2000mg/kg which indicates that oral LD50 of Boerhaavia diffusa root extract is more than 2000mg/kg. The chronic administration of Boerhaavia diffusa for 28 days at a dose of 1000mg/kg body weight did not produce any significant changes in hematological (RBC, WBC, platelets, hemoglobin, bleeding time, clotting time) and biochemical (triglycerides, blood glucose, high density lipoprotein, serum creatinine, serum glutamic oxaloacetic transaminase, serum glutamic pyruvic transaminase) parameters of male and female rats as compared to normal control group. All the animals survived until the scheduled necropsy, and their physical and behavioral examinations did not reveal any treatment-related adverse effects. No pathological changes were observed in histological section of heart, kidney, liver, testis, ovaries and brain of Boerhaavia diffusa treated male and female rats as compared to normal control animals.These observations from oral acute toxicitystudy suggest that the extract is practically non-toxic. Thus, it can be inferred that the Boerhaavia diffusa root extract at levels up to 1000 mg/kg/day was found to be safe and does not cause adverse effects in rats. So, the no-observed effect level (NOAEL) of the extract was found to be 1000mg/kg/day.

Keywords: Boerhaavia diffusa, histology, toxicity, sub-acute

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Authors: Fabiha Tanzeem

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BACKGROUND: Osteoporosis is a skeletal disease that is associated with a reduction in bone mass and microstructures of the bone and deterioration of bone tissue. Fragility fracture due to osteoporosis is the most significant complication of osteoporosis. The increasing prevalence of fragility fractures presents a growing burden on the global economy. There is a rapidly evolving need to improve awareness of the costs associated with these types of fractures and to review current policies and practices for the prevention and management of the disease. This systematic review will identify and describe the direct and indirect costs associated with osteoporotic fragility fractures from a global perspective from the included studies. The review will also find out whether the costs required for the treatment of fragility fractures due to osteoporosis impose an economic burden on the global healthcare system. METHODS: Four major databases were systematically searched for direct and indirect costs of osteoporotic fragility fracture studies in the English Language. PubMed, Cochrane Library, Embase and Google Scholar were searched for suitable articles published between 1990 and July 2020. RESULTS: The original search yielded 1166 papers; from these, 27 articles were selected for this review according to the inclusion and exclusion criteria. In the 27 studies, the highest direct costs were associated with the treatment of pelvic fractures, with the majority of the expenditure due to hospitalization and surgical treatments. It is also observed that most of the articles are from developed countries. CONCLUSION: This review indicates the significance of the economic burden of osteoporosis globally, although more research needs to be done in developing countries. In the treatment of fragility fractures, direct costs were the main reported expenditure in this review. The healthcare costs incurred globally can be significantly reduced by implementing measures to effectively prevent the disease. Raising awareness in children and adults by improving the quality of the information available and standardising policies and planning of services requires further research.

Keywords: systematic review, osteoporosis, cost of illness

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Authors: Amit K. Mishra, Jaswant Singh

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The menace of plastic, which significantly pollutes the aquatic environment, has emerged as a global problem. There is an emerging concern about microplastics (MPs) accumulation in aquatic ecosystems. It is familiar to everyone that the ultimate end for most of the plastic debris is the ocean. Rivers are the efficient carriers for transferring MPs from terrestrial to aquatic, further from upstream to downstream areas, and ultimately to oceans. The root cause study can provide an effective solution to a problem; hence, tracing of MPs in the riverine system can illustrate the long-term microplastic pollution. This study aimed to investigate the occurrence and distribution of microplastic contamination in surface water and sediment of the two major river systems of Uttar Pradesh, India. One is the Gomti River, Lucknow, a tributary of the Ganga, and the second is the Saryu River, the lower part of the Ghagra River, which flows through the city of Ayodhya. In this study, the distribution and abundance of MPs in surface water and sediments of two rivers were compared. Samples of water and sediment were collected from different (four from each river) sampling stations in the river catchment of two rivers. Plastic particles were classified according to type, shape, and color. In this study, 1523 (average abundance 254) and 143 (average abundance 26) microplastics were identified in all studied sites in the Gomati River and Saryu River, respectively. Observations on samples of water showed that the average MPs concentration was 392 (±69.6) and 63 ((±18.9) particles per 50l of water, whereas the sediment sample showed that the average MPs concentration was 116 (±42.9) and 46 (±12.5) particles per 250gm of dry sediment in the Gomati River and Saryu River, respectively. The high concentration of microplastics in the Lucknow area can be attributed to human activities, population density, and the entry of various effluents into the river. Microplastics with fibrous shapes were dominated, followed by fragment shapes in all the samples. The present study is a pioneering effort to count MPs in the Gomati and Saryu River systems.

