Search results for: physiological data extraction
19442 Hearing Aids Maintenance Training for Hearing-Impaired Preschool Children with the Help of Motion Graphic Tools
Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz
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The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.Keywords: hearing aids, hearing aids maintenance skill, hearing impaired children, motion graphics
Procedia PDF Downloads 14819441 Functional Finishing of Organic Cotton Fabric Using Vetiver Root Extract
Authors: Sakeena Naikwadi, K. Jagaluraiah Sannapapamma
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Vetiveria zizanioides is an aromatic grass and traditionally been used in aromatherapy and ayurvedic medicine. Vetiver root is multi-functional biopolymer and has highly aromatic, antimicrobial, UV blocking, antioxidant properties suitable for textile finishing. The vetiver root (Gulabi) powder of different concentration (2, 4, 6,8 percent) were extracted by aqueous and solvent methods subjected to bioassay for antimicrobial efficiency and GCMS spectral analysis. The organic cotton fabric was finished with vetiver root extract (8 percent) by exhaust and pad dry cure methods. The finished fabric was assessed for functional properties viz., UV protective factor, antimicrobial efficiency and aroma intensity. The results revealed that Ethanol extraction showed a greater zone of inhibition compared to aqueous extract in root powder. Among the concentrations, 8 percent root extract in ethanol showed a greater zone of inhibition against gram-positive organism S. aureus and gram-negative organism E. coli. The major compounds present in vetiver root extracts were diethyl pathalate with greater percentage (87.73 %) followed by 7- Isopropyl dimethyl carboxylic acid (4.05 %), 2-butanone 4-trimethyle cyclohexen (1.21 %), phenanthrene carboxylic acid (1.03 %), naphthalene pentanoic acid (0.99 %), 1-phenanthrene carboxylic acid and 1 cyclohexenone 2-methyl oxobuty (0.89 %). The sample finished by pad dry cure method exhibited better UV protection even after 10th wash as compared to exhaust method. Vetiver extract treated samples exhibited maximum zone of inhibition against S. aureus than the E. coli organism. The vetiver root extract treated organic cotton fabric through pad dry cure method possessed good antimicrobial activity against S. aureus and E. coli even after 20th washes compared to vetiver root extract treated by exhaust method. The olfactory analysis was carried out by 30 panels of members and opined that vetiver root extract treated fabric has very good and pleasant aroma with better tactile properties that provide cooling, soothing effect and enhances the mood of the wearer. Vetiver root extract finished organic cotton fabric possessed aroma, antimicrobial and UV properties which are aptly suitable for medical and healthcare textiles viz., wound dressing, bandage gauze, surgical cloths, baby diapers and sanitary napkins. It can be used as after finishing agent for variegated garments and made-ups and can be replaced with commercial after finishing agents.Keywords: antimicrobial, olfactory analysis, UV protection factor, vetiver root extract
Procedia PDF Downloads 22719440 Hedgerow Detection and Characterization Using Very High Spatial Resolution SAR DATA
Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell
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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis
Procedia PDF Downloads 22719439 Variability of Metal Composition and Concentrations in Road Dust in the Urban Environment
Authors: Sandya Mummullage, Prasanna Egodawatta, Ashantha Goonetilleke, Godwin A. Ayoko
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Urban road dust comprises of a range of potentially toxic metal elements and plays a critical role in degrading urban receiving water quality. Hence, assessing the metal composition and concentration in urban road dust is a high priority. This study investigated the variability of metal composition and concentrations in road dust in four different urban land uses in Gold Coast, Australia. Samples from 16 road sites were collected and tested for selected 12 metal species. The data set was analyzed using both univariate and multivariate techniques. Outcomes of the data analysis revealed that the metal concentrations inroad dust differs considerably within and between different land uses. Iron, aluminum, magnesium and zinc are the most abundant in urban land uses. It was also noted that metal species such as titanium, nickel, copper, and zinc have the highest concentrations in industrial land use. The study outcomes revealed that soil and traffic related sources as key sources of metals deposited on road surfaces.Keywords: metals build-up, pollutant accumulation, stormwater quality, urban road dust
Procedia PDF Downloads 28819438 Gc-ms Data Integrated Chemometrics for the Authentication of Vegetable Oil Brands in Minna, Niger State, Nigeria
Authors: Rasaq Bolakale Salau, Maimuna Muhammad Abubakar, Jonathan Yisa, Muhammad Tauheed Bisiriyu, Jimoh Oladejo Tijani, Alexander Ifeanyi Ajai
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Vegetables oils are widely consumed in Nigeria. This has led to competitive manufacture of various oil brands. This leads increasing tendencies for fraud, labelling misinformation and other unwholesome practices. A total of thirty samples including raw and corresponding branded samples of vegetable oils were collected. The Oils were extracted from raw ground nut, soya bean and oil palm fruits. The GC-MS data was subjected to chemometric techniques of PCA and HCA. The SOLO 8.7 version of the standalone chemometrics software developed by Eigenvector research incorporated and powered by PLS Toolbox was used. The GCMS fingerprint gave basis for discrimination as it reveals four predominant but unevenly distributed fatty acids: Hexadecanoic acid methyl ester (10.27- 45.21% PA), 9,12-octadecadienoic acid methyl ester (10.9 - 45.94% PA), 9-octadecenoic acid methyl ester (18.75 - 45.65%PA), and Eicosanoic acid methyl ester (1.19% - 6.29%PA). In PCA modelling, two PCs are retained at cumulative variance captured at 73.15%. The score plots indicated that palm oil brands are most aligned with raw palm oil. PCA loading plot reveals the signature retention times between 4.0 and 6.0 needed for quality assurance and authentication of the oils samples. They are of aromatic hydrocarbons, alcohols and aldehydes functional groups. HCA dendrogram which was modeled using Euclidian distance through Wards method, indicated co-equivalent samples. HCA revealed the pair of raw palm oil brand and palm oil brand in the closest neighbourhood (± 1.62 % A difference) based on variance weighted distance. It showed Palm olein brand to be most authentic. In conclusion, based on the GCMS data with chemometrics, the authenticity of the branded samples is ranked as: Palm oil > Soya oil > groundnut oil.Keywords: vegetable oil, authenticity, chemometrics, PCA, HCA, GC-MS
