Search results for: learning goal orientation

Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

Procedia PDF Downloads 95

Authors: N. Schneider, M. Bruchhage, M. Hartweg, G. Mutungi, J. O Regan, S. Deoni

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Observational neuroimaging studies suggest differences between breast-fed and formula-fed infants in developmental myelination, a key brain process for learning and cognitive development. However, the possible effects of a nutrient formulation on myelin development in healthy term infants in an intervention study have not been investigated. Objective was, therefore, to investigate the efficacy of a nutrient formulation with higher levels of myelin-relevant nutrients as compared to a control formulation with lower levels of the same nutrients on brain myelination and cognitive development in the first 6 months of life. The study is an ongoing randomized, controlled, double-blind, two-center, parallel-group clinical trial with a nonrandomized, non-blinded arm of exclusively breastfed infants. The current findings result from a staged statistical analysis at 6 months; the recruitment and intervention period has been completed for all participants. Follow-up visits at 12, 18 and 24 months are still ongoing. N= 81 enrolled full term, neurotypical infants of both sexes were randomized into either the investigational (N= 42) or the control group (N= 39), and N= 108 children in the breast-fed arm served as a natural reference group. The effect of a blend of docosahexaenoic acid, arachidonic acid, iron, vitamin B12, folic acid as well as sphingomyelin from a uniquely proceed whey protein concentrate enriched in alpha-lactalbumin and phospholipids in an infant nutrition product matrix was investigated. The main outcomes for the staged statistical analyses at 6 months included brain myelination measures derived from MRI. Additional outcomes were brain volume, cognitive development and safety. The full analyses set at 6 months comprised N= 66 infants. Higher levels of myelin-relevant nutrients compared to lower levels resulted in significant differences in myelin structure, volume, and rate of myelination as early as 3 and 6 months of life. The cross-sectional change of means between groups for whole-brain myelin volume was 8.4% for investigational versus control formulation (3.5% versus the breastfeeding reference) group at 3 months and increased to 36.4% for investigational versus control formulation (14.1% versus breastfeeding reference) at 6 months. No statistically significant differences were detected for early cognition scores. Safety findings were largely similar across groups. This is the first pediatric nutritional neuroimaging study demonstrating the efficacy of a myelin nutrient blend on developmental myelination in well-nourished term infants. Myelination is a critical process in learning and development. The effects were demonstrated across the brain, particularly in temporal and parietal regions, known to be functionally involved in sensory, motor and language skills. These first results add to the field of nutritional neuroscience by demonstrating early life nutrition benefits for brain architecture which may be foundational for later cognitive and behavioral outcomes. ClinicalTrials.gov Identifier: NCT03111927 (Infant Nutrition and Brain Development - Full-Text View - ClinicalTrials.gov).

Keywords: brain development, infant nutrition, MRI, myelination

Procedia PDF Downloads 202

Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

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This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

Procedia PDF Downloads 359

Authors: Nattamon Srithammee, Ratchanikorn Chonchaiya

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This study explores the impact of Augmented Reality (AR) technology on mathematics education, focusing on Area and Volume concepts at Phra Dabos School in Thailand. We developed a mobile augmented reality application to present these mathematical concepts innovatively. Using a mixed-methods approach, we assessed the knowledge of 79 students before and after using the application. The results showed a significant improvement in students' understanding of Area and Volume, with average test scores increasing from 3.70 to 9.04 (p < 0.001, Cohen's d = 2.05). Students also reported increased engagement and satisfaction. Our findings suggest that augmented reality technology can be a valuable tool in mathematics education, particularly for enhancing the understanding of abstract concepts like Area and Volume. This study contributes to research on educational technology in STEM education and provides insights for educators and educational technology developers.

Keywords: augmented reality, mathematics education, area and volume, educational technology, STEM education

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Authors: Natasha Yasmin Felles, Gerard Riley