Keywords: freshwater, Gomati, microplastics, Saryu, sediment

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Authors: Daniel L. Clinciu, IkromAbdulaev, Brian D. Oscar

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Various personality profile tests are used to identify personality strengths and limits in individuals, helping both individuals and managers to optimize work and team effort in organizations. One such test, Hartman’s personality profile emphasizes four driving "core motives" influenced or affected by both strengths and limitations. The driving core motives are classified into four colors: Red-motivated by power; Blue-discipline and loyalty; White-peace; and Yellow–fun loving. Two shortcomings of Hartman’s personality test are noted; 1) only one choice for every item/situation allowed and 2) selection of a choice even if not applicable. A test taker may be as much nurturing as he is opinionated but since “opinionated” seems less attractive the individual would likely select nurturing, causing a misidentification in personality strengths and limits. Since few individuals have a "strong" personality, it is difficult to assess their true personality strengths and limits allowing either only one choice or requiring unwanted choices, undermining the potential of the test. We modified Hartman’s personality profile allowing test takers to make either multiple choices for any item/situation or leave them blank when not applying. Sixty-eight participants (38 males and 30 females), 17-49 years old, from countries in Asia, Europe, N. America, CIS, Africa, Latin America, and Oceania were included. 58 participants (85.3%) reported the modified test, allowing either multiple or no choices better identified their personality strengths and limits, while 10 participants (14.7%) expressed the original (one choice version) is sufficient. The overall results show our modified test enhanced the identification and balance of personality strengths and limits, aiding test takers, managers, and firms to better understand personality strengths and limits, particularly useful in making task-related, teamwork, and management decisions.

Keywords: organizational behavior, personality tests, personality limitations, personality strengths, task management, team work

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Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

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Authors: Nora Kuiper, Candace Rowell, Hugues Preud'Homme, Basem Shomar

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As the global dependence on seawater desalination as a primary drinking water resource increases, a unique class of secondary pollutants is emerging. The presence of bromide salts in seawater may result in increased levels of bromine and brominated byproducts in drinking water. The State of Qatar offers a unique setting to study these pollutants and their impacts on consumers as the country is 100% dependent on seawater desalination to supply municipal tap water and locally produced bottled water. Tap water (n=115) and bottled water (n=62) samples were collected throughout the State of Qatar and analyzed for a suite of inorganic and organic compounds, including 54 volatile organic compounds (VOCs), with an emphasis on brominated byproducts. All VOC identification and quantification was completed using a Bruker Scion GCMSMS with static headspace technologies. A risk survey tool was used to collect information regarding local consumption habits, health outcomes and perception of water sources for adults and children. This study is the first of its kind in the country. Dibromomethane, bromoform, and bromobenzene were detected in 61%, 88% and 2%, of the drinking water samples analyzed. The levels of dibromomethane ranged from approximately 100-500 ng/L and the concentrations of bromoform ranged from approximately 5-50 µg/L. Additionally, bromobenzene concentrations were 60 ng/L. The presence of brominated compounds in drinking water is a public health concern specific to populations using seawater as a feed water source and may pose unique risks that have not been previously studied. Risk assessments are ongoing to quantify the risks associated with prolonged consumption of disinfection byproducts; specifically the risks of brominated trihalomethanes as the levels of bromoform found in Qatar’s drinking water reach more than 60% of the US EPA’s Maximum Contaminant Level of all THMs.