Procedia PDF Downloads 1219437 The Impact of Professional Development in the Area of Technology Enhanced Learning on Higher Education Teaching Practices Across Atlantic Technological University – Research Methodology and Preliminary Findings
Authors: Annette Cosgrove
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The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitisation of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence based digital teaching model for use in a future pandemic. The research strategy undertaken for this PhD Study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially , feedback collected and the research instrument was edited to reflect this feedback, before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioners views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology enhanced learning and on teaching practice in a higher education institution.’ The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice . This study includes quantitative and qualitative methods to elicit data which will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments / data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers.. This research is currently being conducted across the ATU multisite campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a west of Ireland university is the focus of the study , The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi- formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning . This paper will present initial findings, reflections and data from this ongoing research study.Keywords: TEL, DTL, digital teaching, digital assessment
Procedia PDF Downloads 5719436 Healthcare Workers' Attitudes Towards People Living With Hiv And Drug Users
Authors: Delband Yekta Moazami
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Background: For proper care and treatment of HIV patients and drug users, the medical staff and physicians must have a correct and positive attitude and knowledge towards such patients. We aimed to assess the attitudes in a sample of health care workers (HCW) working in different hospitals and clinics and medical students in Georgia towards HIV infected people and drug users in Tbilisi. Method: We conducted a cross-sectional study to assess attitudes of health care workers towards people living with HIV and drug users in hospitals and clinics in Tbilisi. The study was carried out from 1st of May 2020 till 30th of September 2020. Data were collected using a self-administered structured online questionnaire. With this tool we evaluated four facets of attitudes: Discrimination, Acceptance of HIV/AIDS patients, Acceptance of drug users and Fear. All data were imported and analyzed with the software SPSS 22 for windows. Results: In total data was collected from168 respondents, that among them 107 (65%) were women and majority of the participants were medical doctors. Women had more acceptance attitudes rather than men towards drug abusers. We found significant differences regarding expressing negative attitudes among HCW who were more than 50 years old comparing with other age groups in all four aspects. Medical doctors expressed more acceptances towards people with HIV and drug users comparing two other groups. Also our study revealed that the group with working experience 21 years and more, showed more discriminatory attitudes comparing other groups. Conclusion: Based on our study findings, there are significant differences regarding respondent’s attitudes based on gender, medical specialty and working experience in health care system. People struggling with HIV and drug use need nonjudgmental and positive behaviors from health care workers and physicians in order to help them for harm reduction and receiving appropriate treatment.Keywords: hiv, addiction, attitudes, healthcare workers
Procedia PDF Downloads 7419435 Affective Attributes and Second Language Performance of Third Year Maritime Students: A Teacher's Compass
Authors: Sonia Pajaron, Flaviano Sentina, Ranulfo Etulle
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Learning a second language calls for a total commitment from the learner whose response is necessary to successfully send and receive linguistic messages. It is relevant to virtually every aspect of human behaviour which is even more challenging when the components on -affective domains- are involved in second language learning. This study investigated the association between the identified affective attributes and second language performance of the one hundred seventeen (117) randomly selected third year maritime students. A descriptive-correlational method was utilized to generate data on their affective attributes while composition writing (2 series) and IELTS-based interview was done for speaking test. Additionally, to establish the respondents’ English language profile, data on their high school grades (GPA), entrance exam results in English subject (written) as well as in the interview was extracted as baseline information. Data were subjected to various statistical treatment (average means, percentages and pearson-r moment coefficient correlation) and found out that, Nautical Science and Marine Engineering students were found to have average high school grade, entrance test results, both written and in the interview turned out to be very satisfactory at 50% passing percentage. Varied results were manifested in their affective attributes towards learning the second language. On attitude, nautical science students had true positive attitude while marine engineering had only a moderate positive one. Secondly, the former were positively motivated to learn English while the latter were just moderately motivated. As regards anxiety, both groups embodied a moderate level of anxiety in the English language. Finally, data showed that nautical science students exuded real confidence while the marine engineering group had only moderate confidence with the second language. Respondents’ English academic achievement (GWA) was significantly correlated with confidence and speaking with anxiety towards the second language among the students from the nautical science group with moderate positive and low negative degree of correlation, respectively. On the other hand, the marine engineering students’ speaking test result was significantly correlated with anxiety and self-confidence with a moderate negative and low positive degree of correlation, respectively while writing was significantly correlated with motivation bearing a low positive degree of correlation.Keywords: affective attributes, second language, second language performance, anxiety, attitude, self-confidence and motivation
Procedia PDF Downloads 26319434 Do the Health Benefits of Oil-Led Economic Development Outweigh the Potential Health Harms from Environmental Pollution in Nigeria?