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Background and Aims: Relationship breakdown is typical when one partner lives with an acquired brain injury caused by issues like a stroke. Research has found that the perception of relationship satisfaction decreases following such an injury among non-injured partners. Non-injured partners also are found to experience caregiver stress/burden as they immediately have to take the role of a caregiver along with being a partner of the injured. Research has also found that the perception of a continuous relationship, i.e. the perception of the relationship to be essentially the same as it was before the injury, also changes among those caregiving partners. However, there is a lack of available intervention strategies that can help those partners with both individual and relationship difficulties. The aim of this case study was to conduct a pilot test of an intervention aimed to explore whether it is possible to support a partner to experience greater continuity within the relationship poststroke, and what benefits such a change might have. Method: A couple, where one partner experienced an acquired brain injury poststroke were provided with Integrated Behavioural Couples Therapy for 3-months. The intervention addressed goals identified as necessary by the couple and by the formulation of their individual and relationship difficulties, alongside the goal of promoting relationship continuity. Before and after measures were taken using a battery of six questionnaires to evaluate changes in perceptions of continuity, stress, and other aspects of the relationship. Results: Both quantitative and qualitative data showed that relationship continuity was improved after the therapy, as were the measures of stress and other aspects of the relationship. The stress felt by the person with the acquired brain injury also showed some evidence of improvement. Conclusion: The study found that perceptions of relationship continuity can be improved by therapy and that improving these might have a beneficial impact on the stress felt by the carer, their satisfaction with the relationship and overall levels of conflict and closeness within the relationship. The study suggested the value of further research on enhancing perceptions of continuity in the relationship after an acquired brain injury. Currently, the findings of the study have been used to develop a pilot feasibility study to collect substantive evidence on the impact of the intervention on the couples and assess its feasibility and acceptability, which will help in further developing a specific generalized relationship continuity intervention, that will be beneficial in preventing relationship breakdown in the future.

Keywords: acquired brain injury, couples therapy, relationship continuity, stroke

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Authors: Ming-Jyh Chen, Wen-Ming Huang, Yi-Chu Liu, Li-Hui Yang

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Introduction: Social responsibility is the key to sustainable organizational development. Under the ground Green Health Hospital Declaration signed by our superintendent, we have launched comprehensive energy conservation management in medical services, the community, and the staff’s life. To execute environment-friendly promotion with robust strategies, we build up a low-carbon medical system and community with smart green public construction promotion as well as intensifying energy conservation education and communication. Purpose/Methods: With the support of the board and the superintendent, we construct an energy management team, commencing with an environment-friendly system, management, education, and ISO 50001 energy management system; we have ameliorated energy performance and energy efficiency and continuing. Results: In the year 2021, we have achieved multiple goals. The energy management system efficiently controls diesel, natural gas, and electricity usage. About 5% of the consumption is saved when compared to the numbers from 2018 and 2021. Our company develops intelligent services and promotes various paperless electronic operations to provide people with a vibrant and environmentally friendly lifestyle. The goal is to save 68.6% on printing and photocopying by reducing 35.15 million sheets of paper yearly. We strengthen the concept of environmental protection classification among colleagues. In the past two years, the amount of resource recycling has reached more than 650 tons, and the resource recycling rate has reached 70%. The annual growth rate of waste recycling is about 28 metric tons. Conclusions: To build a green medical system with “high efficacy, high value, low carbon, low reliance,” energy stewardship, economic prosperity, and social responsibility are our principles when it comes to formulation of energy conservation management strategies, converting limited sources to efficient usage, developing clean energy, and continuing with sustainable energy.

Keywords: energy efficiency, environmental education, green hospital, sustainable development

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Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

Procedia PDF Downloads 142

Authors: Anne Y. Faxer, Ellen Olausson, Jens Hagman, Ana Magazinius, Jenny J. Stier, Tommy Fransson, Oscar Enerback

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While electric vehicles (both battery electric vehicles and plug-in hybrids) have been on the market for around 6 years, they are still far from mainstream and the knowledge of them is still low among the public. This is likely one of the reasons that Sweden, having one of the highest penetrations of electric vehicles in Europe, still has a long way to go in reaching a fossil free vehicle fleet. Car dealerships are an important medium that connects consumers to vehicles, but somehow, their role in introducing electric vehicles has not yet been thoroughly studied. Research from other domains shows that salespeople can affect customer decisions in their choice of products. The aim of this study is to explore the role of car dealerships when it comes to promoting electric vehicles. The long-term goal is to understand how they could be a key in the effort of achieving a mass introduction of electric vehicles in Sweden. By emulating the customer’s experience, this study investigates the interaction between car salespeople and customers, particularly examining whether they present electric vehicles as viable options. Covert participatory observations were conducted for data collection from four different brands at in total twelve car dealers. The observers worked in pairs and played the role of a customer with needs that could be matched by an electric vehicle. The data was summarized in observation protocols and analyzed using thematic coding. The result shows that only one of twelve salespeople offered an electric vehicle as the first option. When environmental factors were brought up by the observers, the salespeople followed up with lower fuel consumption internal combustion engine vehicles rather than suggesting an electric vehicle. All salespeople possessed at least basic knowledge about electric vehicles but their interest of selling them were low in most cases. One of the reasons could be that the price of electric vehicles is usually higher. This could be inferred from the finding that salespeople tend to have a strong focus on price and economy in their dialogues with customers, regardless which type of car they were selling. In conclusion, the study suggests that car salespeople have the potential to help the market to achieve mass introduction of electric vehicles; however, their potential needs to be exploited further. To encourage salespeople to prioritize electric vehicles in the sales process, right incentives need to be in place.