Keywords: brominated byproducts, desalination, trihalomethanes, risk assessment

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Authors: Norbert Simon, Rodeano Roslee, Abdul Ghani Rafek, Goh Thian Lai, Azimah Hussein, Lee Khai Ern

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The 54 km stretch of Ranau-Tambunan (RTM) road in Sabah is subjected to slope failures almost every year. This study is focusing on identifying section of roads that are susceptible to failure based on temporal landslide density and lineament density analyses. In addition to the analyses, the rock slopes in several sections of the road were assessed using the geological strength index (GSI) technique. The analysis involved 148 landslides that were obtained in 1978, 1994, 2009 and 2011. The landslides were digitized as points and the point density was calculated based on every 1km2 of the road. The lineaments of the area was interpreted from Landsat 7 15m panchromatic band. The lineament density was later calculated based on every 1km2 of the area using similar technique with the slope failure density calculation. The landslide and lineament densities were classified into three different classes that indicate the level of susceptibility (low, moderate, high). Subsequently, the two density maps were overlap to produce the final susceptibility map. The combination of both high susceptibility classes from these maps signifies the high potential of slope failure in those locations in the future. The final susceptibility map indicates that there are 22 sections of the road that are highly susceptible. Seven rock slopes were assessed along the RTM road using the GSI technique. It was found from the assessment that rock slopes along this road are highly fractured, weathered and can be classified into fair to poor categories. The poor condition of the rock slope can be attributed to the high lineament density that presence in the study area. Six of the rock slopes are located in the high susceptibility zones. A detailed investigation on the 22 high susceptibility sections of the RTM road should be conducted due to their higher susceptibility to failure, in order to prevent untoward incident to road users in the future.

Keywords: GSI, landslide, landslide density, landslide susceptibility, lineament density

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Authors: Kumar Khatri, Bibhuti Ranjan Jha, Smriti Gurung, Udhab Raj Khadka

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Freshwater fishes are crucial components of aquatic ecosystems but are being affected by a range of anthropogenic activities. A large number of freshwater bodies in Nepal are under different anthropogenic threats, thereby affecting freshwater biodiversity, including fish fauna. Inter-basin water transfer (IBWT) involving damming and diversion has been considered as one of the major threats to the rivers, yet many such projects are in the pipeline. Impact assessment of such projects include generation of baseline information on different biotic and abiotic variables. The aim of this study was to generate baseline information on fish diversity from the glacial-fed Bheri and the spring-fed Babai rivers and their selected tributaries from Western Nepal in the wake of the first inter-basin water transfer from the former to the latter. A total of 10 sites, 5 each from Bheri and Babai systems, were chosen strategically. Seasonal electrofishing was conducted in 2018 following the standard method. A total of 32 species with Catch per Unite Effort (CPUE) of 46.94±24.06 from Bheri and 42 species with CPUE of 63.02±51.80 from Babai were recorded. Cyprinidae, followed by Nemacheilidae, were the most dominant fish Family in both river systems. Barilius vagra and Schistura beavani were the most dominant species in the Bheri and the Babai systems, respectively. Species richness and abundance showed a significant difference between the rivers. The difference in fish assemblages reflects differences in the ecological regimes of these rivers. Of the total species, at least 8 are in the threatened categories of the IUCN Red List, which need active conservation measures. The findings provide a reference to assess the impacts of water transfers on fish in these river systems and could be helpful to other similar river systems in the future.