Authors: Marian Emmanuel Okon
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Introduction: The Niger Delta region of Nigeria has a vast reserve of oil and gas, which has globally positioned the nation as the sixth largest exporter of crude oil. Production rapidly rose following oil discovery. In most oil producing nations of the world, the wealth generated from oil production and export has propelled economic advancement, enabling the development of industries and other relevant infrastructures. Therefore, it can be assumed that majority of the oil resource such as Nigeria’s, has the potential to improve the health of the population via job creation and derived revenues. However, the health benefits of this economic development might be offset by the environmental consequences of oil exploitation and production. Objective: This research aims to evaluate the balance between the health benefits of oil-led economic development and harmful environmental consequences of crude oil exploitation in Nigeria. Study Design: A pathway has been designed to guide data search and this study. The model created will assess the relationship between oil-led economic development and population health development via job creation, improvement of education, development of infrastructure and other forms of development as well as through harmful environmental consequences from oil activities. Data/Emerging Findings: Diverse potentially suitable datasets which are at different geographical scales have been identified, obtained or applied for and the dataset from the World Bank has been the most thoroughly explored. This large dataset contains information that would enable the longitudinal assessment of both the health benefits and harms from oil exploitation in Nigeria as well as identify the disparities that exist between the communities, states and regions. However, these data do not extend far back enough in time to capture the start of crude oil production. Thus, it is possible that the maximum economic benefits and health harms could be missed. To deal with this shortcoming, the potential for a comparative study with countries like United Kingdom, Morocco and Cote D’ivoire has also been taken into consideration, so as to evaluate the differences between these countries as well as identify the areas of improvement in Nigeria’s environmental and health policies. Notwithstanding, these data have shown some differences in each country’s economic, environmental and health state over time as well as a corresponding summary statistics. Conclusion: In theory, the beneficial effects of oil exploitation to the health of the population may be substantial as large swaths of the ‘wider determinants’ of population heath are influenced by the wealth of a nation. However, if uncontrolled, the consequences from environmental pollution and degradation may outweigh these benefits. Thus, there is a need to address this, in order to improve environmental and population health in Nigeria.Keywords: environmental pollution, health benefits, oil-led economic development, petroleum exploitation
Procedia PDF Downloads 32919433 Routing and Energy Efficiency through Data Coupled Clustering in Large Scale Wireless Sensor Networks (WSNs)
Authors: Jainendra Singh, Zaheeruddin
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A typical wireless sensor networks (WSNs) consists of several tiny and low-power sensors which use radio frequency to perform distributed sensing tasks. The longevity of wireless sensor networks (WSNs) is a major issue that impacts the application of such networks. While routing protocols are striving to save energy by acting on sensor nodes, recent studies show that network lifetime can be enhanced by further involving sink mobility. A common approach for energy efficiency is partitioning the network into clusters with correlated data, where the representative nodes simply transmit or average measurements inside the cluster. In this paper, we propose an energy- efficient homogenous clustering (EHC) technique. In this technique, the decision of each sensor is based on their residual energy and an estimate of how many of its neighboring cluster heads (CHs) will benefit from it being a CH. We, also explore the routing algorithm in clustered WSNs. We show that the proposed schemes significantly outperform current approaches in terms of packet delay, hop count and energy consumption of WSNs.Keywords: wireless sensor network, energy efficiency, clustering, routing
Procedia PDF Downloads 25619432 Patterns of Gear Substitution in Norwegian Trawl Fishery
Authors: Tannaz Alizadeh Ashrafi
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Seasonal variability in biological and ecological factors together with relevant socio-economic determinants affect the choice of fishing gear, frequency of its usage and decision about gear conversion under multi-species situation. In order to deal with the complex dynamics of fisheries, fishers, constantly, have to make decisions about how long to fish, when to go fishing, what species to target, and which gear to deploy. In this regard, the purpose of this study is to examine the dynamics of gear/ species combination in Norwegian fishery. A comprehensive vessel-level set of data for the main economically important species including: cod, haddock, saithe, shrimp and mixed catch have been obtained from the Norwegian Directorate of Fisheries covering the daily data in 2010. The present study further analyzes the level of flexibility and rationality of the fishers operating in the trawl fishery. The results show the disproportion between intention of the trawl fishers to maximize profitability of each fishing trip and their harvesting behavior in reality. Discussion is based on so-called maximizing behavior.Keywords: trawl fishery, gear substitution, rationality, profit maximizing behavior
Procedia PDF Downloads 27019431 The Effect of Parents and Coaches on Preschool Children's Self-Control in Preschool Centers in District 5 of Tehran
Authors: Alieh Arasteh