Keywords: car dealerships, covert participatory observation, customer perspective , electric vehicle, market penetration

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Authors: Sandra So, Mohd Roslan Ismail, Safurah Jaafar

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With the rapid proliferation of data in healthcare has provided an opportune platform creation of Artificial Intelligence (AI). AI has brought a paradigm shift for healthcare professionals, promising improvement in delivery and quality. This study aims to determine the perception of healthcare personnel on perceived ease of use, perceived usefulness, and subjective norm toward attitude for artificial intelligence acceptance. A cross-sectional single institutional study of employees’ perception of adopting AI in the hospital was conducted. The survey was conducted using a questionnaire adapted from Technology Acceptance Model and a four-point Likert scale was used. There were 96 or 75.5% of the total population responded. This study has shown the significant relationship and the importance of ease of use, perceived usefulness, and subjective norm to the acceptance of AI. In the study results, it concluded that the determining factor to the strong acceptance of AI in their practices is mostly those respondents with the most interaction with the patients and clinical management.

Keywords: artificial intelligence, machine learning, perceived ease of use, perceived usefulness, subjective norm

Procedia PDF Downloads 231

Authors: S. Kawther, C. Marshall

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Educational neuroscience has the intention of transforming research findings of the underpinning neural processes of learning to educational practices. A main criticism of the field, hitherto, is that less focus has been put on studying the in-progress practical application of these findings. Therefore, this study aims to gain a better understanding of teachers’ perceptions of the practical application and utilization of brain knowledge. This was approached by investigating the answer to 'What are the facilitators and barriers for bringing research from neuroscience to bear on education?'. Following a qualitative design, semi-structured interviews were conducted with 12 teachers who had a proficient course in educational neuroscience. Thematic analysis was performed on the transcribed data applying Braun & Clark’s steps. Findings emerged with four main themes: time, knowledge, teacher’s involvement, and system. These themes revealed that some effective brain-based practices are being engaged in by the teachers. However, the lack of guidance and challenges regarding this implementation were also found. This study discusses findings in light of the development of educational neuroscience implementation.

Keywords: brain-based, educational neuroscience, neuroeducation, neuroscience-informed

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Authors: Marianna Maiaru, Gregory M. Odegard, Josh Kemppainen, Ivan Gallegos, Michael Olaya

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Ceramic matrix composites (CMCs) are typically used in applications that require long-term mechanical integrity at elevated temperatures. CMCs are usually fabricated using a polymer precursor that is initially polymerized in situ with fiber reinforcement, followed by a series of cycles of pyrolysis to transform the polymer matrix into a rigid glass or ceramic. The pyrolysis step typically generates volatile gasses, which creates porosity within the polymer matrix phase of the composite. Subsequent cycles of monomer infusion, polymerization, and pyrolysis are often used to reduce the porosity and thus increase the durability of the composite. Because of the significant expense of such iterative processing cycles, new generations of CMCs with improved durability and manufacturability are difficult and expensive to develop using standard Edisonian approaches. The goal of this research is to develop a computational process-modeling-based approach that can be used to design the next generation of CMC materials with optimized material and processing parameters for maximum strength and efficient manufacturing. The process modeling incorporates computational modeling tools, including molecular dynamics (MD), to simulate the material at multiple length scales. Results from MD simulation are used to inform the continuum-level models to link molecular-level characteristics (material structure, temperature) to bulk-level performance (strength, residual stresses). Processing parameters are optimized such that process-induced residual stresses are minimized and laminate strength is maximized. The multiscale process modeling method developed with this research can play a key role in the development of future CMCs for high-temperature and high-strength applications. By combining multiscale computational tools and process modeling, new manufacturing parameters can be established for optimal fabrication and performance of CMCs for a wide range of applications.