Keywords: babai river, bheri river, fish diversity, damming

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

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Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

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Authors: Shivam Yadav, Neelam Atri

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Cyanobacteria are photoautotrophic prokaryotes able to grow in diverse ecological habitats, originated 2.5 - 3.5 billion years ago and brought oxygenic photosynthesis. Since then superoxide dismutases (SODs) acquired great significance due to their ability to catalyze detoxification of byproducts of oxygenic photosynthesis, i.e. superoxide radicals. Sequence information from several cyanobacterial genomes offers a unique opportunity to conduct a comprehensive comparative analysis of the superoxide dismutases family. In the present study, we extracted information regarding SODs from species of sequenced cyanobacteria and investigated their diversity, conservation, domain structure, and evolution. 144 putative SOD homologues were identified. SODs are present in all cyanobacterial species reflecting their significant role in survival. However, their distribution varies, fewer in unicellular marine strains whereas abundant in filamentous nitrogen-fixing cyanobacteria. Motifs and invariant amino acids typical in eukaryotic SODs were conserved well in these proteins. These SODs were classified into three major families according to their domain structures. Interestingly, they lack additional domains as found in proteins of other family. Phylogenetic relationships correspond well with phylogenies based on 16S rRNA and clustering occurs on the basis of structural characteristics such as domain organization. Similar conserved motifs and amino acids indicate that cyanobacterial SODs make use of a similar catalytic mechanism as eukaryotic SODs. Gene gain-and-loss is insignificant during SOD evolution as evidenced by absence of additional domain. This study has not only examined an overall background of sequence-structure-function interactions for the SOD gene family but also revealed variation among SOD distribution based on ecophysiological and morphological characters.

Keywords: comparative genomics, cyanobacteria, phylogeny, superoxide dismutases

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Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

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The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

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Authors: Pinky Mae O. De Leon, Franchezka S. P. Flores

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This study focuses on applying an enhanced density-based spatial clustering algorithm with noise for fire risk assessments and warnings in Metro Manila. Unlike other clustering algorithms, DBSCAN is known for its ability to identify arbitrary-shaped clusters and its resistance to noise. However, its performance diminishes when handling high dimensional data, wherein it can read the noise points as relevant data points. Also, the algorithm is dependent on the parameters (eps & minPts) set by the user; choosing the wrong parameters can greatly affect its clustering result. To overcome these challenges, the study proposes three key enhancements: first is to utilize multiple MinHash and locality-sensitive hashing to decrease the dimensionality of the data set, second is to implement Jaccard Similarity before applying the parameter Epsilon to ensure that only similar data points are considered neighbors, and third is to use the concept of Jaccard Neighborhood along with the parameter MinPts to improve in classifying core points and identifying noise in the data set. The results show that the modified DBSCAN algorithm outperformed three other clustering methods, achieving fewer outliers, which facilitated a clearer identification of fire-prone areas, high Silhouette score, indicating well-separated clusters that distinctly identify areas with potential fire hazards and exceptionally achieved a low Davies-Bouldin Index and a high Calinski-Harabasz score, highlighting its ability to form compact and well-defined clusters, making it an effective tool for assessing fire hazard zones. This study is intended for assessing areas in Metro Manila that are most prone to fire risk.

Keywords: DBSCAN, clustering, Jaccard similarity, MinHash LSH, fires

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Maria C. Proença, Maria T. Rebelo, Maria J. Alves, Sofia Cunha

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Vector-borne diseases are transmitted to humans by mosquitos, sandflies, bugs, ticks, and other vectors. Some are re-transmitted between vectors, if the infected human has a new contact when his levels of infection are high. The vector is infected for lifetime and can transmit infectious diseases not only between humans but also from animals to humans. Some vector borne diseases are very disabling and globally account for more than one million deaths worldwide. The mosquitoes from the complex Culex pipiens sl. are the most abundant in Portugal, and we dispose in this moment of a data set from the surveillance program that has been carried on since 2006 across the country. All mosquitos’ species are included, but the large coverage of Culex pipiens sl. and its importance for public health make this vector an interesting candidate to assess risk of disease amplification. This work focus on ports and airports identified as key areas of high density of vectors. Mosquitoes being ectothermic organisms, the main factor for vector survival and pathogen development is temperature. Minima and maxima local air temperatures for each area of interest are averaged by month from data gathered on a daily basis at the national network of meteorological stations, and interpolated in a geographic information system (GIS). The range of temperatures ideal for several pathogens are known and this work shows how to use it with the meteorological data in each port and airport facility, to focus an efficient implementation of countermeasures and reduce simultaneously risk transmission and mitigation costs. The results show an increased alert with decreasing latitude, which corresponds to higher minimum and maximum temperatures and a lower amplitude range of the daily temperature.