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The main purpose of this study was to investigate the effect of parents and educators on the self-control of children in pre-primary schools in District 5 of Tehran. The method of this survey was a survey and post-correlation type. The statistical population of this study included all teachers and parents of children in preschool centers in the region. The 5th city of Tehran in 1397 was the number of kindergartens in 117 centers and the number of parents was 1872, the sample size of the parents was 320 and the sample size of the trainers was 76. The method of sampling in this study was randomized and clustered. The data gathering tool was Rosenbaum and Ronen (1992) self-control skills, a five-factor questionnaire NEO personality Costa and McCrae (1985) and a questionnaire on demographic characteristics, reliability using Cronbach's alpha, the data analysis was performed using the software spss24. The results of the research showed that the personality characteristics of parents, parents' socioeconomic status and personality traits of educators affect the self-control dimensions of pre-primary school children (P <0.05).Keywords: self-control, pre-primary school, the effect of parents, couches
Procedia PDF Downloads 16919430 The Composition of Biooil during Biomass Pyrolysis at Various Temperatures
Authors: Zoltan Sebestyen, Eszter Barta-Rajnai, Emma Jakab, Zsuzsanna Czegeny
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Extraction of the energy content of lignocellulosic biomass is one of the possible pathways to reduce the greenhouse gas emission derived from the burning of the fossil fuels. The application of the bioenergy can mitigate the energy dependency of a country from the foreign natural gas and the petroleum. The diversity of the plant materials makes difficult the utilization of the raw biomass in power plants. This problem can be overcome by the application of thermochemical techniques. Pyrolysis is the thermal decomposition of the raw materials under inert atmosphere at high temperatures, which produces pyrolysis gas, biooil and charcoal. The energy content of these products can be exploited by further utilization. The differences in the chemical and physical properties of the raw biomass materials can be reduced by the use of torrefaction. Torrefaction is a promising mild thermal pretreatment method performed at temperatures between 200 and 300 °C in an inert atmosphere. The goal of the pretreatment from a chemical point of view is the removal of water and the acidic groups of hemicelluloses or the whole hemicellulose fraction with minor degradation of cellulose and lignin in the biomass. Thus, the stability of biomass against biodegradation increases, while its energy density increases. The volume of the raw materials decreases so the expenses of the transportation and the storage are reduced as well. Biooil is the major product during pyrolysis and an important by-product during torrefaction of biomass. The composition of biooil mostly depends on the quality of the raw materials and the applied temperature. In this work, thermoanalytical techniques have been used to study the qualitative and quantitative composition of the pyrolysis and torrefaction oils of a woody (black locust) and two herbaceous samples (rape straw and wheat straw). The biooil contains C5 and C6 anhydrosugar molecules, as well as aromatic compounds originating from hemicellulose, cellulose, and lignin, respectively. In this study, special emphasis was placed on the formation of the lignin monomeric products. The structure of the lignin fraction is different in the wood and in the herbaceous plants. According to the thermoanalytical studies the decomposition of lignin starts above 200 °C and ends at about 500 °C. The lignin monomers are present among the components of the torrefaction oil even at relatively low temperatures. We established that the concentration and the composition of the lignin products vary significantly with the applied temperature indicating that different decomposition mechanisms dominate at low and high temperatures. The evolutions of decomposition products as well as the thermal stability of the samples were measured by thermogravimetry/mass spectrometry (TG/MS). The differences in the structure of the lignin products of woody and herbaceous samples were characterized by the method of pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). As a statistical method, principal component analysis (PCA) has been used to find correlation between the composition of lignin products of the biooil and the applied temperatures.Keywords: pyrolysis, torrefaction, biooil, lignin
Procedia PDF Downloads 32019429 The Effects of Siltation in Seagrass along Claver Surigao Del Norte
Authors: Dawn Rosarie M. Fajardo
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Seagrass plays a crucial role in sustaining marine ecosystem. In this investigation two areas (Panyug and Kinalablaban) were studied to assess the effect of siltation in seagrass condition. The size of the sediment was also examined. Data analysis showed that Panyug had higher level of silt compared to Kinalablaban. The results indicate that seagrass is vulnerable to environmental disturbances. The results also indicate that plants grown in undisturbed natural sediments were more successful than plants in sediments which were disturbed. In addition to that, there are total of seven species of seagrass that are found tolerant with siltation it includes Enhalus acoroides, Cymodocea rotundata, Halophila minor, Halodule pinifolia, Halodule uninervis, Syringodium isoetifolium, and Thalassia hemprichii. The results were given emphasis especially for the five representative quadrats in each area. Among these species of seagrass Cymodocea rotundata is the most tolerant to siltation. There is also no significant relationships between silt and seagrass percent cover which had r² = 0.192, Panyug and r² = 0.145, at Kinalablaban at P> 0.05. The data showed that Panyug (area 1) was characterized with high level of silt compared to that of Kinalablaban that contains more granulated sediments.Keywords: seagrass, siltation, cymodocea rotundata, sediments, environmental issues
Procedia PDF Downloads 52719428 Relevance of Dosing Time for Everolimus Toxicity on Thyroid Gland and Hormones in Mice
Authors: Dilek Ozturk, Narin Ozturk, Zeliha Pala Kara, Engin Kaptan, Serap Sancar Bas, Nurten Ozsoy, Alper Okyar