Keywords: digital engineering, finite elements, manufacturing, molecular dynamics

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

Procedia PDF Downloads 234

Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: Peli̇n Yilmaz, Gi̇zemnur Yildiz Uysal, Emi̇ne Bi̇rci̇, Berk Özcan, Burak Koca, Ehsan Tuzcuoğlu, Fati̇h Kasap

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Development of Energy Efficient Programs (EEP) is one of the most significant trends in the wet appliance industry of the recent years. Thanks to the EEP, the energy consumption of a washing machine as one of the most energy-consuming home appliances can shrink considerably, while its washing performance and the textile hygiene should remain almost unchanged. Here in, the goal of the present study is to achieve an optimum EEP algorithm providing excellent textile hygiene results as well as cleaning performance in a domestic washing machine. In this regard, steam-pretreated cold wash approach with a combination of innovative algorithm solution in a relatively short washing cycle duration was implemented. For the parametric study, steam exposure time, washing load, total water consumption, main-washing time, and spinning rpm as the significant parameters affecting the textile hygiene and cleaning performance were investigated within a Design of Experiment study using Minitab 2021 statistical program. For the textile hygiene studies, specific loads containing the contaminated cotton carriers with Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa bacteria were washed. Then, the microbial removal performance of the designed programs was expressed as log reduction calculated as a difference of microbial count per ml of the liquids in which the cotton carriers before and after washing. For the cleaning performance studies, tests were carried out with various types of detergents and EMPA Standard Stain Strip. According to the results, the optimum EEP program provided an excellent hygiene performance of more than 2 log reduction of microorganism and a perfect Washing Efficiency Index (Iw) of 1.035, which is greater than the value specified by EU ecodesign regulation 2019/2023.

Keywords: washing machine, energy efficient programs, hygiene, washing efficiency index, microorganism, escherichia coli, staphylococcus aureus, pseudomonas aeruginosa, laundry

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Authors: German Hernandez-Alonso, Antonio Lazcano, Arturo Becerra

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Until today, viruses remain controversial and poorly understood; about their origin, this problem represents an enigma and one of the great challenges for the contemporary biology. Three main theories have tried to explain the origin of viruses: regressive evolution, escaped host gene, and pre-cellular origin. Under the perspective of the escaped host gene theory, it can be assumed a cellular origin of viral components, like protein RNA-binding domains. These universal distributed RNA-binding domains are related to the RNA metabolism processes, including transcription, processing, and modification of transcripts, translation, RNA degradation and its regulation. In the case of viruses, these domains are present in important viral proteins like helicases, nucleases, polymerases, capsid proteins or regulation factors. Therefore, they are implicated in the replicative cycle and parasitic processes of viruses. That is why it is possible to think that those domains present low levels of divergence due to selective pressures. For these reasons, the main goal for this project is to create a catalogue of the RNA-binding domains found in all the available viral proteomes, using bioinformatics tools in order to analyze its evolutionary process, and thus shed light on the general virus evolution. ProDom database was used to obtain larger than six thousand RNA-binding domain families that belong to the three cellular domains of life and some viral groups. From the sequences of these families, protein profiles were created using HMMER 3.1 tools in order to find distant homologous within greater than four thousand viral proteomes available in GenBank. Once accomplished the analysis, almost three thousand hits were obtained in the viral proteomes. The homologous sequences were found in proteomes of the principal Baltimore viral groups, showing interesting distribution patterns that can contribute to understand the evolution of viruses and their host-virus interactions. Presence of cellular RNA-binding domains within virus proteomes seem to be explained by closed interactions between viruses and their hosts. Recruitment of these domains is advantageous for the viral fitness, allowing viruses to be adapted to the host cellular environment.

Keywords: bioinformatics tools, distant homology, RNA-binding domains, viral evolution

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Medani Prasad Rijal

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Forest itself is a factory as well as product. It supplies tangible and intangible goods and services. It supplies timber, fuel wood, fodder, grass leaf litter as well as non timber edible goods and medicinal and aromatic products additionally provides environmental services. These environmental services are of local, national or even global importance. In Nepal, more than 19 thousands community forests are providing environmental service in less economic benefit than actual efficiency. There is a risk of cost of management of those forest exceeds benefits and forests get converted to open access resources in future. Most of the environmental goods and services do not have markets which mean no prices at which they are available to the consumers, therefore the valuation of these services goods and services establishment of paying mechanism for such services and insure the benefit to community is more relevant in local as well as global scale. There are few examples of carbon trading in domestic level to meet the country wide emission goal. In this contest, the study aims to explore the public attitude towards carbon offsetting and their responsibility over service providers. This study helps in promotion of environment service awareness among general people, service provider and community forest. The research helps to unveil the carbon pool scenario in community forest and willingness to pay for carbon offsetting of people who are consuming more energy than general people and emitting relatively more carbon in atmosphere. The study has assessed the carbon pool status in two community forest and valuated carbon service from community forest through willingness to pay in Dharan municipality situated in eastern. In the study, in two community forests carbon pools were assessed following the guideline “Forest Carbon Inventory Guideline 2010” prescribed by Ministry of Forest and soil Conservation, Nepal. Final outcomes of analysis in intensively managed area of Hokse CF recorded as 103.58 tons C /ha with 6173.30 tons carbon stock. Similarly in Hariyali CF carbon density was recorded 251.72 mg C /ha. The total carbon stock of intensively managed blocks in Hariyali CF is 35839.62 tons carbon.