Keywords: human health, risk assessment, risk management, vector-borne diseases

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Authors: Amritansh Agarwal, Tejaswi Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

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Authors: Abir Dey, Shams Noman

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Introduction: Offshore Island is the remote and isolated area from the terrestrial mainland. They are deprived of their needs. The children from an offshore island are usually underserved in the case of health care because it is a remote area where the health care systems are quite poor compared to mainland. So, the proper information is required for appropriate planning to reduce underlying causes behind visual deprivation among the surviving children of the Offshore Island. Purpose: The purpose of this study was to determine ocular morbidities, knowledge, and barriers of eye care services among children in an Offshore Island. Methods: The study team visited, and all data were collected from different rural communities at Sandwip Upazila, Chittagong district for screening the children aged 5-16 years old by doing spot examination. The whole study was conducted in both qualitative and quantitative methods. To determine ocular status of children, examinations were done under skilled Ophthalmologists and Optometrists. A focus group discussion was held. The sample size was 490. It was a community based descriptive study and the sampling method was purposive sampling. Results: In total 490 children, about 56.90% were female and 43.10% were male. Among them 456 were school-going children (93.1%) and 34 were non-school going children (6.9%). In this study the most common ocular morbidity was Allergic Conjunctivitis (35.2%). Other mentionable ocular morbidities were Refractive error (27.7%), Blepharitis (13.8%), Meibomian Gland Dysfunction (7.5%), Strabismus (6.3%) and Amblyopia (6.3%). Most of the non-school going children were involved in different types of domestic work like farming, fishing, etc. About 90.04% children who had different ocular abnormalities could not attend to the doctor due to various reasons. Conclusions: The ocular morbidity was high in rate on the offshore island. Eye health care facility was also not well established there. Awareness should be raised about necessity of maintaining hygiene and eye healthcare among the island people. Timely intervention through available eye care facilities and management can reduce the ocular morbidity rate in that area.

Keywords: morbidities, screening, barriers, offshore island, knowledge

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Authors: Chingwen Yeh, I. Chen Huang

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This paper aims to conduct a case study on kinesthetic intelligence development intervention with a child who has Asperger symptom identified by physician. First, the characteristics of Asperger were defined based on the related literature. Some Asperger's people are born with outstanding insight and are good at solving complex and difficult problems. In contrast to high-functioning autistic, Asperger children do not lose their ability to express themselves verbally. However in the cognitive function, they focus mainly on the things they are interested in instead of paying attention to the whole surrounding situation. Thus it is difficult for them not only to focus on things that they are not interesting in, but also to interact with people. Secondly, 8-weeks of kinesthetic intelligence development courses were designed within a series of physical action that including the following sections: limbs coordination, various parts of body rhythm changes, strength and space awareness and breathing practice. In classroom observations were recorded both on words and with video as the qualitative research data. Finally, in-depth interview with the case child’s teachers, parents and other in class observers were documented on a weekly base in order to examine the effectiveness of before and after the kinesthetic intelligence development course and to testify the usefulness of the lesson plan. This research found that the case child has improved significantly in terms of attention span and body movement creativity. In the beginning of intervention, the case child made less eyes contact with others. The instructor needed to face the case child to confirm the eyes contact. And the instructor also used various adjective words as guiding language for all kinds of movement sequence practice. The result can cause the case child’s attention and learning motivation. And the case child understand what to do to enhance kinesthetic intelligence. These authors hope findings of this study can contribute as reference for the further research on the related topic.