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Most physiological processes oscillate in a rhythmic manner in mammals including metabolism and energy homeostasis, locomotor activity, hormone secretion, immune and endocrine system functions. Endocrine body rhythms are tightly regulated by the circadian timing system. The hypothalamic-pituitary-thyroid (HPT) axis is under circadian control at multiple levels from hypothalamus to thyroid gland. Since circadian timing system controls a variety of biological functions in mammals, circadian rhythms of biological functions may modify the drug tolerability/toxicity depending on the dosing time. Selective mTOR (mammalian target of rapamycin) inhibitor everolimus is an immunosuppressant and anticancer agent that is active against many cancers. It was also found to be active in medullary thyroid cancer. The aim of this study was to investigate the dosing time-dependent toxicity of everolimus on the thyroid gland and hormones in mice. Healthy C57BL/6J mice were synchronized with 12h:12h Light-Dark cycle (LD12:12, with Zeitgeber Time 0 – ZT0 – corresponding to Light onset). Everolimus was administered to male (5 mg/kg/day) and female mice (15 mg/kg/day) orally at ZT1-rest period- and ZT13-activity period- for 4 weeks; body weight loss, clinical signs and possible changes in serum thyroid hormone levels (TSH and free T4) were examined. Histological alterations in the thyroid gland were evaluated according to the following criteria: follicular size, colloid density and viscidity, height of the follicular epithelium and the presence of necrotic cells. The statistical significance between differences was analyzed with ANOVA. Study findings included everolimus-related diarrhea, decreased activity, decreased body weight gains, alterations in serum TSH levels, and histopathological changes in thyroid gland. Decreases in mean body weight gains were more evident in mice treated at ZT1 as compared to ZT13 (p < 0.001, for both sexes). Control tissue sections of thyroid glands exhibited well-organized histoarchitecture when compared to everolimus-treated groups. Everolimus caused histopathological alterations in thyroid glands in male (5 mg/kg, slightly) and female mice (15 mg/kg; p < 0.01 for both ZT as compared to their controls) irrespective of dosing-time. TSH levels were slightly decreased upon everolimus treatment at ZT13 in both males and females. Conversely, increases in TSH levels were observed when everolimus treated at ZT1 in both males (5 mg/kg; p < 0.05) and females (15 mg/kg; slightly). No statistically significant alterations in serum free T4 levels were observed. TSH and free T4 is clinically important thyroid hormones since a number of disease states have been linked to alterations in these hormones. Serum free T4 levels within the normal ranges in the presence of abnormal serum TSH levels in everolimus treated mice may suggest subclinical thyroid disease which may have repercussions on the cardiovascular system, as well as on other organs and systems. Our study has revealed the histological damage on thyroid gland induced by subacute everolimus administration, this effect was irrespective of dosing time. However, based on the body weight changes and clinical signs upon everolimus treatment, tolerability for the drug was best following dosing at ZT13 in both male and females. Yet, effects of everolimus on thyroid functions may deserve further studies regarding their clinical importance and chronotoxicity.Keywords: circadian rhythm, chronotoxicity, everolimus, thyroid gland, thyroid hormones
Procedia PDF Downloads 34619427 Weighted Rank Regression with Adaptive Penalty Function
Authors: Kang-Mo Jung
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The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression
Procedia PDF Downloads 45719426 Impact of Maternal Nutrition on Newborn Anthropometry and Hemoglobin
Authors: Vinay Mishra, Meena Malkani
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Objectives: To study the effect of physical maternal nutritional markers (viz. weight, height, gestational weight gain, BMI) and third-trimester haemoglobin concentration on anthropometry and cord blood haemoglobin of their newborn. Methods: Study area: Post-natal ward of a tertiary care hospital in an urban area. Study population: All post-partum women and their newborns. Sample size: 100. Maternal and neonatal data and anthropometric measurements were recorded in semi-structured case proforma. Data analysis: The data obtained was analysed using SPSS 20 software.The comparison between the groups was done using One-Way Analysis of Variance for two groups. For more than two groups comparisons further posthoc analysis was done using Tukey test. Pearson correlation coefficient was used for correlating the variables. A P value less than 0.05 was considered significant. Results: 1. Out of the 100 studied mothers, 52% were anaemic. 2. Cord blood haemoglobin values decreased significantly with the order of birth. 3. Cord blood haemoglobin of normal-weight newborns is significantly higher as compared to that of LBW newborns. 4. Cord blood haemoglobin has strong statistical significance with maternal anaemia. 5. Pre-pregnancy weight and gestational weight gain significantly influence the neonates anthropometry. Conclusions: 1. Birth order has a prominent inverse effect on the cord blood haemoglobin. 2. Majority of the expectant mothers are anaemic and give birth to LBW babies with reduced anthropometric markers. 3. Pre-pregnancy weight, height and gestational weight gain has a very significant impact on the neonatal anthropometry. 4. Thus, maternal nutrition during gestation and during the crucial periods of growth in the pre-child bearing age group has a very significant impact on foetal development.Keywords: maternal nutrition, anthropometry, cord blood hemoglobin, newborn
Procedia PDF Downloads 38719425 Organic Facies Classification, Distribution, and Their Geochemical Characteristics in Sirt Basin, Libya
Authors: Khaled Albriki, Feiyu Wang