Keywords: carbon, offsetting, sequestration, valuation, willingness to pay

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Authors: Jo Mitchell, Daniel Johnson

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MindMax is a digital community and learning platform built to maximise the wellbeing and resilience of AFL Players and Australian men. The MindMax application engages men, via their existing connection with sport and video games, in a range of wellbeing ideas, stories and actions, because we believe fit minds, kick goals. MindMax is an AFL Players Association led project, supported by a Movember Foundation grant, to improve the mental health of Australian males aged between 16-35 years. The key engagement and delivery strategy for the project was digital technology, sport (AFL) and video games, underpinned by evidenced based wellbeing science. The project commenced April 2015, and the expected completion date is March 2017. This paper describes the conceptual model underpinning product development, including progress, key learnings and challenges, as well as the research agenda. Evaluation of the MindMax project is a multi-pronged approach of qualitative and quantitative methods, including participatory design workshops, online reference groups, longitudinal survey methods, a naturalistic efficacy trial and evaluation of the social and economic return on investment. MindMax is focused on the wellness pathway and maximising our mind's capacity for fitness by sharing and promoting evidence-based actions that support this. A range of these ideas (from ACT, mindfulness and positive psychology) are already being implemented in AFL programs and services, mostly in face-to-face formats, with strong engagement by players. Player's experience features strongly as part of the product content. Wellbeing science is a discipline of psychology that explores what helps individuals and communities to flourish in life. Rather than ask questions about illness and poor functioning, wellbeing scientists and practitioners ask questions about wellness and optimal functioning. While illness and wellness are related, they operate as separate constructs and as such can be influenced through different pathways. The essential idea was to take the evidence-based wellbeing science around building psychological fitness to the places and spaces that men already frequent, namely sport and video games. There are 800 current senior AFL players, 5000+ past players, and 11 million boys and men that are interested in the lives of AFL Players; what they think and do to be their best both on and off field. AFL Players are also keen video gamers – using games as one way to de-stress, connect and build wellbeing. There are 9.5 million active gamers in Australia with 93% of households having a device for playing games. Video games in MindMax will be used as an engagement and learning tool. Gamers (including AFL players) can also share their personal experience of how games help build their mental fitness. Currently available games (i.e., we are not in the game creation business) will also be used to motivate and connect MindMax participants. The MindMax model is built with replication by other sport codes (e.g., Cricket) in mind. It is intended to not only support our current crop of athletes but also the community that surrounds them, so they can maximise their capacity for health and wellbeing.

Keywords: Australian football league, digital application, positive psychology, wellbeing

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Authors: Yogendra Sisodia

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Researchers are becoming more interested in extracting useful information from legal documents thanks to the development of large-scale language models in natural language processing (NLP), and deep learning has accelerated the creation of powerful text mining models. Legal fields like contracts benefit greatly from semantic text search since it makes it quick and easy to find related clauses. After collecting sentence embeddings, it is relatively simple to locate sentences with a comparable meaning throughout the entire legal corpus. The author of this research investigated two pre-trained language models for this task: MiniLM and Roberta, and further fine-tuned them on Legal Contracts. The author used Multiple Negative Ranking Loss for the creation of sentence transformers. The fine-tuned language models and sentence transformers showed promising results.

Keywords: legal contracts, multiple negative ranking loss, natural language inference, sentence transformers, semantic textual similarity

Procedia PDF Downloads 112

Authors: Lunliang Zhong, Bin Duan

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The undergraduate graduation project is a vital part of the higher education curriculum, crucial for engineering accreditation. Current evaluations often summarize data without identifying underlying issues. This study applies the Peter-Clark algorithm to analyze causal relationships within the graduation project data of an Electronics and Information Engineering program, creating a causal model. Structural equation modeling confirmed the model's validity. The analysis reveals key teaching stages affecting project success, uncovering problems in the process. Introducing causal discovery and inference into project evaluation helps identify issues and propose targeted improvement measures. The effectiveness of these measures is validated by comparing the learning outcomes of two student cohorts, stratified by confounding factors, leading to improved teaching quality.