Keywords: asperger symptom, body rhythm, kinesthetic intelligence, space awareness

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Authors: Xin Li, Yan-Rong Guo, Jin-Fang Lin, Yi Feng, Håkan Billig, Ruijin Shao

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Background: Young women with polycystic ovary syndrome (PCOS) have a high risk of developing endometrial carcinoma. There is a need for the development of new medical therapies that can reduce the need for surgical intervention so as to preserve the fertility of these patients. The aim of the study was to describe and discuss cases of PCOS and insulin resistance (IR) women with early endometrial carcinoma while being co-treated with Diane-35 and metformin. Methods: Five PCOS-IR women who were scheduled for diagnosis and therapy for early endometrial carcinoma were recruited. The hospital records and endometrial pathology reports were reviewed. All patients were co-treated with Diane-35 and metformin for 6 months to reverse the endometrial carcinoma and preserve their fertility. Before, during, and after treatment, endometrial biopsies and blood samples were obtained and oral glucose tolerance tests were performed. Endometrial pathology was evaluated. Body weight (BW), body mass index (BMI), follicle-stimulating hormone (FSH), luteinizing hormone (LH), total testosterone (TT), sex hormone-binding globulin (SHBG), free androgen index (FAI), insulin area under curve (IAUC), and homeostasis model assessment of insulin resistance (HOMA-IR) were determined. Results: Clinical stage 1a, low grade endometrial carcinoma was confirmed before treatment. After 6 months of co-treatment, all patients showed normal epithelia. No evidence of atypical hyperplasia or endometrial carcinoma was found. Co-treatment resulted in significant decreases in BW, BMI, TT, FAI, IAUC, and HOMA-IR in parallel with a significant increase in SHBG. There were no differences in the FSH and LH levels after co-treatment. Conclusions: Combined treatment with Diane-35 and metformin has the potential to revert the endometrial carcinoma into normal endometrial cells in PCOS-IR women. The cellular and molecular mechanisms behind this effect merit further investigation.

Keywords: PCOS, progesterone resistance, insulin resistance, steroid hormone receptors, endometrial carcinoma

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Authors: Ibrahim A. Kareem, Sina O. Ayelaagbe

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This study investigated the effects of web-enabled Sculpture package on Colleges of Education students’ psychomotor level in Fine Arts in South-west, Nigeria. The objectives of this study were to: (i) determine the effect of web-enabled Sculpture package on Fine Arts Students’ performance; (ii) find out the effect of ability levels on Fine Arts Students’ performance and (iii) ascertain the interaction effect of treatment and ability levels on Fine Arts Students’ performance. The study was quasi-experimental design. A total of 48 Fine Arts Students participated in the study. There were 26 students in experimental and 22 for the control. The respondents were purposively sampled from Adeyemi College of Education, Ondo and Federal College of Education (Special) Oyo. Sculpture Achievement Test, Sculpture Skill Test and Sculpture ‘on the Spot’ Skill Assessment Instrument were validated by experts while Pearson’s Product Moment Correlation (PPMC) statistics was used to analyse the instrument while the remaining two instruments were subjected to Cronbach alpha statistics. Data were analysed using t-test and ANCOVA were used to test the hypotheses at 0.05 level of significance. The findings of the study revealed that: (i) Fine Arts Students’ in the experimental group performed significantly better than the control group; (ii) there was a significant difference among high, medium and low ability levels mean scores of Fine Arts Students’ performance in Colleges of Education; (iii) there was no significant interaction effect of treatment and ability levels on the mean scores of Fine Arts Students’ performance in Colleges of Education and. The study concluded that Fine Arts Students exposed to web-enabled Sculpture package performed better than those taught using the conventional method. Based on the study it was recommended that lecturers in Colleges of Education should endeavour to adapt and utilise web-enabled Sculpture package for teaching sculpture.

Keywords: fine art, psychomotor, sculpture, web-enabled

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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