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The failed rifted epicratonic Sirt basin is located in the northern margin of the African Plate with an area of approximately 600,000 km2. The organofacies' classification, characterization, and its distribution vertically and horizontally are carried out in 7 main troughs with 32 typical selected wells. 7 geological and geochemical cross sections including Rock-Eval data and % TOC data are considered in order to analyze and to characterize the main organofacies with respect to their geochemical and geological controls and also to remove the ambiguity behind the complexity of the orgnofacies types and distributions in the basin troughs from where the oil and gas are generated and migrated. This study confirmes that there are four different classical types of organofacies distributed in Sirt basin F, D/E, C, and B. these four clasical types of organofacies controls the type and amount of the hydrocarbon discovered in Sirt basin. Oil bulk property data from more than 20 oil and gas fields indicate that D/E organoface are significant oil and gas contributors similar to B organoface. In the western Sirt basin in Zallah-Dur Al Abd, Hagfa, Kotla, and Dur Atallha troughs, F organoface is identified for Etel formation, Kalash formation and Hagfa formation having % TOC < 0.6, whereas the good quality D/E and B organofacies present in Rachmat formation and Sirte shale formation both have % TOC > 1.1. Results from the deepest trough (Ajdabiya), Etel (Gas pron in Whadyat trough), Kalash, and Hagfa constitute F organofacies, mainly. The Rachmat and Sirt shale both have D/E to B organofacies with % TOC > 1.2, thus indicating the best organofacies quality in Ajdabiya trough. In Maragh trough, results show that Etel F organofacies and D/E, C to B organofacies related to Middle Nubian, Rachmat, and Sirte shale have %TOC > 0.66. Towards the eastern Sirt basin, in troughs (Hameimat, Faregh, and Sarir), results show that the Middle Nubian, Etel, Rachmat, and Sirte shales are strongly dominated by D/E, C to B (% TOC > 0.75) organofacies.Keywords: Etel, Mid-Nubian, organic facies, Rachmat, Sirt basin, Sirte shale
Procedia PDF Downloads 12419424 Seal Capacity Evaluation by Using Mercury Injection Capillary Pressure Method Integrated with Petrographic Data: A Case Study in Green Dragon Oilfield Offshore Vietnam
Authors: Quoc Ngoc Phan, Hieu Van Nguyen, Minh Hong Nguyen
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This study presents an integrated approach using Mercury Injection Capillary Pressure (MICP) and petrographic analysis to assess the seal quality of the inter-bedded shale formations which are considered the intra-formation top seals of hydrocarbon bearing zones in Green Dragon structure. Based on the hydrocarbon column height (HCH) at leak point derived from capillary pressure data, four seal types were identified. Furthermore, the results of scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were interpreted to clarify the influence of clay minerals on seal capacity. The result of the study indicated that the inter-bedded shale formations are the good sealing quality with a majority of analyzed samples ranked type A and B seals in the sample set. Both seal types occurred mainly in mudstones with pore radius estimated less than 0.251 µm. Overall, type A and B seals contained a large amount of authigenic clay minerals such as illite, chlorite which showed the complexity of morphological arrangement in pore space. Conversely, the least common seal type C and D were presented in moderately compacted sandstones with more open pore radius. It is noticeable that there was a reduction of illite and chlorite in clay mineral fraction of these seal type. It is expected that the integrated analysis approach using Mercury Injection Capillary Pressure and petrographic data employed in this study can be applied to assess the sealing quality of future well sites in Green Dragon or other structures.Keywords: seal capacity, hydrocarbon height column, seal type, SEM, XRD
Procedia PDF Downloads 15519423 Intelligent Earthquake Prediction System Based On Neural Network
Authors: Emad Amar, Tawfik Khattab, Fatma Zada
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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.Keywords: BP neural network, prediction, RBF neural network, earthquake
Procedia PDF Downloads 49119422 Multi-Labeled Aromatic Medicinal Plant Image Classification Using Deep Learning
Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih
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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network
Procedia PDF Downloads 17519421 Comparative Analysis of Pet-parent Reported Pruritic Symptoms in Cats: Data from Social Media Listening and Surveys Similar
Authors: Georgina Cherry, Taranpreet Rai, Luke Boyden, Sitira Williams, Andrea Wright, Richard Brown, Viva Chu, Alasdair Cook, Kevin Wells
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Estimating population-level burden, abilities of pet-parents to identify disease and demand for veterinary services worldwide is challenging. The purpose of this study is to compare a feline pruritus survey with social media listening (SML) data discussing this condition. Surveys are expensive and labour intensive to analyse, but SML data is freeform and requires careful filtering for relevancy. This study considers data from a survey of owner-observed symptoms of 156 pruritic cats conducted using Pet Parade® and SML posts collected through web-scraping to gain insights into the characterisation and management of feline pruritus. SML posts meeting a feline body area, behaviour and symptom were captured and reviewed for relevance representing 1299 public posts collected from 2021 to 2023. The survey involved 1067 pet-parents who reported on pruritic symptoms in their cats. Among the observed cats, approximately 18.37% (n=196) exhibited at least one symptom. The most frequently reported symptoms were hair loss (9.2%), bald spots (7.3%) and infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin (8.2%). Notably, bald spots were the primary symptom reported for short-haired cats, while other symptoms were more prevalent in medium and long-haired cats. Affected body areas, according to pet-parents, were primarily the head, face, chin, neck (27%), and the top of the body, along the spine (22%). 