Keywords: causal discovery, causal inference, continuous improvement, Peter-Clark algorithm, structural equation modeling

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Authors: Rania Hanafi Mahmoud Said, Rasha Mohamed Taha

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Background: The use of nanoparticles for medication delivery offers the possibility of avoiding the negative effects of systemic antibiotic dosing as well as antibiotic resistance in bacteria. Aim of the study: The goal of this study was to see the efficiency of local administration of tetracycline loaded on nano chitosan in the treatment of the induced infection of the albino rats gingiva with Porphyromonas gingivalis through Immunohistochemical localization of Interleukin-1beta (IL-1β) as a proinflammatory cytokine.Material and methods: Fifty adult male albino rats 150 - 180 grams body weight used in this investigation. Any changes in rats’ weights were detected. The male albino rats were divided haphazardly into five groups as Group I involved ten rats; they served as a normal negative control group. Group II involved ten rats; they were infected once with P.gingivalis that was injected into the interdental gingiva. Group III involved ten rats; they were subjected to the same procedure as group II and then to daily injection at the site of infection with diluted tetracycline powder. Group IV involved ten rats; they were subjected to the same procedure as group II and then to daily injection of nano Chitosan at the site of injection. Group V involved ten rats; they were subjected to the same procedure as group II and then to daily injection of tetracycline loaded on nano Chitosan at the site of injection. After rats had been euthanized, the extraction and preparation of their gingiva were carried out in order to examine histologically and immunohistochemically. Results: The light microscopic results of groups II, III, and IV showed degeneration represented by swollen epithelial cells, collagen fibers dissociation of the connective tissue of lamina propria, and areas of basement membrane discontinuation, while groups I and V showed an almost normal histological picture of gingival tissue. Immunohistochemical results showed a significant difference in Group II and III when compared to control. No significant difference appears in group V when compared to the control (group I). Conclusion: Using nanochitosan as a carrier for tetracycline is a new technology to get over the increasing resistance of tetracycline.

Keywords: immunohistochemistry, P.gingivalis, nano-chitosan, tetracycline, periodontitis

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Authors: Leijun Zhang

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Reading literacy has become a powerful tool for academic success and an essential goal of education. The ability to read is not only fundamental for pupils’ academic success but also a prerequisite for successful participation in today’s vastly expanding multi-literate textual environment. It is also important to recognize that, in many educational settings, students are expected to learn a foreign/second language for successful participation in the increasingly globalized world. Therefore, it is crucial to help learners become skilled foreign-language readers. Research indicates that students’ reading comprehension can be significantly improved through explicit instruction of multiple reading strategies. Despite the wealth of research on how to enhance learners’ reading comprehension achievement by identifying an enormous range of reading strategies and techniques for assisting students in comprehending specific texts, relatively scattered studies have centered on whether these reading comprehension strategies and techniques are used in classrooms, especially in Chinese academic settings. Given the central role of ‘the teacher’ in reading instruction, the study investigates the degree of importance that EFL teachers attach to reading comprehension strategies and their classroom employment of those strategies in secondary schools in China. It also explores the efficiency of reading strategy instruction on pupils’ reading comprehension performance. As a mix-method study, the analysis drew on data from a quantitative survey and interviews with seven teachers. The study revealed that the EFL teachers had positive attitudes toward the use of cognitive strategies despite their insufficient knowledge about and limited attention to the metacognitive strategies and supporting strategies. Regarding the selection of reading strategies for instruction, the mandated curriculum and high-stakes examinations, text features and demands, teaching preparation programs and their own EFL reading experiences were the major criteria in their responses, while few teachers took into account the learner needs in their choice of reading strategies. Although many teachers agreed upon the efficiency of reading strategy instruction in developing students’ reading comprehension competence, three challenges were identified in their implementation of the strategy instruction. The study provides some insights into reading strategy instruction in EFL contexts and proposes implications for curriculum innovation, teacher professional development, and reading instruction research.

Keywords: reading comprehension strategies, EFL reading instruction, language teacher cognition, teacher education

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Authors: Raquel Galante, Marina Braga, Daniela Ghisleni, Terezinha J. A. Pinto, Rogério Colaço, Ana Paula Serro

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The sensitive nature of soft biomaterials, such as hydrogels, renders their sterilization a particularly challenging task for the biomedical industry. Widely used contact lenses are now studied as promising platforms for topical corneal drug delivery. However, to the best of the authors knowledge, the influence of sterilization methods on these systems has yet to be evaluated. The main goal of this study was to understand how different pairs drug-hydrogel would interact under an ozone-based sterilization method in comparison with two conventional processes (steam heat and gamma irradiation). For that, Si-Hy containing hydroxylethyl methacrylate (HEMA) and [tris(trimethylsiloxy)silyl]propyl methacrylate (TRIS) was produced and soaked in different drug solutions, commonly used for the treatment of ocular diseases (levofloxacin, chlorhexidine, diclofenac and timolol maleate). The drug release profiles and main material properties were evaluated before and after the sterilization. Namely, swelling capacity was determined by water uptake studies, transparency was accessed by UV-Vis spectroscopy, surface topography/morphology by scanning electron microscopy (SEM) and mechanical properties by performing tensile tests. The drug released was quantified by high performance liquid chromatography (HPLC). The effectiveness of the sterilization procedures was assured by performing sterility tests. Ozone gas method led to a significant reduction of drug released and to the formation of degradation products specially for diclofenac and levofloxacin. Gamma irradiation led to darkening of the loaded Si-Hys and to the complete degradation of levofloxacin. Steam heat led to smoother surfaces and to a decrease of the amount of drug released, however, with no formation of degradation products. This difference in the total drug released could be the related to drug/polymer interactions promoted by the sterilization conditions in presence of the drug. Our findings offer important insights that, in turn, could be a useful contribution to the safe development of actual products.

Keywords: drug delivery, silicone hydrogels, sterilization, gamma irradiation, steam heat, ozone gas

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Authors: Fiza Azam, Sahar Zia, Fatima Nazir Ali, Aysha Hanif

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Health is a fundamental human right, and a healthy population is essential for the prosperity and sustainable development of any country. This research is aligned with United Nations' Goal 3: Good Health and Well-being. It aims to assess and rank key health indicators across selected South Asian countries. The study focuses on urban areas in these nations, drawing on data from the World Bank’s primary collection of relevant indicators and specific health determinants outlined by the World Health Organization (WHO). These determinants include the physical environment, income and social status, education, social support networks, and personal behavior. To evaluate disparities in urban health across the region, the Urban Health Index (UHI) developed by Georgia State University, USA, is employed, followed by a mapping technique including visualization through a choropleth map to identify the pattern of spatial variations in our key variables, such as socioeconomic indicators across the region. This index serves as a comparative tool to rank health outcomes, where higher UHI values indicate better health conditions. The findings reveal notable disparities across South Asia. Afghanistan, with the lowest UHI score of 0.0423, ranks first, indicating the least favorable urban health conditions. Pakistan follows with a UHI score of 0.1190. Bangladesh and India rank third and fourth with UHI scores of 0.3099 and 0.3250, respectively. The Maldives and Sri Lanka rank fifth and sixth, with UHI scores of 0.3432 and 0.3495. Bhutan is ranked seventh with a score of 0.4750. Nepal, with a UHI score of 0.5012, ranks eighth, indicating the best urban health conditions among the countries studied. The findings of this research are crucial for addressing health disparities, improving living conditions, and enhancing social well-being in the region. These insights can inform policy measures aimed at reducing inequalities and promoting sustainable urban health in South Asia.

Keywords: urban health index, health disparities, sustainable development, South Asia, World Health Organization, United Nations, living conditions, public health

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Authors: Fernando Valerio-Holguin

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Over the recent three decades, the tourism industry in the Dominican Republic has had an enormous impact on the country’s culture. The arrival of tourists from Germany, France, Italy, Russia and the United States has rewritten Dominican cultural identity and created a cultural palimpsest in the areas of language, gastronomy, habits, fashion, values, and gender relations. As a consequence of tourism, a prostitution network has flourished across the country. In the film Sand Dollars (2015) directed by Laura Amelia Guzmán and Israel Cárdenas, Noelí (Janet Mojica), a young mulatto woman, altogether with her boyfriend (Ricardo Ariel Toribio), strips tourists of dollars and euro through prostitution. One of her frequent clients is Anne, a mature French woman (Geraldine Chaplin). While Noeli’s goal is to get all the euros she can, Anne falls in love with her and tries to bring her to France. Both the content of the film and its cinematographic languages are analyzed in light of theory of coloniality. This concept shows how European and American tourism, through the power of money, perpetuates colonial discourse, i. e., how race and ethnocentrism permeate cultural activities in their former colonies. Moreover, in the content analysis of the film the concepts of exchange value and fetishism are crucial to understanding how the colonial body becomes sexual commodity. They facilitate grasping the film’s inequity in terms of power in the relationship between the two women: the white old European woman and the young, poor, third-world mulatta. Even though the film attempts to break away from compulsory heterosexuality, the power relation between the two women persists due to the presence of the axis of race, ethnicity, age and gender. Both the novel Les dollars des sables written by Jean-Noel Pancrazi, and the film Sand Dollars offer an interesting insight into sex tourism and coloniality and shed additional light on the power relations between the former colonizers and its colonies.