35% of all cats displayed excessive behaviours consistent with pruritic skin disease. Interestingly, 27% of these cats were perceived as non-symptomatic by their owners, suggesting an under-identification of itch-related signs. Furthermore, a significant proportion of symptomatic cats did not receive any skin disease medication, whether prescribed or over the counter (n=41). These findings indicate a higher incidence of pruritic skin disease in cats than recognized by pet owners, potentially leading to a lack of medical intervention for clinically symptomatic cases. The comparison between the survey and social media listening data revealed bald spots were reported in similar proportions in both datasets (25% in the survey and 28% in SML). Infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin accounted for 31% of symptoms in the survey, whereas it represented 53% of relevant SML posts (excluding bumpy skin). Abnormal licking or chewing behaviours were mentioned by pet-parents in 40% of SML posts compared to 38% in the survey. The consistency in the findings of these two disparate data sources, including a complete overlap in affected body areas for the top 80% of social media listening posts, indicates minimal biases in each method, as significant biases would likely yield divergent results. Therefore, the strong agreement across pruritic symptoms, affected body areas, and reported behaviours enhances our confidence in the reliability of the findings. Moreover, the small differences identified between the datasets underscore the valuable insights that arise from utilising multiple data sources. These variations provide additional depth in characterising and managing feline pruritus, allowing for more comprehensive understanding of the condition. By combining survey data and social media listening, researchers can obtain a nuanced perspective and capture a wider range of experiences and perspectives, supporting informed decision-making in veterinary practice.Keywords: social media listening, feline pruritus, surveys, felines, cats, pet owners
Procedia PDF Downloads 11919420 Hybrid Wavelet-Adaptive Neuro-Fuzzy Inference System Model for a Greenhouse Energy Demand Prediction
Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani
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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse
Procedia PDF Downloads 7819419 Structural Barriers to Voting among Young Voters: an Intersectional Approach
Authors: Ryo Sato
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The United States and many other countries witness alarmingly low voting rates among youths, skewing democratic representation. Many scholars and pundits have ascribed to this trend young voters' laziness, indifference, and self-centeredness and placed blame on them. However, a growing body of research is focusing on structural barriers to voting, which are defined as built-in obstacles lying in electoral laws and procedures. Drawing on national survey data from 891 young adults in 2020 and extant literature on structural barriers to voting, the project aims to develop a framework for analyzing systematic obstacles to voting experienced by young people and offer tangible policy recommendations. The preliminary findings presented at this conference include an intersectional analysis of the survey data, focusing on how different social categories — race, gender, socioeconomic status, immigration status, and others — in combination create unique voting experiences and barriers. This project offers a critical framework to combat the individualized understanding of low voting rates among youths and inform pathways to functional democracy.Keywords: youth voting behavior, structural barriers, intersectionality, democratic participation, S
Procedia PDF Downloads 5219418 Explanatory Variables for Crash Injury Risk Analysis
Authors: Guilhermina Torrao
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An extensive number of studies have been conducted to determine the factors which influence crash injury risk (CIR); however, uncertainties inherent to selected variables have been neglected. A review of existing literature is required to not only obtain an overview of the variables and measures but also ascertain the implications when comparing studies without a systematic view of variable taxonomy. Therefore, the aim of this literature review is to examine and report on peer-reviewed studies in the field of crash analysis and to understand the implications of broad variations in variable selection in CIR analysis. The objective of this study is to demonstrate the variance in variable selection and classification when modeling injury risk involving occupants of light vehicles by presenting an analytical review of the literature. Based on data collected from 64 journal publications reported over the past 21 years, the analytical review discusses the variables selected by each study across an organized list of predictors for CIR analysis and provides a better understanding of the contribution of accident and vehicle factors to injuries acquired by occupants of light vehicles. A cross-comparison analysis demonstrates that almost half the studies (48%) did not consider vehicle design specifications (e.g., vehicle weight), whereas, for those that did, the vehicle age/model year was the most selected explanatory variable used by 41% of the literature studies. For those studies that included speed risk factor in their analyses, the majority (64%) used the legal speed limit data as a ‘proxy’ of vehicle speed at the moment of a crash, imposing limitations for CIR analysis and modeling. Despite the proven efficiency of airbags in minimizing injury impact following a crash, only 22% of studies included airbag deployment data. A major contribution of this study is to highlight the uncertainty linked to explanatory variable selection and identify opportunities for improvements when performing future studies in the field of road injuries.Keywords: crash, exploratory, injury, risk, variables, vehicle
Procedia PDF Downloads 12419417 Factors Related with Self-Care Behaviors among Iranian Type 2 Diabetic Patients: An Application of Health Belief Model
Authors: Ali Soroush, Mehdi Mirzaei Alavijeh, Touraj Ahmadi Jouybari, Fazel Zinat-Motlagh, Abbas Aghaei, Mari Ataee
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Diabetes is a disease with long cardiovascular, renal, ophthalmic and neural complications. It is prevalent all around the world including Iran, and its prevalence is increasing. The aim of this study was to determine the factors related to self-care behavior based on health belief model among sample of Iranian diabetic patients. This cross-sectional study was conducted among 301 type 2 diabetic patients in Gachsaran, Iran. Data collection was based on an interview and the data were analyzed by SPSS version 20 using ANOVA, t-tests, Pearson correlation, and linear regression statistical tests at 95% significant level. Linear regression analyses showed the health belief model variables accounted for 29% of the variation in self-care behavior; and perceived severity and perceived self-efficacy are more influential predictors on self-care behavior among diabetic patients.Keywords: diabetes, patients, self-care behaviors, health belief model
Procedia PDF Downloads 46319416 Coronavirus Academic Paper Sorting Application
Authors: Christina A. van Hal, Xiaoqian Jiang, Luyao Chen, Yan Chu, Robert D. Jolly, Yaobin Lin, Jitian Zhao, Kang Lin Hsieh
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The COVID-19 Literature Summary App was created for the primary purpose of enabling academicians and clinicians to quickly sort through the vast array of recent coronavirus publications by topics of interest. Multiple methods of summarizing and sorting the manuscripts were created. A summary page introduces the application function and capabilities, while an interactive map provides daily updates on infection, death, and recovery rates. A page with a pivot table allows publication sorting by topic, with an interactive data table that allows sorting topics by columns, as wells as the capability to view abstracts. Additionally, publications may be sorted by the medical topics they cover. We used the CORD-19 database to compile lists of publications. The data table can sort binary variables, allowing the user to pick desired publication topics, such as papers that describe COVID-19 symptoms. The application is primarily designed for use by researchers but can be used by anybody who wants a faster and more efficient means of locating papers of interest.Keywords: COVID-19, literature summary, information retrieval, Snorkel
Procedia PDF Downloads 14719415 Assessment of Impact of Manpower Training and Development in the Construction Industry
Authors: Olalekan Bamidele Aruleba
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This research assessed the impact of manpower training and development in the construction industry. The aim is to determine the effect of training and development on employees for effective organizational growth in the construction industry to identify the training method for each category of employee in the construction industry, challenges to training and development of workers in the construction industry and impact of manpower training and development on employees and employers. Data for the study were obtained through a well-structured questionnaire administered to building professionals in Nigeria construction firm. Eighty (80) questionnaires were distributed among building professionals in three selected local governments within Ondo State and sixty-four (64) were returned. Data collected were analysed using descriptive statistics and ranking. Findings of the study revealed that in house training and in-service training methods were preferred by most construction industry. It concluded that the attitude of top management and lack of fund was seen as the significant challenges militating against training of employees. The study recommended that manpower training and development must be sustained by all stakeholders in the industry in order to improve workers' productivity; the organization should adopt the right method in training each category of employees and carry out the need assessment for training to avoid training wrong employees.Keywords: construction, development, manpower, training
Procedia PDF Downloads 21819414 A Structuring and Classification Method for Assigning Application Areas to Suitable Digital Factory Models
Authors: R. Hellmuth
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The method of factory planning has changed a lot, especially when it is about planning the factory building itself. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity and Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Furthermore, digital building models are increasingly being used in factories to support facility management and manufacturing processes. The main research question of this paper is, therefore: What kind of digital factory model is suitable for the different areas of application during the operation of a factory? First, different types of digital factory models are investigated, and their properties and usabilities for use cases are analysed. Within the scope of investigation are point cloud models, building information models, photogrammetry models, and these enriched with sensor data are examined. It is investigated which digital models allow a simple integration of sensor data and where the differences are. Subsequently, possible application areas of digital factory models are determined by means of a survey and the respective digital factory models are assigned to the application areas. Finally, an application case from maintenance is selected and implemented with the help of the appropriate digital factory model. It is shown how a completely digitalized maintenance process can be supported by a digital factory model by providing information. Among other purposes, the digital factory model is used for indoor navigation, information provision, and display of sensor data. In summary, the paper shows a structuring of digital factory models that concentrates on the geometric representation of a factory building and its technical facilities. A practical application case is shown and implemented. Thus, the systematic selection of digital factory models with the corresponding application cases is evaluated.Keywords: building information modeling, digital factory model, factory planning, maintenance
Procedia PDF Downloads 10319413 Development of an Artificial Neural Network to Measure Science Literacy Leveraging Neuroscience
Authors: Amanda Kavner, Richard Lamb
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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience
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