Keywords: coloniality, ethnocentrism, exchange value, Europe, fetishism, money, power, prostitution, sex tourism, United States of America

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Authors: Sheraz Akhtar

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In recent years, a massive influx of refugees into developing countries has placed significant constraints on the host government’s capacities to provide social services, including education, to all. As a result, the refugee communities often find themselves deprived of their rights to education in these host countries, particularly for those who to live outside camps in urban locations. While previous research has examined the educational experiences of refugees who have resettled in developed nations, there remains a dearth of research on the educational experiences of urban refugees in developing nations. This study examines this issue through a case study of Pakistani Christian refugees living in urban settings in Thailand. Using a combination of observations within community learning centres set up by international non-government organisations (INGOs) working with these communities, and interviews with young Pakistani Christian refugees and their families, the research aims to give greater voice to the Pakistani Christian refugee community living in Thailand, and better understand their educational aspirations.

Keywords: Education, Developing Countries , INGOs, Urban Refugees

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Authors: Fatna Benmessaoud, Mohammed Cheikh, Vencent Velay, Vanessa Vedal, Farhad Rezai-Aria, Christine Boher

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The global mechanical behavior of materials is strongly linked to their microstructure, especially their crystallographic texture and their grains morphology. These material aspects determine the mechanical fields character (heterogeneous or homogeneous), thus, they give to the global behavior a degree of anisotropy according the initial microstructure. For these reasons, the prediction of global behavior of materials in relationship with the microstructure must be performed with a multi-scale approach. Therefore, multi-scale modeling in the context of crystal plasticity is widely used. In this present contribution, a phenomenological elasto-viscoplastic model developed in the crystal plasticity context and finite element method are used to investigate the effects of crystallographic texture and grains sizes on global behavior of a polycrystalline equiaxed Ti-6Al-4V alloy. The constitutive equations of this model are written on local scale for each slip system within each grain while the strain and stress mechanical fields are investigated at the global scale via finite element scale transition. The beta phase of Ti-6Al-4V alloy modeled is negligible; its percent is less than 10%. Three families of slip systems of alpha phase are considered: basal and prismatic families with a burgers vector and pyramidal family with a burgers vector. The twinning mechanism of plastic strain is not observed in Ti-6Al-4V, therefore, it is not considered in the present modeling. Nine representative elementary volumes (REV) are generated with Voronoi tessellations. For each individual equiaxed grain, the own crystallographic orientation vis-à-vis the loading is taken into account. The meshing strategy is optimized in a way to eliminate the meshing effects and at the same time to allow calculating the individual grain size. The stress and strain fields are determined in each Gauss point of the mesh element. A post-treatment is used to calculate the local behavior (in each grain) and then by appropriate homogenization, the macroscopic behavior is calculated. The developed model is validated by comparing the numerical simulation results with an experimental data reported in the literature. It is observed that the present model is able to predict the global mechanical behavior of Ti-6Al-4V alloy and investigate the microstructural parameters' effects. According to the simulations performed on the generated volumes (REV), the macroscopic mechanical behavior of Ti-6Al-4V is strongly linked to the active slip systems family (prismatic, basal or pyramidal). The crystallographic texture determines which family of slip systems can be activated; therefore it gives to the plastic strain a heterogeneous character thus an anisotropic macroscopic mechanical behavior. The average grains size influences also the Ti-6Al-4V mechanical proprieties, especially the yield stress; by decreasing of the average grains size, the yield strength increases according to Hall-Petch relationship. The grains sizes' distribution gives to the strain fields considerable heterogeneity. By increasing grain sizes, the scattering in the localization of plastic strain is observed, thus, in certain areas the stress concentrations are stronger than other regions.

Keywords: microstructural parameters, multi-scale modeling, crystal plasticity, Ti-6Al-4V alloy

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Authors: André M. Senna, Mary L. G. S. Senna, Rosa M. Machado-de-Sena

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One of the great challenges presented in educational practice is how to ensure the students not only acquire knowledge of training courses throughout their academic life, but also how to apply it in their current professional activities. Consequently, aiming to incite changes in the education system of healthcare professionals noticed the inadequacy of the training providers to solve the social problems related to health, the education related to these procedures should initiate in the earliest years of process. Following that idea, there is another question that needs an answer: If the change in the education should start sooner, in the period of basic training of healthcare professionals, what guidelines should a permanent education program incorporate to promote changes in an already established system? For this reason, the objective of this paper is to present different views of the teaching-learning process, with the purpose of better understanding the behavior adopted by healthcare professionals, through bibliographic study. The conclusion was that more than imparting knowledge to the individual, a larger approach is necessary on permanent education programs concerning the performance of professional health services in order to foment significant changes in education.

Keywords: Health Education, continuing education, training, behavior

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